WCC Digital Report

IMD World Digital Competitiveness Ranking

2025

Reconfiguring digital strategies amid trade fragmentation

World Competitiveness Center

wccinfo@imd.org

Preface

The IMD World Competitiveness Center has long played a role in improving nations’ abilities to generate sustainable value and improve the quality of life for its citizens, through in-depth data and analysis.

In 2017, we bolstered our ability to do this by creating a digital ranking. That year, blockchain technology was sparking great interest, and voice assistants like Alexa, Siri, and Google Assistant were starting to bring AI technology into the home and workplace. Fast forward eight years, and the digital economy now accounts for 15% of world GDP, with AI integrated at scale into healthcare, finance, education, and manufacturing.

The digital economy might not seem dependent on traditional trade flows due to its intangibility. But this year’s ranking finds that trade wars are affecting it – and in turn dictating digital competitiveness at both national and firm levels. In addition, the 2025 ranking takes a microscopic lens to industry trends in today’s digital geopolitical sphere, using data from the IMD Executive Opinion Survey. Readers can therefore not only understand their country’s mechanisms, but those of their sector on a global level.

Global trade fragmentation is affecting the digital competitiveness of nations in three main ways: firstly, it’s creating winners and losers in digital infrastructure (the winners have been investing more in recent years than others, building a better framework, say, for telecoms, internet, or the application of technologies, enabling domestic reliance).

Secondly, while talent remains mobile, people are not entering certain countries in the same numbers due to geopolitical instability. This affects digital competitiveness when domestic policies and regional instability combust into a situation where more talent is leaving the country than entering it. Several of the economies we assess are victims of this and have fallen in our rankings, as my colleagues’ analysis will expose.

Thirdly, in a fragmented world, regulatory advantages are becoming a key determinant of digital competitiveness. Regulatory clarification and safety enable companies and governments to incorporate the technology available as efficiently and effectively as possible. We have the EU, the US, and Southeast Asia recognizing this with certain regulatory improvements.

This year, we’ve added data on AI-related patent publications (from the WIPO Statistics Database) and on annual private investment in artificial intelligence (from Quid, via the Stanford AI Index Report). Namibia, Kenya, and Oman are welcome newcomers.

Our thanks go to our partner institutes for their continued commitment to facilitating this publication, and especially their support in disseminating our survey and supporting our statistical data collection, enabling us to ensure accuracy and local relevance.

Arturo Bris Director IMD World Competitiveness Center

Profiles

The IMD World Competitiveness Center

For more than thirty-five years, the IMD World Competitiveness Center has pioneered research on how countries and companies compete to lay the foundations for sustainable value creation. The competitiveness of nations is probably one of the most significant developments in modern management and IMD is committed to leading the field. The World Competitiveness Center conducts its mission in cooperation with a network of 73 Partner Institutes in 60 countries to provide the government, business and academic communities with the following services:

The IMD World Competitiveness Center Team

Professor Arturo Bris Director

Competitiveness Special Reports

Competitiveness Prognostic Reports

Workshops/Mega Dives on competitiveness

IMD World Competitiveness Yearbook

IMD World Digital Competitiveness Ranking IMD World Talent Ranking

Hinrich-IMD Sustainable Trade Index Smart City Index

José Caballero Senior Economist

Christos Cabolis Chief Economist & Head of Operations

Fabian Grimm Research Specialist

Madeleine Hediger Data Research and Online Services Specialist

Matisse Graf Intern

Jean-François Kaeser IT Consultant (KAESCO Consulting)

Odete Madureira WCC Coordinator

William Milner Associate Director

Chinar Sharma Projects Analyst

Alice Tozer Content Manager

We also have the privilege of collaborating with a unique network of Partner Institutes, and other organizations, which guarantees the relevance of the data gathered.

Contact

e-mail: wccinfo@imd.org Internet: www.imd.org/wcc

Database: https://worldcompetitiveness.imd.org

Partner Institutes

We would like to express our deep appreciation for the contribution of our Partner Institutes, enabling an extensive coverage of competitiveness in their home countries. The following Institutes and people supplied data from national sources and helped distribute the survey questionnaires:

Argentina

Instituto Shaw de Estudios Empresariales, Universidad Católica Argentina http://www.uca.edu.ar

Dr. Marcelo Resico, Director, Shaw Institute for Business Studies (ISEE)

Pilar Agostina Ferreyra, Research Assistant

Australia

CEDA – Committee for Economic Development of Australia http://www.ceda.com.au

Cassandra Winzar, Chief Economist Justine Parker, Media Manager

Austria

Federation of Austrian Industries, Vienna Austrian Institute of Economic Research, Vienna www.iv.at

Dr. Christian Helmenstein, Chief Economist

Mag. Michael Oliver, Economist

Bahrain

Ministry of Finance and National Economy http://www.mofne.gov.bh

Dr. Faisal Hammad, Assistant Undersecretary for Competitiveness & Economic Indicators

Belgium

Federation of Enterprises in Belgium

http://www.feb.be

Dries Vantomme, Attaché Economics & Business Cycle

Botswana

Botswana National Productivity Centre (BNPC), Botswana

http://www.bnpc.bw

Babuya S. Siku, General Manager (Acting)

Letsogile Batsetswe, Experienced Research Consultant

Brazil

Fundação Dom Cabral Innovation, AI and Digital Technologies Center http://www.fdc.org.br

Hugo Tadeu, Director and Professor Jersone Tasso Moreira Silva, Associate Professor

Bruna Diniz, Researcher Kaua Kenner, Researcher

Bulgaria

Bulgarian Chamber of Commerce and Industry http://www.bcci.bg

Boryana Abadzhieva, Head of Economic Analysis and Policy Department

Magdalena Koshulyanova, Junior expert, Economic Analysis and Policy Department

Applied Research and Communications Fund, Center for the Study of Democracy, Sofia

http://www.arcfund.net; http://www.csd.eu

Atanas Nedyalkov, Senior Analyst, Innovation and Finance, Applied Research and Communications Fund

Ruslan G. Steanov, Program Director and Chief Economist, Center for the Study of Democracy

Daniela Mineva, Senior Analyst, Geoeconomics Program, Center for the Study of Democracy

Canada

Information and Communications Technology Council (ICTC)

http://www.ictc-ctic.ca

Anne M. Patterson, Chief Research and Communications Officer

Chile

Universidad de Chile, Facultad de Economía y Negocios (FEN)

http://www.fen.uchile.cl

Dr. Enrique Manzur, Vice Dean

Dr. Sergio Olavarrieta, Vice President

Dr. Pedro Hidalgo, Associate Professor

China

China Institute for Development Planning, Tsingua University http://www.cidp.tsinghua.edu.cn

Dr. Gong Pu, Assistant Professor and Director of Research

Dr. Yang, Yongheng, Professor & Deputy Dean Dr. Wang, Youqiang, Professor Huang, Suyuan, Vice Director of Research Bi, Shiyao, MA Candidate Jin, Shiyao, Research Assistant Dr. Lang, Yu, Postdoctoral Fellow Dr. Su, Chaoyang, Postdoctoral Fellow Tang, Yuwen, MA Candidate Yu, Hanying, MA Candidate Zhu, Siyao, PhD Candidate

Colombia

National Planning Department http://www.dnp.gov.co

Alexander Lopez Maya, General Director, Department of National Planning (DNP)

Mónica Lorena Ortíz Medina, Technical Director, Innovation and Private Sector Development - DNP

Croatia

National Competitiveness Council

Ivan Mišetić, Acting President

Biserka Sladović, Advisor Hrvoje Stojić, Chief Economist

Croatian Employers’ Association https://www.hup.hr

Iva Tomic, PhD, Chief Economist

Cyprus

Cyprus Employers and Industrialists Federation http://www.oeb.org.cy

Antonis Frangoudis

Economics Research Centre, University of Cyprus http://ucy.ac.cy/erc/en

Sofronis Clerides, Professor of Economics

Nicoletta Pashourtidou, Assistant Director

Denmark

Confederation of Danish Industry http://www.danskindustri.dk/english

Allan Sørensen, Chief Economist

Estonia

Estonian Institute of Economic Research (EKI) http://www.ki.ee/en

Peeter Raudsepp, Member of the Board

Bruno Pulver, Member of the Board

Enterprise Estonia (EAS) https://eis.ee/en

Helery Tasane, Head of Strategy and Analysis

Finland

ETLA Economic Research www.etla.fi

Dr. Ville Kaitila, Researcher

Päivi Puonti, Head of Forecasting Aki Kangasharju, Managing Director

Ghana

Management Development and Productivity Institute http://www.mdpi.gov.gh

Professor Elijah Yendaw, Ag. Director General

Ethel Ansah-Antwi, Ag. Director, Consultancy Unit

Stephen Asirifi Essel, Consultancy Unit

Greece

Federation of Industries of Greece (SBE), Thessaloniki sbe.org.gr

Dr. Christos Georgiou, Director Research & Documentation Dept.

Constantinos Styliaras, Economist, Research and Documentation Department

Foundation for Economic and Industrial Research (FEIR/ IOBE), Athens

http://iobe.gr/default_en.asp

Sophia Stavraki, Research Associate

Hong Kong SAR Hong Kong Trade Development Council http://www.hktdc.com

Wing Chu, Principal Economist Cherry Yeung, Senior Economist Cathy Kwan, Senior Research Executive

Hungary

ICEG European Center, Budapest http://icegec.org

Renata Jaksa, Director Oliver Kovacs, Senior Research Fellow

National University of Public Service www.uni-nke.hu

Dr. Magdolna Csath, Private Professor

Iceland

Icelandic Chamber of Commerce, Reykjavik http://www.chamber.is

Björn Brynjúlfur Björnsson, Managing Director

Gunnar Úlfarsson, Chief Economist

India

National Productivity Council, New Delhi http://www.npcindia.gov.in

Rajesh Sund, Director & Group Head (Economic Services)

Indonesia

Lembaga Management, Faculty of Economics and Business, Universitas Indonesia (LM FEB UI), Jakarta www.lmfebui.com

Prof. Dr. Ir. T. Ezni Balqiah, M.E., M.H., Director of Research and Consulting

Dr. Nurdin Sobari, Senior Researcher

Dr. Willem A. Makaliwe, Senior Researcher Bayuadi Wibowo, Senior Researcher

AA Dwi Mustia Dewi, Researcher

Annisa Pratiwi, Researcher

NuPMK Consulting, Jakarta http://nupmk.co.id

Tini Moeis, Managing Director Devi Ria Dinanti, Chief Marketing Officer

Ireland

IDA Ireland, Investment and Development Agency

http://www.idaireland.com Malgorzata Ferraz, Planning Manager

Japan

Keizai Doyukai, Japan Association of Corporate Executives https://www.doyukai.or.jp/en Katsumi Miyazaki

Mitsubishi Research Institute, Inc., Tokyo Research Centre for Policy and Economy

https://www.mri.co.jp/en/index.html

Dr. Hirotsugu Sakai, Research Director

Jordan

Ministry of Planning and International Cooperation http://www.mop.gov.jo

Omar Fanek, National Policies Support Department Director

Mira Mango, Head of the Competitiveness and International Indices Division

Kazakhstan

Economic Research Institute, JSC of the Ministry of National Economy of the Republic of Kazakhstan, Astana

https://eri.kz

Kymbat Akhmetzhanova, Director, Center for Strategic Analysis

Assel Tasbauova, Deputy Director

Natalya Novokshanova, Deputy Director

Aimira Sabugaliyeva, Lead Expert

Kenya

National Productivity and Competitiveness Centre https://saraka.info/ministries/labour-and-social-protection/ labour-and-skill-development/npcc/

George E. G. Njiru, Principal Productivity Officer

Dr. Nahashon Moitaleel, Director

Korea

Korea Chamber of Commerce and Industry (KCCI) http://english.korcham.net/ Ethan Cho, Deputy Director

Korea Institute for International Economic Policy (KIEP) https://www.kiep.go.kr/eng/

Jiyun Lee, Researcher, International Macroeconomics Team

Dr. Hayun Song, Associate Research Fellow, International Macroeconomics Team

Kuwait

Kuwait Anti Corruption Authority (Nazaha)

https://www.nazaha.gov.kw

Dhari Buyabes, Head of International Organizations and Conferences, International Cooperation Department

Latvia

University of Latvia, Faculty of Economic and Social Sciences, Centre for European and Transition Studies - CETS

http://www.lu.lv/cets

Dr. Zane Zeibote, Director

Prof. Dr. Tatjana Muravska, Honorary Director

Lithuania

Innovation Agency Lithuania https://innovationagency.lt

Kotryna Tamoševičienė, Head of Research and Analysis Unit

Indrė Žebrauskaitė, Senior Analyst

Luxembourg

Luxembourg Chamber of Commerce

https://www.cc.lu/en

Sidonie Paris, Senior Economist

Anthony Villeneuve, Senior Economist Christel Chatelain

Malaysia

Malaysia Productivity Corporation http://www.mpc.gov.my

Zahid Ismail, Director General

Dr. Mazrina Mohamed Ibramsah, Deputy Director General

Dr. Mohamad Norjayadi Tamam, Deputy Director General

Wan Fazlin Nadia Wan Osman, Director

Mohammed Alamin Rehan, Director Shanthini Tamadoram

Mexico

Center for Strategic Studies for Competitiveness

http://www.ceec.edu.mx

Carlos Maroto Espinosa, General Manager

Mongolia Economic Policy and Competitiveness Research Center

http://www.ecrc.mn

Tsagaan Puntsag, Founder and Chairman of Board Lakshmi Boojoo, Director General

Odonchimeg Ikhbayar, Deputy Director, Head of Research

Ganbat Chuluun, Research Economist

Tungalag Erdenebat, Research Economist Mungunjiguur Battsolmon, Research Economist

Namibia

Namibia Investment Promotion and Development Board

https://www.nipdb.com

Dr. Nangula Nelulu Uaandja, Chief Executive Officer Margareth Gustavo, Executive: Competitiveness & Branding

Netherlands Confederation of Netherlands Industry and Employers (VNO-NCW), Netherlands www.vno-ncw.nl

Thomas Grosfeld

Tim Zandbergen

New Zealand

Auckland Business Chamber

https://aucklandchamber.co.nz

Simon Bridges, Chief Executive Officer

Nigeria

National Productivity Centre, Nigeria

https://productivity.gov.ng/

Dr. Baffa Babba Dan Agundi, Director-General

Dr. Adejoh David Onuche, Director, Productivity Measurement & Index

Oman

National Competitiveness Office, Oman

https://www.nco.om

Dr. Fahad Rashid Saif Al Jahwari, Director Abdulrahman Al Hinaai, Head of National Account Indicators Department, National Centre for Statistics and Information Jawaher Al Habsi, Statistical Data Analyst

Peru

CENTRUM PUCP

https://centrum.pucp.edu.pe

Percy Marquina, General Director

Dr. Luis Del Carpio, Director of Programs Beatrice Avolio, General Director Victor Fajardo, Researcher José Calsina, Research Assistant

Philippines

Asian Institute of Management R.S.N. Policy Center for Competitiveness (AIM RSN PCC)

https://aim.edu/research-centers/rizalino-s-navarropolicy-center-competitiveness

Prof. Jamil Paolo S. Francisco, Executive Director Christopher Caboverde, Research Manager Hauvre Somova, Economist

Poland

SGH Warsaw School of Economics

https://www.sgh.waw.pl/en

Prof. Marzenna Weresa, Dean

Dr. Anna Dzienis, Adjunct Professor

Portugal

Porto Business School, University of Porto, Porto

https://www.pbs.up.pt

José Esteves, Dean

Cátia Santana, Project Officer

Prof. Álvaro Almeida

Prof. Daniel Bessa

Prof. Filipe Grilo

Prof. José Luís Alvim

Prof. João Loureiro

Prof. Patrícia Teixeira Lopes

Puerto Rico

Puerto Rico Department of Economic Development and Commerce

https://www.desarrollo.pr.gov/

Hon. Sebastián Negrón Reichard, Secretary for Economic Development & Commerce

José L. Rivera Rivera, Economist - Director for Economic Analysis & Business Intelligence

Invest Puerto Rico

https://www.investpr.org

John Bozek, Chief Strategy and Research Officer

Puerto Rico International Competitiveness Center https://www.uagm.edu/es/division-de-negocios-turismo-yemprendimiento

Francisco Montalvo Fiol, Adjunct Professor, Doctoral Program

Qatar

National Planning Council http://www.npc.qa

Ahmed Alsumaiti, Director of International indicator & International Cooperation Dep. Hissa AL-Assiry, Project Manager

Romania

CIT-IRECSON Center of Technological Information https://cit.irecson.ro

Dr. Bogdan Ciocanel, Phd, Director Dan Grigore, Economist

Saudi Arabia

NCC, National Competitiveness Center https://www.ncc.gov.sa/en/Pages/default.aspx

H.E. Dr Eiman AlMutairi, CEO of National Competitiveness Center

Waleed AlRudaian, Vice President

Salman M. AlTukhaifi, General Manager of Analytics & Business Intelligence

Singapore Ministry of Trade and Industry http://www.mti.gov.sg

Singapore Business Federation https://www.sbf.org.sg

Edwin Heng, Director, Research and publishing Lim Kai Yun, Assistant Manager, Research & Publishing

Slovak Republic Institute of Freedom and Enterprise Ján Oravec, Chairman

Slovenia Institute for Economic Research https://www.ier.si/en

Peter Stanovnik, President

Sonja Uršič

University of Ljubljana, School of Economics and Business

http://www.ef.uni-lj.si/en

Mateja Drnovsek, Full Professor

South Africa

Productivity SA

www.productivitysa.co.za

Amelia Naidoo, Acting Chief Executive Officer

Sebolelo Juliet Mashabela, Acting Chief Economist

Spain

Spanish Confederation of Employers

https://www.ceoe.es/es

Edita Pereira, Head of Economic Research Unit

Paloma Blanco, Economic Research Unit

Taiwan (Chinese Taipei)

National Development Council http://www.ndc.gov.tw

Kao, Shien-Quey, Deputy Minister

Chiu-Ying Chiu, Director of Economic Development Department

Wang, Chen-Ya, Executive Officer

Thailand

Thailand Management Association

http://www.tma.or.th

Wanweera Rachdawong, Chief Executive Officer

Pornkanok Wipusanawan, Director TMA Center for Competitiveness

Tossanun Preratipoomsret, Manager, TMA Center for Competitiveness

Türkiye

TUSIAD Turkish Industry and Business Association, Economic Research Department

http://www.tusiad.org

Gizem Öztok Altınsaç, Chief Economist

Yiğit Başat Şimşek, Director

İsmet Tosunoğlu, Economist

İrem Sipahi, Senior Expert

United Arab Emirates Federal Competitiveness and Statistics Centre (FCSC) http://fcsc.gov.ae/

Venezuela

National Council to Investment Promotion (CONAPRI) http://www.conapri.org

Dr. Juan Cabral, Executive Director Jennyn Osorio, Economics Affairs Manager

Lilian Zambrano, Manager of Legal Affairs

User guide

User Guide for the IMD World Digital Competitiveness Ranking

Overall and Breakdown: Digital Rankings

The IMD World Digital Competitiveness Ranking presents the 2025 overall rankings for the 69 economies covered by the WCY. The rankings are calculated on the basis of the 61 ranked criteria: 40 hard and 21 survey data. The countries are ranked from the most to the least digital competitive. The final column shows the improvement or decline from the previous year. The index value or “score” is also indicated for each country.

Selected breakdowns of the IMD World Digital Competitiveness Ranking

In addition to global digital rankings, other rankings are provided to show comparisons based on different perspectives. These digital rankings include countries split by population size (populations above and below 20 million), by GDP per capita to reflect different peer groups (above and below $20,000) and three regional rankings drawn from different geographical areas (Europe-Middle East-Africa, Asia-Pacific and the Americas). Digital Competitiveness Factor Rankings

The global rankings for each of the Digital Competitiveness Factors are then shown as individual ranking tables. Again, the economies are ranked from the most to the least digital competitive and the previous year’s rankings (2024) are shown in brackets. Similar to the Overall Digital Ranking, the values or “scores” are indicated for each Factor. However, there is only one economy that has a score of 100 and one economy with

score of 0 across all four Factors.

Overall Ranking and Digital Competitiveness Factors

This section presents the overall rankings and the 5-year trends for each of the three Digital Competitiveness Factors: Knowledge, Technology and Future Readiness. Thus, the reader is able to analyze the digital evolution of an economy over the past few years relative to the others on a global basis.

Digital Sub-factor Rankings

A summary of the rankings for all nine sub-factors is presented for the 69 economies for 2025. It is possible, at a glance, to determine in what areas of digital competitiveness an economy excels or has particular weaknesses and to make comparisons between countries. These rankings provide a more detailed examination of specific aspects of the digital transformation and can be used to, for example, evaluate the technological framework of a country or support international investment decisions.

We view the rankings as a tool for managers or policy makers to use when they analyze the above questions. Of course, each company must take into consideration the logic of its own economic sector, economic forecasts and its own traditions as well as governments should consider the national identity and value system of their economy.

SWITZERLAND

Digital Competitiveness

Each two-page profile analyses the performance of one of the 69 economies that are included in the IMD World Digital Competitiveness Ranking. The economies are presented in alphabetical order. The term economy signifies an economic entity and does not imply any political independence.

It is possible, in one glimpse, to evaluate the digital evolution of each economy over time and its relative strengths and weaknesses. However, each economy’s particular situation is influenced by its development level, political restraints and social value system.

Page 1: Digital Competitiveness – Overall and factors trends

This page shows the overall, factor and sub-factor ranking performances of the country in 2025, their 5-year trends and a comparison between competitiveness and digital competitiveness rankings. The following indicators are presented:

1. Overall Performance

Overall, factors and sub-factors digital ranking performances of the country in 2025. The direction of the triangles indicates whether there has been an improvement or a decline with respect to the previous year.

2. Overall & Factors – 5 years

The evolution of the overall and factors digital rankings in the past 5 years.

3. Competitiveness and Digital Rankings

Comparison of the country’ performances in the World Competitiveness Ranking and World Digital Competitiveness Ranking in the last 5 years.

4. Peer Group Rankings

Based on geographical region and population size.

SWITZERLAND

Digital Competitiveness

Page 2: Factors breakdown & Strengths and Weaknesses

This page shows the country’s performance over time for each of the nine sub-factors composing the three Digital Competitiveness Factors (Knowledge, Technology and Future Readiness) and their 61 criteria rankings for 2025.

1. Factors Breakdown

Shows the 5-years evolution of the sub-factors rankings composing the three factors of Knowledge, Technology and Future Readiness.

2. Strengths and Weaknesses

This section highlights the economy’s strongest and weakest criteria included in the World Digital Competitiveness Ranking. The triangles identify the five top criteria in which the economy ranks best (strengths ) and the five criteria in which its performance is the worst (weaknesses ) compared to the other countries included in the WCY sample. The selection of indicators is determined by the standard deviation values (STD) of the country for that specific criteria. In other words, the criteria selected represent the highest STD values and the lowest STD values among the 61 indicators composing the World Digital Competitiveness Ranking and can thus be considered the digital competitive advantages and disadvantages of the economy.

The full criteria names can be found in the Appendix and the statistical tables are available for subscribers of the IMD World Competitiveness Online

It is important to note that what constitutes a strength or weakness is relative to each economy’s circumstances or development. Also, the ranking position of a country may not necessarily improve or decline as a consequence of its own evolution since it is always relative to the performance of the other economies. Therefore, an improvement may not be reflected by a higher ranking position if other economies have performed better for the criterion in question. The same can be said for any declines in performance – the economy’s ranking position relative to the others may or may not fall, depending on how the other economies have performed.

Appendices

Appendix 1: Composition of sub-regions and regions

Austria Italy

Belgium Luxemburg

Cyprus Netherlands

Denmark Norway

Finland Portugal

Western Europe

Eastern Europe

France Spain

Germany Sweden

Greece Switzerland

Iceland United Kingdom

Ireland

Bulgaria Lithuania

Czech Republic Poland

Estonia Romania

Croatia Slovenia

Hungary Slovak Republic

Latvia

Bahrain Nigeria

Botswana Oman

Ghana Qatar

Western Asia & Africa

Jordan Saudi Arabia

Kenya South Africa

Kuwait Türkiye

Namibia UAE

Europe, Middle East & Africa

Ex-CIS & Central Asia

Eastern Asia

Southern Asia & The Pacific

North America

Kazakhstan

Mongolia

China Korea Republic Hong Kong SAR Taiwan (Chinese Taipei)

Japan

Australia New Zealand

India Philippines

Indonesia

Singapore

Malaysia Thailand

Canada Puerto Rico

Mexico USA

South America Argentina Colombia Brazil Peru

Chile Venezuela

Asia & Pacific

Reconfiguring digital strategies amid trade fragmentation National and firm-level challenges

The current world (dis)order is characterized by escalating geopolitical rivalries, contested trade norms, and fragmented institutional frameworks, which are together shaping all aspects of economic life and having particularly deep effects on firms operating across borders. Trade conflicts were once thought to be confined to disputes over tariffs or quotas, but are now clearly extending deep into the intangible roots of the digital economy: intellectual property, data flows, technical standards, and strategic technologies.

As a result, the competitiveness environment in which firms operate is no longer defined solely by market forces or innovation capabilities, but increasingly by the volatility of trade relations and the growing differences among countries and regions in the ways they regulate, develop, and adopt technology. In such a context, digital strategy is far from protected from external disruptions. Moreover, it is structurally embedded within such disruptions.

Access to technology and overseas markets, as well as research collaboration and international talent mobility, have become subject to a complex web of bilateral restrictions, retaliatory policies, and non-tariff barriers. This new level of institutional fragmentation erodes the predictability on which digital competitiveness has historically relied. Firms, particularly those embedded in global value chains or reliant on platform interoperability, face major strategic consequences. Their digital ambitions are now filtered through questions of geopolitical alignment, jurisdictional compliance, and technological selfsufficiency.

Moreover, the ripple effects extend beyond technologyintensive sectors. Even service-oriented firms must contend with localization demands (e.g., digital platforms built or hosted locally), dual-use restrictions (e.g., export controls on technologies with commercial and potential military use), and uncertainty in international standards recognition. In short, the

ongoing disintegration of the global economic order is not a background variable, but a hindrance to strategic viability.

José Caballero

Senior Economist

IMD World Competitiveness Center

As firms evaluate their digital strategies amid mounting trade tensions, the boundaries between economic planning and geopolitical risk management continue to blur. Understanding this multi-domain disruption is essential for analyzing how digital competitiveness is redefined in the current international economy. Not through efficiency and scale alone, rather, through resilience, adaptability, and institutional effectiveness across an increasingly contested global context.

With this scenario in mind, we assess in greater detail the impact of several strategic domains on digital strategy and how trade tensions are affecting them. These domains include market access and expansion, access to technology, regulatory environment, innovation and R&D, and talent acquisition and retention. The analysis of each domain is two-fold. First, we examine their fundamental role in digital strategy. Second, we present highlights of national rankings, regional patterns, and sectoral dynamics relevant to each domain. Such an assessment of the impact of trade fragmentation is based on evidence drawn from the perspectives of business leaders who participated in IMD’s Executive Opinion Survey.

Indeed, a core part of the data forming the results of the IMD Digital Competitiveness Ranking comes from the survey responses from 6,162 senior executives in 69 countries. By focusing on a specific section of this survey, we can delve deeper into how trade conflict is affecting the five strategic domains of digital strategy at the firm level.

The survey asked respondents: “In which areas do international trade conflicts have the most impact on the digital strategy of your organization?” They could choose any number of the following answers: market access and expansion, access to technology, the regulatory environment, innovation and R&D, and talent acquisition and retention.

Reconfiguring digital strategies amid trade fragmentation

National and firm-level challenges

The results are different on a country level but globally consistent.

The results indicate that the disruption firms are facing due to trade conflict is multi-dimensional. While market access and expansion, and access to technology emerge as the most widely cited areas of concern, regulatory fragmentation, innovation and R&D constraints, and talent

shortages are widely reported (see Figure 1). Highly impacted countries, meaning countries where executives voted the most for any one of the five domains, include both advanced and emerging economies. This suggests that exposure to cross-border digital flows, and not income level, is the primary determinant of strategic vulnerability to trade fragmentation.

Below, we analyze each domain comparatively and highlight national rankings, regional patterns, and sectoral dynamics. The findings show that trade conflict is now a structural feature of the global economy. It can shape where, how, and with whom digital strategies can be executed.

1. Market access and expansion

Market access stands out as the domain most directly and immediately affected by trade

conflicts. While traditionally associated with tariffs and border logistics, market access in the digital economy encompasses a wider and more complex set of institutional conditions. These include access to digital platforms, cloud infrastructure, foreign client bases, and interoperable data ecosystems. Firms pursuing digital expansion strategies rely not only on the ability to deliver services across borders but also on predictable access to regulatory environments that support secure, scalable, and lawful engagement with international customers.

Evidence highlights the outsized impact of trade-induced constraints on market access. Small and medium-sized enterprises (SMEs), for instance, engaged in digital exports, experience revenue declines of up to 20% when faced with delays, licensing restrictions, or compliance bottlenecks associated with trade conflict.1 This pattern is corroborated by countries experiencing digital trade restrictions, which see significantly reduced digital service exports and slower technological adoption.2 Furthermore, access barriers disproportionately affect firms that lack the legal or administrative capacity to navigate fragmented trade regimes, particularly those in emerging markets. Such constraints operate through a range of formal and informal channels. Regulatory asymmetries like mandatory data localization, inconsistent licensing frameworks, and cross-border taxation undermine the ability of firms to operate seamlessly across jurisdictions.3

These policies convert scale-driven digital services into geographically isolated operations. The latter requires duplicated infrastructure, specialized compliance teams, or the abandonment of certain markets altogether. Even when firms are technically capable of cross-border operations, the reputational and legal risks introduced by trade-based retaliation can deter investment or hinder market-entry strategies.

What do executives say?

Among the five strategic domains evaluated in our Executive Opinion Survey, market access emerges as the most frequently affected by international trade conflicts. A total of 51.63% of survey participants report that trade tensions have negatively influenced their firm’s ability to enter, operate in, or expand across international markets. This finding, in turn, underscores the heightened vulnerability of cross-border commercial engagement in an era of growing institutional fragmentation, retaliatory trade measures, and technopolitical segmentation. Market access in the digital economy encompasses access to cloud platforms, cross-jurisdictional licensing, regulatory interoperability, and data mobility. All of these dimensions are increasingly subject to policy volatility. Firms pursuing digital internationalization rely on predictable access to digital infrastructure, stable digital services taxation frameworks, and legal assurance for remote service delivery. Trade conflict compromises these foundations by introducing abrupt changes in legal exposure, compliance cost, and reputational risk.

Jordan and Kenya exemplify the challenges faced by smaller, outward-oriented digital economies navigating multiple regulatory regimes.4 Jordanian firms in fintech, business process outsourcing (BPO), and software as a service (SaaS) operate across the Middle East, Europe, and North America, but face mounting barriers from divergent cybersecurity standards, digital tax rules, and platformspecific sanctions. Similarly, Kenya’s role as East Africa’s digital hub is constrained by cross-border frictions such as content hosting mandates, internet taxation, and conflicting consumer protection laws. Emerging data nationalism policies further fragment regional markets, turning previously dynamic digital service flows into isolated national systems.5 In Europe, Lithuania, Latvia, and Bulgaria illustrate how smaller EU members with active tech export sectors remain vulnerable to external trade frictions. Though integrated into the EU digital market, their reliance on clients in the UK, the US, and Asia exposes them to post-Brexit divergence, GDPR debates, and transatlantic disputes. These elements raise compliance costs, legal uncertainty, and the need for duplicative infrastructure.

trade volumes, firms are feeling the impact of shifting access conditions, such as those related to cloud services, authentication protocols, and transnational payments. Additionally, Taiwan (Chinese Taipei, 64.66%) and Denmark (63.46%) offer cases of advanced economies facing unique access challenges. On the one hand, Taiwan’s strategic alignment with US technology architecture exposes its firms to exclusion from certain Chinese platforms and standards while also making them collateral targets in retaliatory trade responses. On the other hand, Denmark’s high score is notable given its strong digital governance record and EU integration. The likely drivers include stricter enforcement of EU digital services rules and uncertainty regarding access to non-EU digital markets amid increasing regulatory fragmentation.

1 Freund, C., Mattoo, A., Mulabdic, A., & Ruta, M. (2024). Is US trade policy reshaping global supply chains?. Journal of International Economics, 152, 104011.

2 Ferracane, M. F., Lee-Makiyama, H., & Van Der Marel, E. (2018). Digital trade restrictiveness index. European Center for International Political Economy, 5.

3 Ferracane, M. F., Kren, J., & Van Der Marel, E. (2020). Do data policy restrictions impact the productivity performance of firms and industries?. Review of International Economics, 28(3), 676-722.

The countries reporting the most severe market access constraints provide key insights into how this disruption plays out in different economic contexts. Jordan ranks first globally, with 79.21% of executives citing trade-induced obstacles to market access. Kenya follows at 72.22%, Lithuania (70%), Latvia (69.05%), and Bulgaria (65.22%) complete the top five. Despite wide variation in income levels and digital sector maturity, these countries share common features. They have outward-oriented digital services sectors, limited domestic markets, and reliance on platform interoperability or transnational regulatory access.

Other Asian and African countries also report substantial market access disruptions. Indonesia (63.93%) ranks sixth globally, reflecting the country’s increasing digital export orientation. Indonesian firms face constraints from both China-US platform divisions and data flow friction with key ASEAN trading partners. Botswana (63.08%) and South Africa (62.30%) also appear in the top ten. The latter indicates that even in regions with lower aggregate digital

4 World Bank, & World Trade Organization. (2023). Digital trade for development. Washington, DC: World Bank; Geneva: World Trade Organization. https://openknowledge.worldbank.org/handle/10986/40454

5 Del Giovane, C., Ferencz, J. & López-González, J. (2023). Nature, evolution and potential implications of data localisation measures (OECD Trade Policy Papers No. 278). OECD Publishing.

What emerges across these examples is a clear pattern. The loss of market access is not necessarily due to declining competitiveness or lack of innovation, but to rising uncertainty in the legal, technological, and political conditions that govern international digital transactions. Firms are often caught between conflicting regimes such as the US cloud export compliance, Chinese platform restrictions, and EU data localization, and must make difficult strategic decisions about jurisdictional alignment.

2. Access to technology

Access to enabling technologies, including hardware, software, digital platforms, and specialized components, is essential for digital competitiveness. While innovation drives the creation of new capabilities, access to technology determines a firm’s ability to adopt, scale, and operationalize those innovations.

Trade policy plays a critical role in this access. When trade is open, it facilitates the global diffusion of cutting-edge tools. Conversely, when restricted, it isolates firms from critical resources. That is to say that trade integration accelerates technological upgrading via imports of intermediate and capital goods.6 However, such a process is jeopardized when geopolitical tensions result in export bans, blacklists, or licensing limitations.

There is evidence that digital trade barriers significantly reduce technological innovation efficiency.7 These barriers include cross-border licensing requirements, data localization rules, and platform access restrictions. Their effects are particularly important in midincome economies with limited domestic alternatives. For example, evidence indicates that semiconductor trade disruptions led to cascading delays and cost increases in downstream firms reliant on timely access to high-performance chips. These indirect effects highlight the systemic character of technology supply chains, where constraints at the upstream level reverberate throughout entire sectors.8

At the firm level, the uncertainty surrounding trade-based technology restrictions inhibits investment in infrastructure upgrades and system integration. Firms facing uncertain access to foundational technologies, whether due to export controls, supply chain reconfiguration, or retaliatory sanctions, tend to delay digital modernization in favor of legacy

6 See for instance Coe, D. T., & Helpman, E. (1995). International R&D spillovers. European economic review, 39(5), 859-887.

7 Yan, M., & Liu, H. (2024). The impact of digital trade barriers on technological innovation efficiency and sustainable development. Sustainability, 16(12), 5169.

8 Kravchenko, K., Gruchmann, T., Ivanova, M., & Ivanov, D. (2024). Responding to the ripple effect from systemic disruptions: empirical evidence from the semiconductor shortage during COVID-19. Modern Supply Chain Research and Applications, 6(4), 354-375.

system maintenance.9 In dynamic sectors like fintech, logistics, and e-commerce, such hesitation leads to digital competitiveness gaps that are difficult to recover. In short, access to technology is not a passive condition but an active determinant of competitiveness parity in a volatile global economy.

What do executives say?

Access to enabling technologies also forms the operational basis of any digitally competitive enterprise. Think cloud infrastructure, digital platforms, semiconductors, and AI engines. In an increasingly conflictual trade landscape, this domain is subject to growing strain. 41.98% of survey respondents report that international trade conflicts have negatively affected their firm’s access to essential technologies.

Cross-national analysis indicates that such an impact is not confined to any one region or income group. Rather, the most severely affected economies include both advanced industrial countries and emerging digital markets. Poland leads the global ranking, with 67.61% of executives citing negative effects in this domain. Ghana (61.40%), France (61.02%), Malaysia (60.50%), and Botswana (56.92%) round out the top five. This distribution points to a convergence of technological dependencies across geographies, where supply chain positioning and external licensing access may matter more than domestic capacity alone.

Poland and Ghana illustrate different forms of vulnerability to trade-related technology disruptions. Poland’s dual role as both importer and integrator of digital systems makes its firms, particularly in manufacturing and logistics,

highly sensitive to export controls, platform restrictions, and evolving certification regimes linked to US, East Asian, and EU policies. Despite being embedded in the EU single market, Polish firms rely on external software and infrastructure, and face friction as initiatives like GAIA-X and the European Chips Act remain under development.10 Ghana, by contrast, represents the challenges faced by emerging digital economies that depend on imported telecom hardware, enterprise platforms, and licensed software to support growth. SMEs are especially vulnerable to tariff hikes, licensing barriers, and software access delays, with limited domestic substitutes. Similar risks affect other African digital exporters, including Nigeria (55.65%), where structural reliance on global platforms amplifies exposure to trade fragmentation.11 France, Malaysia, and the Philippines illustrate how trade conflict disrupts technology access through both regulatory and supply chain channels. France’s high impact score reflects tensions between its digital sovereignty agenda and reliance on global tech ecosystems. National rules on data residency and EU-focused procurement impose complex compliance burdens, which are intensified by platform shifts linked to US-China trade tensions.12 In Southeast Asia, Malaysia faces technology friction due to supply chain exposure. Malaysia’s role in global semiconductor production makes it vulnerable to restrictions on chip designs and cloud platforms. Malaysian firms are thus constrained by geopolitical dynamics beyond their control.13

10 Del Giovane, et al., 2023. Nature, evolution and potential implications of data localisation…; and European Commission. (2023). The European Chips Act. https://digital-strategy.ec.europa.eu/en/policies/ european-chips-act

11 World Bank & World Trade Organization, 2023. Digital trade for development...; and UNCTAD. (2021). Digital economy report 2021: Cross-border data flows and development—For whom the data flow. https://unctad.org/webflyer/digital-economy-report-2021

12 Del Giovane, et al., 2023. Nature, evolution and potential implications of data localisation…; and UNCTAD, 2021. Digital economy report 2021…

13 World Bank & World Trade Organization, 2023. Digital trade for development...

Ultimately, access to technology is no longer ensured by economic status or national policy alone. It now depends on complex trade relations, licensing constraints, and platform geopolitics. Firms increasingly face disruptions to essential tools (e.g., cloud services and AI libraries) due to policy decisions beyond their control. As digital sovereignty efforts, fragmented standards, and retaliatory restrictions grow, access to technology is shaped as much by geopolitical alignment as by innovation capacity.

3. The regulatory environment

The regulatory environment has become one of the most complex and consequential domains through which trade conflicts disrupt digital strategy. Unlike traditional trade barriers, which are often transparent and quantifiable (e.g., tariffs or quotas), regulatory barriers emerge “behind the border” and operate through technical standards, compliance protocols, and institutional divergence. These non-tariff measures can exert greater economic influence than tariffs precisely because they are harder to contest, measure, or harmonize.14 In the context of digital strategy, regulatory divergence directly affects how, and whether, firms can scale services, transfer data, protect intellectual property, and secure legal standing in foreign markets.

Studies support the conclusion that regulatory fragmentation is a central constraint on digital trade and firm competitiveness. Barriers related to cross-border data flows, local content requirements, and technology certification significantly reduce services exports, especially

14 Baldwin, R. (2016). The great convergence: Information technology and the new globalization. Harvard University Press. Reconfiguring

among SMEs with limited compliance capacity.15 In parallel, the implementation of the General Data Protection Regulation (GDPR) has had extraterritorial consequences. While GDPR has raised global data privacy standards, its variable enforcement across jurisdictions has created legal uncertainty and fragmented compliance obligations, particularly for non-EU firms.16 That is, regulatory measures intended to enhance trust and accountability can unintentionally serve as exclusionary trade practices.

The burden of regulatory fragmentation is intensified by the fact that digital regulations are cross-cutting rather than sector-specific. In turn, such regulations force firms to simultaneously comply with overlapping standards in AI, financial reporting, and data governance across jurisdictions. This institutional decoupling reduces investment efficiency and stifles innovation in emerging technologies such as AI, biotech, and blockchain.17 Southeast Asia illustrates these dynamics clearly. ASEAN’s efforts at regulatory harmonization are undermined by national divergences and geopolitical sensitivities, which delay data exchange and weaken digital supply chain integration.18 Firms in Malaysia, for instance, face concurrent compliance with local data residency laws, US-China platform divides, and EU-style privacy standards. That level of compliance imposes significant structural and strategic costs. As a result, regulatory alignment is at the forefront of digital competitiveness, requiring legal foresight, jurisdictional

15 Ferracane, M., & Marel, E. V. D. (2019). Do data policy restrictions inhibit trade in services?. Robert Schuman Centre for Advanced Studies Research Paper No. RSCAS, 29.

16 Ferracane, M. F., Kren, J., & Van der Marel, E. (2021). The costs of data protectionism. Big data and global trade law, 63-82.

17 Cerdeiro, D. A., Mano, R., Eugster, J., & Peiris, M. S. J. (2021). Sizing up the effects of technological decoupling. International Monetary Fund.

18 Wiedemann, N., & Leicht, M. (2023). Supply Chain Data Sharing: Evaluating Challenges and Opportunities of EU Data Law. Available at SSRN 4651903.

adaptability, and sustained investment in compliance capabilities. Such factors cannot be easily hedged or outsourced in an increasingly fragmented digital economy.

What do executives say?

In the digital economy, the regulatory environment plays a decisive role in shaping how firms scale across markets, manage data, protect intellectual property, and ensure operational continuity. Unlike traditional trade barriers, which tend to be explicit and quantifiable, regulatory barriers emerge behind the border through technical standards, compliance frameworks, and institutional divergence. Such barriers are difficult to contest in trade negotiations and disproportionately affect digital firms operating in multiple jurisdictions. According to survey results, 36.42% of executives indicate that trade conflict has introduced or exacerbated regulatory constraints on their firm’s digital strategy. This result suggests that the coherence of the legal environment is now a strategic variable in digital competitiveness.

At the global level, the five most affected countries are Jordan (56.44%), Malaysia (56.30%), Belgium (51.11%), Austria (50.56%), and Spain and Chile (both with 50%). Each of these countries illustrates a different facet of regulatory vulnerability. In Jordan and Malaysia, firms must navigate overlapping and sometimes contradictory legal regimes imposed by trading partners, technology suppliers, and regional blocs. In the European cases, regulatory complexity stems less from institutional weakness than from excessive fragmentation and extraterritorial legal exposure. The latter is particularly so in relation to global data governance norms. Meanwhile, Chile has opted for a hybrid positioning that leads it to

participate in OECD frameworks while engaging in Pacific regional trade. Such positioning exposes its digital landscape to simultaneous pressure from Western data norms and AsiaPacific digital sovereignty measures.19

The rest of the top 10 includes the Netherlands (48%), Indonesia (47.54%), Germany (46.88%), and Ireland (46.55%). In the Netherlands and Germany, regulatory complexity arises not from lack of legal clarity but from geopolitical entanglements. As host countries to multinational cloud providers and digital platforms, they are often front-line implementers of contested global data policies.20 German firms in particular are impacted by export controls tied to cybersecurity certifications and AI risk classifications.21 Indonesia’s challenge arises from dual pressures. First, it needs to uphold national digital sovereignty while remaining compatible with global interoperability frameworks. Such a balance becomes harder to maintain under intensifying trade tensions.22

Across all these cases, one finding remains clear. Regulatory divergence is no longer an incidental or secondary concern. It is a core issue in digital strategy formulation. As such, it affects everything from product architecture and user interface localization to contract structuring and data pipeline design. Firms must now budget for multi-jurisdiction legal compliance, anticipate rule changes driven by retaliatory trade actions, and maintain

19 Ministry of Trade and Industry, Government of Singapore. (2025). Overview of the Digital Economy Partnership Agreement (DEPA); and OECD (2025). Digital Government in Chile: Strengthening the Management of Digital Investments. OECD Publishing.

20 The Cyber Hive Analysis. (2025). European businesses rethinking cloud dependencies amid geopolitical risk. The Cyber Hive.

21 OECD (2024). OECD Artificial Intelligence Review of Germany. OECD Publishing.

22 OECD. (2024). OECD Digital Economy Outlook 2024: Embracing the Technology Frontier. OECD Publishing.

regulatory adaptability as a core capability. Success in such a context depends not only on technological innovation or market demand, but also on institutional intelligence. That is, the ability to interpret, align with, and adapt to a shifting regulatory landscape.

4. Innovation and R&D

Innovation and R&D are at the core of firmlevel digital competitiveness. They enable the development of new products, processes, and services that differentiate firms in increasingly saturated markets. Trade openness is important in fostering innovation through knowledge spillovers, access to advanced inputs, and global learning-by-doing mechanisms.23 In practice, these mechanisms are disrupted when geopolitical tensions limit cross-border flows of information, capital, and technical collaboration. Thus, any erosion of international trade cooperation directly threatens the effectiveness of innovation systems. This is particularly so for those dependent on globally distributed R&D networks.

There is evidence that trade conflict-induced constraints on innovation are not only financial but structural. For instance, while Chinese firms on US entity lists (i.e., classified as a national security issue by US authorities) increased their R&D expenditures by 16.6% in response to export restrictions, they did not experience a corresponding increase in innovation output, such as patents or product launches.24 Such a divergence reveals the limitations of defensive innovation strategies that attempt to substitute domestic efforts for blocked international inputs

23 Grossman, G. M., & Helpman, E. (1991). Trade, knowledge spillovers, and growth. European economic review, 35(2-3), 517-526.

24 Hu, H., Yang, S., Zeng, L., & Zhang, X. (2024). US–China trade conflicts and R&D investment: evidence from the BIS entity lists. Humanities and Social Sciences Communications, 11(1), 1-15.

National and firm-level challenges

or partnerships. The quality and strategic value of innovation declines when global collaboration and specialized imports are no longer reliably accessible.

The vulnerability of innovation to trade conflict is particularly visible in countries situated within larger regional innovation networks. Geopolitical sanctions and policy frictions reduce copatenting and joint research activities between Western and Eastern Europe.25 Fragmentation of research ecosystems erodes the diversity and quality of innovation pipelines. Fragmentation thus reduces firms’ ability to harness external expertise and technological advances. This is not limited to formal R&D partnerships. Informal diffusion channels such as industry conferences, cross-border hiring, and shared research infrastructure are also undermined by trade conflict. Furthermore, planning for innovation becomes increasingly volatile under conditions of trade uncertainty. Firms facing policy ambiguity often delay or scale down irreversible investments.26 Innovation projects, which require multi-year capital commitments and involve considerable sunk costs, are particularly sensitive to this risk.

What do executives say?

Innovation and R&D are increasingly shaped by the pressures of geopolitical fragmentation.

31.96% of high-level executives report that international trade conflicts have adversely affected their organization’s innovation and R&D strategies. While this figure is lower than the impact levels recorded for market access and technology acquisition, it nonetheless signals

a structural vulnerability in firms’ capacity to sustain long-term innovation cycles under conditions of strategic uncertainty.

Economies that are deeply embedded in cross-border innovation environments show the highest levels of concern in this regard. The Czech Republic ranks first, with 58.33% of executives identifying trade conflict as a significant constraint. Malaysia follows closely at 54.62%, while Indonesia (49.18%), Korea Rep. (48.68%), and China (47.95%) round out the top five. These economies, though diverse in income and innovation capacity, share a common trait. They experience high exposure to international research collaboration, technological codependence, and integrated production value chains. The Czech Republic and Malaysia exemplify how deep integration into regional innovation ecosystems heightens exposure to geopolitical disruption. Czech firms, though moderate in domestic R&D spending, rely heavily on EU research funding, cross-border technology transfer, and industrial partnerships linked to Germany and Austria. These ties make innovation performance sensitive to trade tensions such as EU-US data-sharing uncertainties, dual-use export controls, and shifting digital services regulation.27 Malaysia’s high vulnerability similarly reflects its role in East Asia’s semiconductor and electronics value chains, where local firms act as R&D intermediaries for Japanese, Korean, and Chinese tech leaders. This position leaves them exposed to export restrictions and platform sanctions originating from the US-China technology rivalry, particularly in areas like cloud access, AI tools, and chip design, which directly constrain their innovation capacity.28

Indonesia represents a distinct but instructive case. As a rising fintech and e-commerce center, its digital innovation environment is more service-oriented and less dependent on hardware co-development. Nevertheless, it is structurally reliant on foreign intellectual property (IP), software platforms, and crossborder investment.29 Restrictions on foreign participation in digital infrastructure, or platform decoupling between Chinese and Western providers, introduce friction into R&D planning.30 In such a context, digital firms depend on an uninterrupted flow of global tools and standards to remain competitive. Furthermore, Korea and China highlight the challenges faced by national innovation systems under tradeinduced decoupling. In China’s case, aggressive domestic R&D investment has been ramped up to compensate for diminished access to US technologies, but results have been mixed. Research has shown that while firms increase expenditures, the innovation yield measured in patents, collaborations, or commercialized breakthroughs has not always improved proportionally.31 Korea faces parallel challenges, with US and Chinese export controls affecting critical sectors such as AI, advanced displays, and 5G infrastructure.32

Survey results thus highlight that innovation resilience depends on domestic capability or spending intensity as well as on a country’s structural position within global research flows and technological dependencies. As trade

tensions multiply and multilateral coordination declines, countries and firms embedded in collaborative environments face heightened exposure to external regulatory shifts, export barriers, and retaliatory policies.

5. Talent acquisition and retention

25 Makkonen, T., & Mitze, T. (2021). Geo-political conflicts, economic

26

391-415.

27 Del Giovane, et al., 2023. Nature, evolution and potential implications of data localisation…; and European Commission (2023). Digital Decade policy programme 2030. https://digital-strategy.ec.europa.eu/ en/library/digital-decade-policy-programme-2030

28 World Bank & World Trade Organization, 2023. Digital trade for development...; and UNCTAD, 2021. Digital economy report 2021…

29 OECD (2024). Services Trade in Indonesia: Exploring patterns, policies, and reform Scenarios. OECD Publishing.

30 U.S. International Trade Administration. (2025). Indonesia Digital Economy. Retrieved from https://www.trade.gov/country-commercial-guides/indonesia-digital-economy

31 Hu, H., Yang, S., Zeng, L., & Zhang, X. (2024). US–China trade conflicts and R&D investment: evidence from the BIS entity lists. Humanities and Social Sciences Communications, 11(1), 1-15.

32 Kim, H., & Cho, J. (2024). The impact of US export controls on Korean semiconductor exports. KDI Journal of Economic Policy, 46(3), 1-23.

In an economy increasingly defined by digital capabilities, access to high-skilled human capital has become a central determinant of firm digital competitiveness. Talent acquisition and retention are particularly vulnerable to trade conflicts because they rely on frameworks that enable mobility, cross-border service provision, and international recognition of qualifications. When these frameworks are disrupted, for instance, through visa restrictions or retaliatory immigration policies, the ability of firms to hire globally competitive talent deteriorates. This has both direct operational consequences and long-term strategic implications for innovation, service delivery, and market responsiveness. Evidence suggests that firms operating in jurisdictions affected by trade-related restrictions on labor mobility report longer recruitment timelines and lower productivity. Multinationals exposed to bilateral trade tensions often face hiring delays and higher labor costs due to increased visa compliance, partner country retaliation, or exclusion from cooperative education and training programs.33 These frictions are particularly harmful in digitally intensive sectors where expertise in cybersecurity, AI, cloud architecture, or data engineering is both scarce and globally contested. Firms unable to source talent externally are often forced into suboptimal

33 Gordon, J. (2022). In the zone: Work at the intersection of trade and migration. Theoretical Inquiries in Law, 23(2), 147-183.

domestic hiring or expensive retraining initiatives, which limit their capacity to scale up their digital transformation.

The spatial fragmentation of digital labor markets also limits the use of remote work and online platforms, which were once seen as mitigating tools for talent shortages. Trade conflicts affecting cloud infrastructure, cross-border payments, and data governance indirectly reduce the viability of digital freelancing and remote service delivery.34 This disproportionately affects firms in emerging markets that depend on global talent marketplaces to access specialized expertise. Even when local skills are available, the absence of global exposure and collaboration hinders capability development, reinforcing the digital skills divide between countries. Furthermore, high-skilled migration is often tightly linked to research collaboration, joint ventures, and corporate mobility programs. Digital firms in the US and EU increasingly cite restrictive immigration policies exacerbated by trade tensions as barriers to hiring in AI, biotech, and fintech sectors.35 The erosion of the academic and professional mobility pipelines, moreover, reduces not only the volume but also the diversity of available talent, which undermines organizational adaptability and innovation capabilities. In other words, the intersection of trade and talent mobility reveals a new vulnerability in the digital strategy formulation. Firms that once relied on globally competitive labor markets must now build resilience in an environment of constrained access and politicized hiring frameworks.

34 Berg, J., Furrer, M., Harmon, E., Rani, U., & Silberman, M. S. (2018). Digital labour platforms and the future of work: Towards decent work in the online world. ILO

35 See Zwetsloot, R., Zhang, B., Dreksler, N., Kahn, L., Anderljung, M., Dafoe, A., & Horowitz, M. C. (2021, July). Skilled and Mobile: Survey Evidence of AI Researchers’ Immigration Preferences. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (pp. 1050-1059).

What do executives say?

Talent acquisition is a critical dimension of digital competitiveness, yet it remains particularly vulnerable to disruption in a fragmented global trade environment. Tradeinduced restrictions on labor mobility include visa tightening, diplomatic frictions, or restrictions on labor-sending countries. Survey results indicate that 31.49% of respondents report international trade conflicts have negatively affected their ability to hire or retain digital talent. While this makes talent the least cited of the five strategic domains analyzed, the absolute level of concern (i.e., reported by nearly one in three respondents) suggests that human capital flows are subject to structural pressures with significant operational implications. The highest reported impact levels come from countries with distinct forms of labor market dependency and openness. Kuwait ranks first, with 56.92% of executives citing traderelated disruptions to talent strategy. The Philippines (45.54%), Cyprus (44.68%), Puerto Rico (44.44%), and Indonesia (44.26%) follow closely behind. These figures highlight a shared vulnerability across economies that rely either on expatriate labor for digital operations or on international labor markets to source specialized digital expertise.

Kuwait’s top position reflects its structural reliance on imported talent in sectors such as IT consulting, digital infrastructure, and fintech. Despite policy efforts to nationalize portions of the workforce, the country’s digital economy continues to draw heavily from South Asian and Southeast Asian labor markets.36 Trade-related restrictions on labor mobility pose direct threats to workforce continuity. These constraints are

compounded by the increasing politicization of migration policy and the spillover effects of bilateral diplomatic tensions. The Philippines, a global hub for business process outsourcing (BPO), relies on skilled digital professionals to serve clients across North America, Europe, and Asia. Trade-related barriers (e.g., remote work taxes, licensing hurdles, and data flow restrictions) make it harder for firms to maintain contracts and retain talent, especially in smaller BPO centers with limited shock absorption capacity.

Cyprus and Puerto Rico provide another example of small economies reliant on crossborder digital talent. Cyprus is a growing hub for IT services, software development, and digital marketing. Firms in the country depend heavily on internationally mobile professionals. Any disruptions in visa reciprocity or international credential recognition thus undermine the subcontracting pipelines and workforce continuity.37 Similarly, Puerto Rico’s digital firms face shrinking talent pools and compliance burdens when international remote work and licensing rules shift. Additionally, Indonesia presents distinct vulnerabilities. Despite its large domestic market, its digital economy, particularly in fintech and logistics tech, is constrained by severe shortages of advanced technical talent. Firms tap into talent within the ASEAN region, yet trade-related restrictions such as hiring bans and cross-border frictions significantly limit access to the skills needed for innovation.38

Other countries that report high impact in this domain include Peru (43.18%), Malaysia (42.86%), Bulgaria (42.03%), Türkiye (41.67%),

37

38

and Hungary (41.57%). In Malaysia’s case, the dual dynamic of being both a receiver of digital talent and a regional exporter of IT services means that any hindrance to labor mobility resonates through both demand and supply channels. In Türkiye and Hungary, the issue is compounded by economic and political uncertainty, which amplifies the difficulty of attracting and retaining internationally mobile talent even without formal restrictions. While the impact on talent acquisition is more localized than market entry or technology access, its implications are no less strategic. A constrained talent environment not only raises costs and delays project implementation but also limits innovation and digital integration across business units. For AI and platform engineering globally competitive firms, reliance on specialized cross-border expertise is a structural feature of their business models. When those models are disrupted by external policy tensions, substitution is rarely immediate or efficient.

Rethinking digital strategy amid 2025’s trade fragmentation

Digital strategy is no longer defined solely by internal capabilities or innovation diffusion.39 It should now be understood as an externally responsive process, shaped by trade conflict, regulatory fragmentation, and geopolitical alignment. The five domains examined

39 Ismail, M. H., Khater, M., & Zaki, M. (2017). Digital business transformation and strategy: What do we know so far. Cambridge Service Alliance, 10(1), 1-35.

(market access, access to technology, regulatory environment, innovation and R&D, and talent acquisition and retention) serve as the principal channels through which these external pressures condition firm-level digital competitiveness. Each of these areas connects to broader institutional dynamics and subsequently to digital strategy. Market access and access to technology were the most frequently cited but concerns across the five domains were evenly distributed, globally. Countries like the Czech Republic, Malaysia, and Jordan illustrate that vulnerability to the impact of trade fragmentation is driven less by digital capacity and more by exposure to cross-border flows.

Analysis of the executives’ answers shows us that the five domains are interdependent. This means that firms cannot isolate one area without encountering constraints in others. For instance, impacts on market access could cascade into barriers to talent acquisition, innovation and R&D, and/or regulatory compliance. In such a context, firms interested in growing their strategic resilience therefore need to develop capabilities across multiple fronts, including regulatory and geopolitical adaptability and jurisdictional flexibility. For policymakers, supporting digital competitiveness is starting to demand much more than investment in infrastructure or even in skills. Instead, it needs a coordinated trade policy and regulatory

alignment with a view to reducing institutional uncertainty and restoring coherence to the digital economy’s operating environment. Trade conflicts, in short, have evolved into a structural condition of the global economy. They shape the geography, processes, and partnerships through which countries and firms implement their digital strategies.

Digital enablers at the industry level

Impacts

and trends

Digital competitiveness is central to economic performance and has become a defining component of national resilience in the face of shocks. Therefore, the rapid pace at which industries, companies, and governments are adopting and applying new technologies underscores the need for robust digital policy frameworks, flexible and adaptive business practices, as well as having mobile and highly skilled talent capable of maximizing the benefits of increased digital penetration. From datadriven automation and decision-making to artificial intelligence, digital technologies are reshaping production, services, and governance at an alarmingly disruptive pace across all industries.

The 2025 World Digital Competitiveness Ranking (WDCR) is based on a combination of 40 hard data indicators and 21 survey questions capturing executive perceptions, providing a comprehensive assessment of how economies are adapting to digital transformation. This essay focuses specifically on insights from IMD’s Executive Opinion Survey, which collected the perspectives of more than 6,000 senior executives worldwide between January and March 2025. Analyzing these responses by country and sector of activity reveals that digital progress is far from uniform across economies. The resulting digital divide reflects structural disparities both between countries and, more significantly, within them.

The data forming the results of the 2025 WDCR is from international, national, and regional sources.

A core part of the data making up the results of the 2025 World Digital Competitiveness Ranking is the IMD Executive Opinion Survey. Between January and March 2025, we asked 6,162 global executives 21 questions on the business climate in their location. In addition, this year we took the survey and disaggregated responses to one digitally related question (the only question that did not feed into the overall results, incidentally):

“How do trade disputes affect the digital strategy of your company?”

We regrouped the answers from executives in each country by the sector of activity of the respondents and then looked for patterns that cross-cut them. We found that economies are not advancing digitally in a uniform way. The resulting digital divide is not only a matter of disparities between countries, but also within them.

These domestic gaps might be geographical –rural and urban areas being very different – or socioeconomic, reflecting variations across income groups. But what jumped out the most is that they are also sectoral, with the various industries experiencing and undertaking digital adoption at vastly different speeds. While some sectors move quickly to integrate digital tools, others lag, creating vulnerabilities for their country’s long-term competitiveness.

These disparities matter deeply in the current global context. Ongoing geopolitical tensions are complicating national and company-level digital strategies. Meanwhile, trade disputes, diverging regulatory frameworks, and a growing desire for digital sovereignty – that is, boosting nations or firms’ abilities to control their digital environment – are fragmenting global digital governance.

Impacts and trends

The result is increased uncertainty and complexity for firms and governments attempting to navigate an increasingly contested landscape. In this environment, understanding how digital enablers impact industries in different ways becomes an essential analytical tool for working out why some industries and countries will continue to benefit from a competitive edge in the digital economy.

Research by the World Competitiveness Center suggests that industry performance and country-level competitiveness in the digital arena are primarily influenced by three critical digital enablers that facilitate technology adoption and assimilation: (1) digital governance and policy frameworks, (2) company capabilities, and (3) human capital.

By analyzing all three, we can move beyond isolated indicators and highlight the systemic conditions through which industries convert digital opportunities into competitiveness. For each enabler, we examine survey-based industry results to understand how executives perceive their digital readiness, see where gaps emerge, and why these differences matter.

In the IMD Executive Opinion Survey, business leaders answer questions using a scale from 1 to 6. A score of 1 indicates that the factor being evaluated does not support competitiveness in its economy, and 6 means that it strongly does. For this analysis only, we have converted these scores into percentages to provide a clearer basis for comparison: a score of 0% reflects complete dissatisfaction, while 100% represents the highest possible level of support for competitiveness according to executives.

By grouping the 21 survey questions into three categories – the key digital enablers – our analysis moves beyond individual data points to highlight systemic strengths and weaknesses that are perceived at the industry level. This is supported by the supposition that the enablers provide the structural conditions through which firms and industries translate digital opportunities into tangible performance gains.

Enabler

1: Digital governance and policy frameworks

Effective digital governance creates the conditions for industries to adopt and scale digital tools. It encompasses the institutional and regulatory environment that shapes how firms can operate digitally, covering areas from cybersecurity to intellectual property protection, and can include public-private partnerships or the management of digital infrastructure. As global digital governance fragments, however, the outcomes of such frameworks diverge across industries.

Our analysis examines six survey questions related to this enabler: management of cities, banking and financial services, public-private partnerships, cybersecurity, laws relating to scientific research, and intellectual property rights. The results reveal significant variation in how executives perceive the quality of digital governance in their economies.

Banking and financial services consistently score highly across industries, with an average satisfaction rate of 62.2%. Executives in finance and insurance report the highest satisfaction at 69.5%, reflecting decades of regulatory attention and investment in digital infrastructure. At the other end of the spectrum, executives in agriculture (58%) and construction (57.8%) are least satisfied, suggesting that existing regulatory and financial frameworks are less responsive to the needs of more traditional sectors. The relative uniformity of scores across industries highlights the long-standing policy priority given to the digitalization of financial services in economies across the world, helping explain why the financial sector has often spearheaded digital adoption. However, the lower satisfaction in agriculture and construction signals potential blind spots: without targeted policies to extend governance benefits more evenly, economies risk entrenching a digital divide between highly digitized and lagging industries.

The small disparities observed in banking services satisfaction extend more prominently to other areas of digital governance, suggesting that institutional attention remains uneven across sectors. Traditional industries like agriculture score notably lower on important governance indicators such as intellectual

property rights protection (61.2% compared to the industry-wide average of 67%) or the management of cities (59.8% versus 65.3%). This suggests that governance frameworks in the digital sphere may be optimized for certain sectors that are considered more profitable at the expense of more traditional ones, such as construction and education.

This pattern extends to opinions on the level of cybersecurity within each field: whereas agriculture, construction and education executives rate cybersecurity slightly below the global average of 60.2%, executives in finance, insurance, and real estate rate their level of cybersecurity at 65.4%, indicating that digital security governance may not adequately address emerging vulnerabilities in sectors undergoing digital transformation and may be overly focused on protecting the industries which have already undertaken such digitalization. This could also reflect cybersecurity policies that have evolved reactively around highvalue sectors rather than proactively across the broader economy.

Public–private partnerships reveal further asymmetries. Transport and storage executives rate this dimension at 65.5%, above the cross-industry average of 62.6%, likely reflecting the infrastructure-intensive nature of the sector and its reliance on government coordination in areas such as port digitalization or smart traffic systems. Construction, hospitality, and manufacturing show similar levels of satisfaction, indicating that public investments are perceived as more effectively implemented in infrastructure-heavy industries. By contrast, satisfaction scores are lowest in the electricity, gas, and water sectors; industries that, despite being partly nationalized, often face complex governance structures that slow innovation. This could suggest that governments may prioritize PPPs where returns are most visible, leaving less profitable sectors undersupported.

Divergent regulatory approaches among major economies further complicate governance outcomes. The European Union’s focus on data protection through frameworks such as the GDPR provides robust consumer safeguards but imposes compliance burdens that can weigh heavily on smaller firms and certain industries. Meanwhile, competition between the United States and China over technology exports has introduced new trade restrictions, which further fragment markets and increase uncertainty. As

this regulatory divergence deepens, industries operating across borders face growing complexity that risks slowing innovation diffusion and scale, two critical drivers of digital competitiveness.

Enabler 2: Company capabilities

Company capabilities refer to firm-level organizational attributes that enable digital adoption, literacy, and competitiveness more broadly. It includes indicators such as company agility, knowledge transfer, use of big data, access to venture capital, recognition of opportunities and threats, and flexibility and adaptability. Analysis of these six indicators reveals that digital capabilities are unevenly distributed across industries, with important implications for national competitiveness strategies.

The most striking finding is the universal challenge faced by firms when trying to access venture capital to develop their activities. The executive opinion survey suggests that every industry struggles in this dimension, with satisfaction scores ranging from a low of just 43.6% in the arts, entertainment, and recreation industries to a high of only 59.6% in accommodation and food services. Manufacturing, despite being the largest sector in our sample with over 1,100 respondents (21% of the total), scores just 51%. Executives in professional, scientific, and technical services, which should theoretically attract innovation capital, also report just 52.6% satisfaction with their access to venture capital. Similarly, in the IT and communications sectors, the core of the digital economy, executives’ satisfaction is below average at 59%.

This industry-wide dissatisfaction points to a systemic financing gap. Venture capital remains concentrated in a few geographic hubs (like Silicon Valley) and narrow technology fields such as software or fintech, leaving most traditional industries digitally undercapitalized despite their potential for transformation. Digitalization in sectors such as manufacturing, agriculture, or transport requires financing models aligned with longer time horizons and higher capital intensity, yet current mechanisms are structurally misaligned with these needs. In short, venture capital markets appear ill-suited to enabling large-scale digital transformation beyond the startup ecosystem.

Company agility shows more variation and reveals some

unexpected patterns that challenge common assumptions about digital readiness. Executives in the transport and storage industries scored 63.4% in company agility, matching manufacturing and slightly ahead of the finance, insurance, and real estate sector, which all exceeded the industry-wide average of 61.2%. Construction also achieves 60%, a strong result for a sector often characterized as resistant to change. These findings could suggest that operational pressures in logistics and global supply chains have driven higher organizational agility in sectors previously believed to be digitally conservative. The contrast with education is instructive: despite its knowledge-intensive nature, executives in education rate their sector just 58% on agility, likely reflecting frustration with institutional rigidity and regulatory constraints rather than the nature of the work itself. Ultimately, these results suggest that digital competitiveness depends as much on organizational flexibility and decision-making structures as on access to new technologies themselves.

Knowledge transfer presents perhaps one of the most concerning patterns for long-term digital competitiveness. In the education sector, responsible for developing and disseminating knowledge across society, executives only score 55.4% satisfaction with their ability to do that effectively, below the cross-industry average of 57.3% and behind professional, scientific, and technical services (56.4%). This result underscores structural rigidity with deep implications: if educational institutions face difficulty transferring knowledge within their own systems, their ability to prepare students and professionals for rapidly evolving digital careers is inherently limited. The challenge extends across the economy. Agriculture scores 55%, manufacturing 56.8%, and even the IT and communications sector, which is expected to lead in digital diffusion, registers just 58.2% from its executives. Such scores could point to a systemic weakness in moving knowledge from research to application, from innovators to adopters, and from early experimentation to broad operational use. In this sense, weak knowledge transfer mechanisms constrain the translation of national R&D capacity into productivity gains, particularly in traditional sectors where institutional collaboration is limited or fragmented.

The adoption of big data analytics shows clear sectoral stratification that correlates with both the availability of data and the clarity of use cases. For instance, the manufacturing sector

has clear potential applications for big data use in predictive maintenance, quality control, and supply chain optimization. However, executives in the field only score a satisfaction of 55.8%, below the industry-wide average, potentially indicating dissatisfaction with data availability. On the other hand, the sector most satisfied with its use and application of big data is accommodation and food services, which outperforms expectations at 62.6%, possibly reflecting the sector’s intensive collection and use of customer and operational data. It is interesting to note that, once again, executives in knowledgeintensive sectors such as education and scientific research are unhappy with the lack of data-driven decision-making that occurs in their field, scoring below the industry-wide average.

Cross-country comparisons reinforce the dynamics explored and support these arguments. In Germany’s manufacturing sector, for example, executives report strong operational capabilities: employee training (72%), technology development (70%), and digital skills (72%) all exceed global averages and reflect decades of investment in vocational training, close university–industry collaboration, and structured initiatives to embed digital skills in production systems. Yet, despite this, weaknesses emerge in company capabilities. Most notably, venture capital access stands 7 percentage points below the average at just 44% and knowledge transfer scores 52%, versus 57% globally. This dual profile reveals a critical insight: strong institutional frameworks for workforce development and operational excellence don’t automatically create innovation ecosystems at the company level or entrepreneurial dynamism. Germany excels at helping established manufacturers adopt and apply digital technologies, but struggles to generate funds for and scale disruptive digital innovations.

In the United States, the landscape of company capabilities shows even more variations between industries and, implicitly, between regions. IT and communications executives rate venture capital access at 64%, the highest value in the sample, and knowledge transfer at 66%, nearly ten percent above the global average. These high scores reflect the strength of innovation clusters such as Silicon Valley, Seattle, and Austin, where dense ecosystems of investors, accelerators, universities, and experienced entrepreneurs reinforce one another. However, traditional sectors tell a different story. US manufacturing

executives record only 42% satisfaction with venture capital access and 50% for big data analytics, below global averages and well under leading US industries. This internal divergence reflects both geographic concentration of digital capabilities and sectorspecific institutional development. Technology hubs benefit from dense networks of investors, accelerators, universities, and experienced entrepreneurs. However, traditional industries in other regions lack these ecosystems, creating an internal digital divide, even within one of the world’s leading digital economies.

These findings underscore that company capabilities are a foundational yet uneven enabler of digital competitiveness. They determine how effectively firms can absorb, adapt, and scale digital innovations, but also reveal structural asymmetries that shape national digital performance. Across industries, the persistent financing gap in venture capital and the systemic weakness in knowledge transfer point to a broader institutional misalignment between the digital economy’s needs and existing market mechanisms. Meanwhile, differences in agility and big data adoption show that organizational flexibility and managerial culture remain critical to turning technological potential into productivity gains.

At the national level, contrasting examples highlight two distinct models of capability development. Germany’s strength in skills formation and operational excellence demonstrates the power of long-term institutional investment but also exposes the limits of execution-driven systems that struggle to foster entrepreneurial experimentation. The United States, by contrast, illustrates how innovation ecosystems (which are dense, regionally concentrated networks of capital, talent, and research) can drive digital leadership in specific industries while leaving others behind. Both cases reveal that digital competitiveness increasingly depends not just on the presence of technology or talent, but on the ability of firms and institutions to integrate them into coherent, agile systems of innovation. Building inclusive digital economies requires fostering the organizational, financial, and knowledgetransfer mechanisms that allow all sectors, not just digital frontrunners, to participate in and benefit from technological progress.

Enabler 3: Human capital

Human capital encompasses the workforce skills and talent mobility necessary to develop digital competencies. Our analysis examines six indicators: employee training, digital skills, immigration laws, attitude towards globalization, foreign highly skilled personnel, and international experience of senior managers. The patterns that emerge challenge several conventional assumptions about which sectors possess strong digital human capital and reveal where economies risk structural skill mismatches.

Executive satisfaction with digital skills as an enabler of competitiveness shows a surprising hierarchy, with many industries scoring high marks compared to other indicators. Not surprisingly, IT and communications score amongst the highest with 70.4%, surpassed only by the transport industry (71.8%) and the finance, insurance, and real estate sector (71%). Even within more traditional sectors, satisfaction with digital skills is high with manufacturing (68.8%), construction (67.6%), and education (66.8%), all relatively close behind. The relatively strong performance of infrastructure-intensive sectors suggests a broader trend: industries with tangible efficiency gains from digitalization invest more successfully in workforce digital capabilities than those where the benefits are diffuse or harder to quantify.

On the other hand, executives’ assessment of employee training reveals concerning disparities that hint at the existence of a growing digital divide with regard to human capital. With a crossindustry average of 62.3%, three industries stand out as notable weak performers in 2025: agriculture (60.6%), services (58%), and most concerningly, education (55.2%). Though such results are prone to the personal bias of respondents, the latter score is somewhat concerning, as it suggests that the sector responsible for training young professionals is itself underinvesting in digital skill development. This potential institutional weakness could have important cascading effects. If educators lack digital proficiency and pedagogical models remain outdated, they cannot effectively prepare future talent for digitally intensive careers. The issue here is not simply one of technical order through skill acquisition, but rather about the capacity for continuous learning and adaptation, which are attributes central to resilience in the face of technological change.

The strongest performers in employee training provide valuable contrasts. Transport and storage lead with 67.2%, followed by manufacturing (65.8%) and accommodation and food services (65.6%). These sectors face direct operational consequences from inadequate training, such as safety risks, service failures, or quality lapses, which create powerful incentives for workforce investment. Education, by contrast, experiences more diffuse and delayed feedback from training gaps, reducing the urgency for reform and modernization.

Recruitment of foreign highly skilled personnel shows the widest variation of any human capital indicator, exposing how industries integrate (or fail to integrate) into global talent markets. Agriculture ranks lowest at 51.4%, reflecting the relative geographic immobility of agricultural work and challenges in attracting international expertise. Construction follows at 59.4%, again showing how location-bound sectors struggle with global recruitment. In contrast, accommodation and food services reach 64.4%, benefiting from the global nature of hospitality careers. IT and communications score 59.2%, and professional, scientific, and technical services slightly lower at 58.6%, suggesting that immigration restrictions and regulatory hurdles constrain even knowledge-intensive and internationally integrated sectors.

International experience of senior managers follows a similar pattern. Accommodation and food services (63.0%) and transport (63.4%) lead agriculture (56.0%) and arts and entertainment (53.2%) by significant margins. The notion of international experience within an industry is extremely relevant because internationally experienced leadership correlates with awareness of global best practices, openness to external innovation, and access to transnational networks that facilitate knowledge transfer. Industries whose leadership has global exposure are better positioned to identify and adopt digital innovations, regardless of their origin. Attitudes toward globalization, while less dispersed, still vary meaningfully and range from 62.2% in arts and entertainment to 70.0% in accommodation and food services. This consistency across industries suggests that while executive sentiment about global integration remains generally positive, practical integration through skilled migration and crossborder managerial experience is less uniform.

Country examples illustrate how these dynamics play out in practice. Poland’s professional, scientific, and technical services sector demonstrates both the progress and constraints of human capital development in emerging economies. Digital skills reach around 68%, close to Germany’s 72%, and communications technology infrastructure scores near 74%, reflecting sustained investment in STEM education and an expanding technology services base. Yet venture capital access remains low at 36%, international managerial experience around 48%, and foreign talent recruitment approximately 56%. Poland’s trajectory shows how strong domestic capability development can narrow execution gaps with advanced economies, but integration into global innovation networks and capital flows remains limited.

Japan offers a contrasting view. Executives rate technology development at 82% and digital skills at 72%, underscoring world-class technical education and engineering capacity. However, company agility is just 40% (versus a 61% global benchmark), decision-making using big data analytics is 39% (versus 56.2%), and the international experience of senior managers is a mere 30%. Knowledge transfer (50%) and attitudes toward globalization (57%) also fall below global averages. Hierarchical management cultures, consensus-oriented decisionmaking, and limited international exposure constrain Japan’s ability to translate technical proficiency into organizational adaptability. An interesting takeaway from the Japanese scenario is that technical expertise alone is insufficient; digital competitiveness also requires adaptability, cross-cultural fluency, and institutional openness to experimentation and failure.

Human capital remains one of the most decisive enablers of digital competitiveness, but also one of the most complex. The data suggests that digital skills and training investments are unevenly distributed across sectors, often favoring those with immediate operational incentives. Meanwhile, barriers to global talent mobility and limited international experience constrain cross-border learning and innovation diffusion. Countries like Germany and Japan show that technical excellence does not guarantee agility, while emerging economies like Poland reveal that domestic capability-building must be paired with international integration to achieve lasting competitiveness. Building human capital for the digital age, therefore, requires more than skill accumulation; it demands institutional

adaptability, openness to global exchange, and leadership capable of bridging technological potential with strategic execution.

Four sectoral trends shaping digital policy

Several cross-cutting themes emerge from the analysis of the role and impact of digital governance, company capabilities, and human capital as key enablers of digital competitiveness. From the insights of executives, here are four sectoral trends that are particularly relevant for future digital policy.

1. Infrastructure-intensive industries outperform expectations.

Transport, construction, and manufacturing display high digital readiness across communications technology, digital skills, and company agility. For instance, executives in construction rate their industry at 72.4% in communications technology, 67.6% in digital skills, and 66.4% in flexibility and adaptability. Operational imperatives such as efficiency, safety, and cost control may play an important role in accelerating digital adoption where the benefits are immediate and measurable. This challenges the long-standing narrative that traditional industries are resistant to digital transformation and illustrates that well-defined incentives and proven business cases can drive significant progress even in more conservative or manual sectors.

2. Knowledge-based sectors are underperforming despite their strategic importance.

According to executives in education, the industry is underperforming compared to other economic sectors in a few key metrics such as employee training (55.2%), knowledge transfer (55.4%), and digital skills (66.8%), revealing some important structural bottlenecks in the way economies address human capital accumulation in one of the most important industries for digital proficiency: teaching and education. As the sector tasked with enhancing human capital, its perceived inability to modernize could heavily undermine broader

digital readiness. The issue appears institutional rather than technological: rigid governance, static employment structures, and risk-averse cultures inhibit reform even where awareness and resources exist. Without addressing these systemic barriers, economies risk reinforcing a digital skills deficit that limits innovation diffusion across all industries.

3. The lack of venture capital availability is a universal constraint.

Globally, executives across all industries demonstrate dissatisfaction with their access to venture capital. In fact, of all 21 survey questions, the global average for venture capital availability is the lowest in the sample (50.6%), nearly ten points behind executives’ satisfaction with the availability of company funding for technological development (59.4%). Even leading industries such as IT and communications (50.8%), professional, scientific, and technical services (52.6%), and finance, insurance, and real estate (51.4%) report dissatisfaction. This could hint at a structural misalignment between existing venture capital models, which are generally designed for asset-light and rapidly scalable startups, and the capital-intensive realities of digital transformation in manufacturing, transport, or agriculture. Unless financing mechanisms evolve to support longer innovation cycles and physical investment needs, digital transformation could risk remaining concentrated in a narrow set of industries.

4. Governance frameworks remain uneven across sectors.

Banking, finance, and infrastructure benefit from decades of coordinated regulation, public investment, and institutional support for digital initiatives. In contrast, emerging digital sectors and transforming traditional industries face fragmented governance characterized by unclear regulatory pathways, weak IP protection, and limited public-private coordination. This unevenness generates uncertainty and slows digital diffusion beyond the most regulated sectors. Expanding governance frameworks to support a wider range of industries could strengthen national digital resilience and ensure more inclusive competitiveness.

We can see from these global patterns that different industries experience digital enablers in different ways. For business leaders, understanding both which industries and countries are successfully addressing specific digital challenges can inform partnership strategies, investment decisions, and talent development priorities. Recognizing that multiple pathways to competitiveness exist allows for learning from diverse models rather than assuming a single approach works universally.

Ultimately, digital competitiveness in a fragmented world depends on bridging divides. Success lies not in achieving headline scores in isolated sectors but in ensuring digital transformation spreads broadly, inclusively, and sustainably

across the economic landscape. Economies that combine robust governance, adaptable companies, and continuous human capital development across all industries, not just priority sectors, will prove more resilient than those dependent on narrow excellence, however exceptional that excellence may be.

As geopolitical tensions continue to reshape the institutional environment for digital strategy, this broad-based resilience becomes ever more critical for sustained digital competitiveness.

An analysis of the 2025 World Digital Competitiveness Ranking’s Top 10

Switzerland climbs to the top of the 2025 edition of IMD’s World Digital Competitiveness Ranking (WDCR), advancing one position from the previous year. It is followed by the US, which makes a significant leap of two positions to claim second place, and Singapore, which moves down two spots to complete this year’s podium. Hong Kong SAR continues its ascent, gaining three positions to rank fourth, while Denmark slips two places to fifth. The Netherlands shows a solid improvement, moving up two positions to sixth overall. A notable new entrant to the top 10 is Canada, which jumps an impressive six positions to rank seventh. Sweden, however, experiences a decline, dropping three spots to eighth. The United Arab Emirates also enters the top 10 for the first time, climbing two positions to ninth. Finally, Taiwan (Chinese Taipei) moves down one position to complete the top 10. Korea Republic (previously sixth) and Norway (previously 10th) drop out of the top 10 in 2025, losing nine and three positions, respectively.

Switzerland secures the top spot in the 2025 WDCR, driven by its world-leading performance in the Knowledge factor, where it maintains first position, and a significant three-position jump in the Future Readiness factor to second place. While its Technology factor ranking saw a slight decline of three positions to seventh, the country’s overall profile remains exceptionally strong and balanced. At the sub-factor level, Switzerland demonstrates leading performance in Talent (second), Training & Education (fifth), and Business Agility (third). Its ascent in Future Readiness is underpinned by improvements across its components, showcasing a society and business environment that is highly prepared for digital transformation. Switzerland’s key strengths are deeply embedded in its human capital and institutional quality. It ranks first globally for the quality of employee training, the effectiveness of its scientific research legislation, its robust intellectual property rights, and its unparalleled capacity for knowledge transfer between companies and universities. However, the slight dip in the Technology factor can be attributed to relative declines in the Regulatory Framework (seventh, down from second) and Capital (15th, down from 11th) sub-factors. Specific areas for improvement include enforcing contracts, where Switzerland ranks 40th, and the penetration of wireless broadband, where it places a surprisingly low 55th.

The US makes a significant leap into second place overall, climbing two positions from 2024. This strong performance is driven by its undisputed leadership in the Technology factor, where it ranks first globally, and a strong showing in the Knowledge (sixth) and Future Readiness (eighth) factors. The US’s core strength in Technology is built on its top-ranked Capital subfactor, which is fueled by the world’s largest pool of AI private investment (first), readily available funding for technological development (sixth), and a vibrant venture capital market as perceived by its executives (fourth). Its natural leadership in the Scientific Concentration sub-factor (second) is evidenced by top five ranks in five out of seven indicators, including second positions in both AI-related patent publications and the number of robots in education and R&D. At the indicator level, the US displays many strengths, including the world’s largest volume of internet retailing (first), the highest protection against software piracy (first), and the world’s best computer science education index (first). However, the country’s overall performance is moderated by notable weaknesses in areas related to social adaptation and talent accessibility. It ranks poorly for its attitudes toward globalization (61st) and faces challenges with its immigration laws, which are perceived as a barrier to attracting talent (ranking 64th). Other areas for improvement include the quality of employee training (39th) and public expenditure on education (14th), suggesting that while the nation excels at high-end innovation, it could face future challenges linked to an inadequate framework for talent attraction and retention.

After leading the ranking in 2024, Singapore slides to third position in the 2025 WDCR. Despite this shift, it remains a digital powerhouse, securing top-tier rankings across all three factors: Knowledge (fourth), Technology (second), and Future Readiness (sixth). Singapore’s performance is remarkably balanced, ranking in the top 10 for six of the nine sub-factors, and demonstrates exceptional strength in its Regulatory Framework (first), a testament to its business-friendly digital environment. At the indicator level, Singapore’s strengths are widespread. It tops the number of high-tech patent grants per capita worldwide (first) and achieves the second rank for both its PISA math educational

assessment scores and the effectiveness of its banking and financial services. Additionally, Singapore demonstrates high levels of institutional support for IT Integration in its economy (sixth) with strong performances in E-government scores (third) and the government’s cyber security capacity (third). Its business environment is further characterized by highly agile companies (ninth) and a positive attitude towards globalization (eighth). The decline in its overall rank can be mostly attributed to Singapore’s weaker performance across all three sub-factors in Future Readiness, including a 10-position drop in both the Adaptive Attitudes and Business Agility sub-factors. Such results can be explained by lagging levels of internet retailing (28th), low perceptions of firm flexibility and adaptability (26th), low investment in telecommunications (61st). Other persistent weaknesses include its low total public expenditure on education (63rd) and a comparatively low proportion of female researchers (46th).

Hong Kong SAR continues its impressive upward trajectory in digital competitiveness, climbing three places to rank fourth overall. This strong performance in 2025 is built on top five positions in the Technology (third) and Knowledge (fifth) factors, complemented by a solid 10th place in Future Readiness, a five-position increase from the previous year. Hong Kong’s technological prowess is highlighted by its first place ranking in the Technological Framework and Adaptive Attitudes subfactors, as well as top 10 positions in the Talent (fifth), Training & Education (third), and Business Agility (Seventh) sub-factors. Hong Kong demonstrates world-leading scores in the Talent sub-factor, with top ranks in PISA math scores (fourth), the international experience of its managers (sixth), and scientific and technical employment (seventh). Its digital competitiveness is further supported by its large proportion of high-tech exports (second) coupled with the world’s highest percentage of graduates in the sciences (first). At the indicator level, Hong Kong excels in several key areas, including the ease of starting a business (fourth), and the quality of its banking and financial services (eighth). Its Adaptive Attitudes scores are also a major asset, ranking first globally in this sub-factor, driven by the second highest smartphone possession rate and a highly positive attitude toward globalization (second). Despite these strengths, Hong Kong continues to fare poorly under the IT Integration sub-factor (29th), particularly in areas linked to institutional

strength as demonstrated by low scores concerning government cybersecurity capacity (44th) and the legal framework for privacy protection (49th).

Denmark slips two positions to fifth in the 2025 ranking but remains one of the world’s most digitally advanced economies. Its performance is balanced, with top 10 rankings in all three factors: Future Readiness (first), Technology (fifth), and Knowledge (ninth). Denmark’s top position in Future Readiness is a testament to its highly adaptive society and agile business sector. It leads the world in E-Participation (first) and E-Government (first), demonstrating a seamless integration of digital tools into civic and public life. The Business Agility sub-factor (second) is another major strength, with Danish companies ranking fourth for their agility and second for their use of big data and analytics according to executives. In the Technology factor, Denmark excels in its Regulatory Framework (second) and boasts the highest number of secure internet servers per capita globally (first). The country’s strengths are further evidenced by its top ranking for country credit rating and the quality of employee training (second). The minor drop in the overall ranking is partly due to a relative decline in the Knowledge factor, where weaknesses persist in the number of graduates in sciences (25th) and the proportion of female researchers (35th). Scientific Concentration appears to be a consistent area for improvement, with weak scores in R&D productivity by publication (47th) and a low number of high-tech patent grants (35th).

The Netherlands gains two ranks to secure sixth place in 2025. This advancement is driven by consistent improvements across all three digital factors, with the biggest gain achieved in Technology (fourth, up from eighth) followed by Future Readiness (fourth, up from seventh) and a solid seventh place in the Knowledge factor (up from ninth). The country’s technological infrastructure is world-class, reflected in its sixth place rank for the Technological Framework sub-factor, which includes having the third most secure internet servers per capita. The Netherlands also boasts an exceptional environment for Capital, ranking third in this sub-factor, supported by the second largest IT & media stock market capitalization as a percentage of GDP. In Future Readiness, the country excels in Adaptive Attitudes (third) and IT Integration (ninth), with its population showing a highly positive attitude towards globalization (third) and a high degree

of tablet possession (ninth). The Knowledge factor is bolstered by the Talent sub-factor (sixth), with managers possessing significant international experience (fourth) and the economy demonstrating a strong ability to attract foreign highly skilled personnel (seventh). Despite these strengths, the Netherlands shows room for improvement in Training & Education (25th), particularly concerning the quality of employee training (16th). Other weaknesses include a relatively low number of graduates in the sciences (45th) of which few are women (49th).

Canada makes a remarkable entry into the top 10, jumping six positions to seventh place overall. This significant leap is primarily fueled by a substantial improvement in the Future Readiness factor, climbing 10 positions to ninth, and in the Knowledge factor, where it climbs from sixth to second place. At the sub-factor level, Canada demonstrates world-leading performances in Training & Education (first), Talent (third), and IT Integration (fifth). The country ranks second for the percentage of women with degrees and sixth for higher education achievement, showcasing a highly educated workforce. The country excels in talent appeal, with a high net flow of international students (fifth) and a strong ability to attract foreign highly skilled personnel (ninth), in part due to its high levels of scientific and technical employment (third). In the Technology factor, Canada showcases a dynamic environment that attracts capital (second in the sub-factor) with significant private investment in AI (fifth) and access to venture capital that satisfies business executives (seventh). Further strengths at the indicator level include the government’s cyber security capacity (fourth), and the knowledge transfer occurring in the economy (third). Canada’s primary weaknesses lie in specific infrastructure indicators, such as wireless broadband penetration (59th) or its low proportion of high-tech exports (33rd). Further improvements could also be made in contract enforcement (53rd) and the number of AI policies passed into law (32nd).

Sweden experiences a three-position drop to eighth place in the 2025 ranking. Despite this decline, it retains strong digital attributes across all digital factors, particularly in Knowledge where it ranks third and achieves top 10 positions in all three subfactors. Sweden’s most notable attributes include high public expenditure on education (third), high quality employee training (fourth), and its scientific and technical employment (first). In the

Technology factor, Sweden remains 10th, showcasing strengths in intellectual property rights (11th), its banking and financial services (fourth), the level of AI investment (fourth) as well as the country’s credit rating (first). However, Sweden’s overall rank was impacted by a sharp decline in the Future Readiness factor (down to 11th from fourth). The most notable drop is observed in the Business Agility sub-factor, falling from ninth to 16th as a result primarily of declining business sentiment relating to the detection of opportunities and threats (41st) and entrepreneurial fear of failure (23rd). At the indicator level, while the country remains a leader in the use of big data and analytics (eighth), perceptions of company agility have weakened (16th). Other challenges include a relatively low number of female researchers (38th) and low investment in telecommunications (53rd), which could hinder future infrastructure development.

The United Arab Emirates (UAE) first time, climbing two spots to ninth place. This achievement is a testament to its focused strategy on digital transformation, reflected in outstanding performances in the Future Readiness (fifth) and Technology (sixth) factors. The UAE’s key strength lies in its world-leading Talent sub-factor (first), where it ranks first for the international experience of its managers, first for digital/technological skills, and second for attracting foreign highly skilled personnel. This ability to attract and retain top global talent is the foundation of the UAE’s digital economy. In the Technology factor, the UAE excels in its Regulatory Framework (fourth) and Capital environment (ninth). Its businessfriendly policies include immigration laws that are conducive to a more productive economy (second) and the development and application of technology (third). Further strengths include the quality of public-private partnerships (first) and the highly positive attitudes of the business world to globalization (fourth). Despite these strengths, the UAE’s performance in the Knowledge factor (12th) is held back by a weaker Scientific Concentration sub-factor (34th), performing relatively lower in R&D expenditure and personnel per capita compared to other top digital economies. At the institutional level, further improvements should be considered in increasing total public spending on education (51st) as well as a sharper focus on passing AI policies into law (57th) and implementing privacy protection laws (40th) to increase the general level of cyber security of the population.

companies ranking second for agility and third for their use of big data and analytics. Taiwan also demonstrates strengths in the Technology factor (11th), supported by a top-tier capital environment (fifth) that includes the world’s largest IT & media stock market capitalization as a percentage of GDP (first). Its technological prowess is further highlighted by its high rank for high-tech exports (fourth). The Knowledge factor (16th) remains the area with the most room for improvement, although it performs strongly in Training & Education (sixth) and Scientific Concentration (10th), boasting the second highest R&D personnel per capita. Key weaknesses that temper its overall rank include a low proportion of female researchers (56th), a high pupil-teacher ratio in tertiary education (51st), and persistent challenges in the regulatory space, ranking last (68th) for having AI policies passed into law, indicating a need to formalize its governance of

Rankings in a Nutshell

The 2025 IMD World Digital Competitiveness Ranking

2025 COMPETITIVENESS RANKING

The IMD World Digital Competitiveness Ranking presents the 2025 overall ranking for the 69 economies covered by the Center. The economies are ranked from the most to the least competitive. The Scores shown to the right are actually indices (0 to 100) generated for the unique purpose of constructing charts and graphics. The final column shows the improvement or decline from the previous year.

2025 Digital Competitiveness Ranking

The IMD World Digital Competitiveness Ranking

Methodology

The IMD World Digital Competitiveness Ranking (WDCR) analyzes and ranks the extent to which countries adopt and explore digital technologies leading to transformation in government practices, business models and society in general.

As in the case of the IMD World Competitiveness Ranking, we assume that digital transformation takes place primarily at enterprise level (whether private or state-owned) but it also occurs at the government and society levels.

Based on our research, the methodology of the WDCR ranking defines digital competitiveness into three main factors:

In turn, each of these factors is divided into 3 sub-factors which highlight every facet of the areas analyzed. Altogether, the WDCR features 9 such sub-factors. These 9 sub-factors comprise 61 criteria, although each sub-factor does not necessarily have the same number of criteria (for example, it takes more criteria to assess Training and Education than to evaluate IT integration).

Each sub-factor, independently of the number of criteria it contains, has the same weight in the overall consolidation of results, that is approximately 11.1% (100 ÷ 9 ~ 11.1).

Criteria can be hard data, which analyze digital competitiveness as it can be measured (e.g. Internet bandwidth speed) or soft data, which analyze competitiveness as it can be perceived (e.g. Agility of companies). Hard criteria represent a weight of 2/3 in the overall ranking whereas the survey data represent a weight of 1/3.

The 61 criteria include 25 new indicators which are only used in the assessment of the WDCR ranking. The rest of the indicators are shared with the IMD World Competitiveness Ranking.

In addition, two criteria are for background information only, which means that they are not used in calculating the overall competitiveness ranking (i.e., Population and GDP).

Finally, aggregating the results of the 9 sub-factors makes the total consolidation, which leads to the overall ranking of the WDCR.

What is the IMD World Digital Competitiveness Ranking?

Digital Competitiveness Factors and Sub-factors

Knowledge

Know-how necessary to discover, understand and build new technologies.

• Talent

• Training and Education

• Scientific Concentration

Overall context that enables the development of digital technologies.

• Regulatory Framework • Capital • Technological Framework

Level of country preparedness to exploit

• Adaptive Attitudes

The 2025 IMD World Digital Competitiveness Ranking

Europe - Middle East - Africa

Asia

The Americas

KNOWLEDGE

TECHNOLOGY

Factor Rankings: five-year overview

Sub-factor Rankings

IMD World Digital Competitiveness Economy Profiles

ARGENTINA

ARGENTINA

AUSTRALIA

AUSTRALIA

AUSTRIA

AUSTRIA

BAHRAIN

BAHRAIN

BELGIUM

BELGIUM

KNOWLEDGE

BOTSWANA

BOTSWANA

KNOWLEDGE

BRAZIL

BRAZIL

BULGARIA

BULGARIA

CANADA

CANADA

CHILE

TECHNOLOGY

Technological

CHINA

CHINA

FACTORS BREAKDOWN - STRENGTHS AND WEAKNESSES

COLOMBIA

COLOMBIA

CROATIA

CROATIA

CYPRUS

CYPRUS

KNOWLEDGE

FUTURE READINESS

CZECH REPUBLIC

CZECH REPUBLIC

DENMARK

DENMARK

KNOWLEDGE

FUTURE READINESS

ESTONIA

ESTONIA

KNOWLEDGE

FUTURE READINESS

FINLAND

FINLAND

KNOWLEDGE

FRANCE

KNOWLEDGE

GERMANY

KNOWLEDGE

FUTURE READINESS

GHANA

KNOWLEDGE

GREECE

GREECE

KNOWLEDGE

TECHNOLOGY

FUTURE READINESS

HONG KONG SAR

HONG KONG SAR

KNOWLEDGE

FUTURE READINESS

HUNGARY

HUNGARY

KNOWLEDGE

FUTURE READINESS

ICELAND

KNOWLEDGE

FUTURE READINESS

INDIA

INDIA

KNOWLEDGE

INDONESIA

INDONESIA

KNOWLEDGE

IRELAND

IRELAND

KNOWLEDGE

TECHNOLOGY

FUTURE READINESS

ITALY

KNOWLEDGE

TECHNOLOGY

FUTURE READINESS

JAPAN

KNOWLEDGE

JORDAN

KNOWLEDGE

TECHNOLOGY

FUTURE READINESS

KAZAKHSTAN

KAZAKHSTAN

KNOWLEDGE

KENYA

KNOWLEDGE

KOREA REP.

KOREA REP.

KNOWLEDGE

FUTURE READINESS

KUWAIT

KNOWLEDGE

LATVIA

LATVIA

KNOWLEDGE

LITHUANIA

LITHUANIA

LUXEMBOURG

LUXEMBOURG

KNOWLEDGE

TECHNOLOGY

FUTURE

MALAYSIA

KNOWLEDGE

MEXICO

KNOWLEDGE

MONGOLIA

KNOWLEDGE

NAMIBIA

NAMIBIA

KNOWLEDGE

NETHERLANDS

NETHERLANDS

TECHNOLOGY

NEW ZEALAND

NEW ZEALAND

KNOWLEDGE

NIGERIA

KNOWLEDGE

FUTURE READINESS

NORWAY

NORWAY

KNOWLEDGE

FUTURE READINESS

OMAN

KNOWLEDGE

PERU

KNOWLEDGE

PHILIPPINES

PHILIPPINES

KNOWLEDGE

FUTURE READINESS

POLAND

POLAND

KNOWLEDGE

FUTURE READINESS

PORTUGAL

PORTUGAL

KNOWLEDGE

PUERTO RICO

PUERTO RICO

KNOWLEDGE

QATAR

KNOWLEDGE

FUTURE READINESS

ROMANIA

ROMANIA

KNOWLEDGE

SAUDI ARABIA

SAUDI ARABIA

KNOWLEDGE

SINGAPORE

SINGAPORE

KNOWLEDGE

FUTURE READINESS

SLOVAK REPUBLIC

SLOVAK REPUBLIC

KNOWLEDGE

TECHNOLOGY

SLOVENIA

SLOVENIA

KNOWLEDGE

SOUTH AFRICA

SOUTH AFRICA

KNOWLEDGE

TECHNOLOGY

SPAIN

KNOWLEDGE

SWEDEN

KNOWLEDGE

FUTURE READINESS

SWITZERLAND

SWITZERLAND

(CHINESE TAIPEI)

TAIWAN (CHINESE TAIPEI)

THAILAND

KNOWLEDGE

TÜRKIYE

KNOWLEDGE

TECHNOLOGY

UNITED KINGDOM

UNITED KINGDOM

KNOWLEDGE

FUTURE READINESS

KNOWLEDGE

VENEZUELA

VENEZUELA

KNOWLEDGE

Appendices

Notes and Sources by Criteria

The source of the survey criteria is:

IMD World Competitiveness Center’s Executive Opinion Survey 2025 which was conducted from March- May 2025, with a total number of 6,162 responses used in the construction of the ranking.

Standard notes used in the data tables

When statistical data is not available or is too out-dated to be relevant for a particular economy, the name appears at the bottom of the statistical table and a dash is shown. When the data is older than the reference year, the year of the data is shown next to the criterion value.

Exchange rate

Per capita

As most data are expressed in U.S. dollars, you will find the exchange rates used at the beginning of the Statistical Tables. The sources for the Exchange Rates are International Financial Statistics Online (IMF) and national sources.

For all information presented “per capita” the sources for the population are Passport GMID (Euromonitor) and national sources.

% of GDP For all information presented as a “percentage of GDP” the sources for GDP are the OECD Main Economic Indicators and national sources.

The criteria is a background criteria. They are not taken into consideration when constructing the rankings and provided for information only.

Background

0.0.1 [B] Exchange rate

IMF International Financial Statistics

IMF World Ecopnomic Outlook April 2025

Period average.

0.0.2 [B] Population - market size

IMF World Economic Outlook April 2025

National sources

Mid-year estimates. Brazil, Bulgaria, Saudi Arabia: break in series in 2023. Croatia: new census in 2011 with a new methodology. India: break in series in 2011. Iceland, Romania as of January 1. Jordan: series have been revised according to the the new Population and Housing Census published in 2016. End of year population for 2019 and 2020. Lithuania: break in series 2011 - census revised population figure downwards by 10% (emigration to EU over past decade). Philippines: Projected population (medium assumption) excluding for 2015, which is based on the 2015 Census. Portugal: methodological change in 2011. Russia: including Crimea as of 2015. UAE: re-estimation of the national population was made by the National Bureau of Statistics in 2010 (consequent increase as of 2008).

0.0.3 [B] GDP per capita

OECD Annual GDP and components

National sources

Provisional data or estimates for most recent year. Malaysia: Data for 2023 is sum of 4 quarters. Taiwan (Chinese Taipei): Data 2021 and 2022 are revised according to the annual revisions released by DGBAS in November 2023, 2023 is the latest preliminary estimate in February 2024.

1.1.1 Educational assessment PISA - Math PISA (OECD)

http://www.oecd.org/pisa/

The OECD’s Programme for International Student Assessment (PISA) is a regular survey of 15-year olds which assesses aspects of their preparedness for adult life. PISA selects a sample of students that represents the full population of 15-year-old students in each participating country or education system, in both public and private schools. Mathematical literacy: an individual’s capacity to identify and understand the role that mathematics plays in the world, to make well-founded judgments and to use and engage with mathematics in ways that meet the needs of that individual’s life as a constructive, concerned and reflective citizen. Scientific literacy: an individual’s scientific knowledge and use of that knowledge to identify questions, to acquire new knowledge, to explain scientific phenomena, and to draw evidence based conclusions about science-related issues, understanding of the characteristic features of science as a form of human knowledge and enquiry, awareness of how science and technology shape our material, intellectual, and cultural environments, and willingness to engage in science-related issues, and with the ideas of science, as a reflective citizen. Hong Kong SAR, Netherlands, Portugal and United States: Data did not meet the PISA technical standards but were accepted as largely comparable. China: limited regions (B-S-J-Z); the municipalities of Beijing and Shanghai and the provinces of Jiangsu and Zhejiang participated.

Training & education

1.2.2 Total public expenditure on education

IMF Government Finance Statistics

Eurostat

UNESCO

National sources

Total general (local, regional and central) government expenditure in educational institutions (current and capital). It excludes transfers to private entities such as subsidies to households and students, but includes expenditure funded by transfers from international sources to government. It includes pre-primary, primary, secondary all levels and tertiary public institutions. Chile and Jordan: Budgetary central government. Philippines: Total disbursements to the Department of Education and State Colleges and Universities.

1.2.3 Higher education achievemen

OECD Education at a Glance

National sources

1.1.6

Net flow of international students

UNESCO

National sources

Net flow of internationally mobile students (inbound from abroad studying in a given country minus outbound from a given country), both sexes, in tertiary education. Data can refer to the school or financial year prior or after the reference year.

1.1.7 Female researchers

UNESCO

OECD Main Science and Technology Indicators, OECD Science, Technology and R&D Statistics (database)

Female researchers (headcount) who are mainly or partially employed in R&D. This includes staff employed both full-time and part-time. Expressed as a percentage of the total workforce (male + female)

1.1.8 Scientific and technical employment

Eurostat

OECD “”Labour Force Statistics: Employment by activities and status””

OECD Employment and Labour Market Statistics

ILOSTAT

National sources

Scientific and technical employment as a % of total employment. Defined as formal employment within the ‘scientific and technical’ sector. For more information, refer to NACE2 category M (or equivalent). Philippines: 2020 data are preliminary figures for October 2020.

1.2.4

Percentage of the population aged 25-34 that has attained tertiary-type B and tertiary-type A and advance research programs. Tertiary-type A education covers more theoretical programs that give access to advanced research programs and to professions with high general skills requirements. Tertiary-type B education covers more practical or occupationally specific programs that provide participants with a qualification of immediate relevance to the labor market. Hong Kong SAR: Figures starting from 2012 exclude post-secondary diploma or certificate and exclude foreign domestic helpers. Kazakhstan: The data were reviewed taking into account the inclusion of graduates in technical and vocational education organizations (MCKO-5). New-Zealand and Slovenia: break in series. Peru: Tertiary education type A refers to University tertiary level and terciary education type B refers to Non-university tertiary level; for 25 years and more. Singapore: proportion of resident non-students aged 25-34 years with polytechnic, professional qualification or other diploma, or university qualification. Japan: Data for tertiary education include upper secondary or post-secondary non-tertiary programmes (less than 5% of adults are in this group).

Pupil-teacher ratio (tertiary education)

UNESCO

National sources

Average number of pupils per teacher at a given level of education, based on headcounts of both pupils and teachers. Tertiary education (ISCED levels 5 to 8). Tertiary education builds on secondary education, providing learning activities in specialised fields of education. It aims at learning at a high level of complexity and specialisation. Tertiary education includes what is commonly understood as academic education but also includes advanced vocational or professional education. Czech Republic, France, Ireland and Poland: based on full-time equivalents. Philippines: Academic Year 2017-2018 data. Data includes students and faculty from both public and private tertiary educational institutions.

1.2.5 Graduates in Sciences

OECD Education at a Glance

UNESCO

Share of graduates in Natural Sciences; Mathematics and Statistics; Information and Communication technologies; Engineering, manufacturing and construction. In tertiary education (ISCED2011 levels 5 to 8), both sexes (%). Japan: Data on information and communication technologies are included in other fields. Jordan: 2020 data used in 2019. Philippines: includes Medical and Allied Disciplines Graduates.

1.2.6 Women with degrees

OECD Education at a Glance

National sources

Educational attainment in tertiary education of 25-64 year-old females expressed as a percentage of the female population 25-64. In most countries data refer to ISCED 2011 (codes 5/6/7/8). Japan: includes data from another category. Kazakhstan: Share of women with tertiary level degree (age 25-44).

1.2.7 Computer science education index

World University Ranking, Times Higher Education

IMD WCC developed index calculated from the Times Higher Education ranking of the top 1’000 university computer science courses, measuring the quantity and quality of the universities in each economy. 33% weighting is the number of universities in THES ranking for each country, 33% weighting is the total score, 33% weighting is the total score per capita.

Scientific concentration

1.3.1 Total expenditure on R&D (%)

OECD Main Science and Technology Indicators

UNESCO

National sources

National estimates, projections or provisional data for the most recent year. Chile, Denmark, France, Japan, Korea, Netherlands, Portugal, Slovenia, Spain and Sweden: break in series. Hungary (up to 2003), Israel: defense excluded(all or mostly). Indonesia: Estimate based on target GERD by the Ministry of Science and Technology. Sweden: underestimated or based on underestimated data. USA: excludes most or all capital expenditure.

1.3.2 Total R&D personnel per capita

OECD Main Science and Technology Indicators

UNESCO National sources

National estimates, projections or provisional data for most recent year. Czech Republic, Colombia, Denmark, Finland, Korea, Mexico, Netherlands, Hungary, Japan, Portugal, Slovenia, Sweden and Taiwan (Chinese Taipei): break in series. Mongolia: Total number of employees in science sector. United Kingdom: underestimated or based on underestimated data. Jordan, Philippines: based on headcount, not FTE.

1.3.3 R&D productivity by publication

NSF Science & Engineering Indicators

Courtesy: National Science Foundation

National sources

The indicator is calculated as a ratio between the number of scientific articles by author’s origin and the total expenditure in R&D as % GDP, which clearly include the input costs to produce research (e.g. researchers’ salaries, equipement etc.). The result gives therefore the number of scientific articles published every year for a one percent (of GDP) expenditure in R&D activities. This measure can be consider as a proxy to assess the efficiency (or productivity) in producing high-level scientific research at country level.

1.3.4 High-tech patent grants

WIPO Statistics Database

TIPO for Taiwan (Chinese Taipei)

High-Tech patent grants as a percentage of total patent grants (Direct and PCT national phase entries) by applicant’s origin. Three year average to reduce volatility. Counts are based on the grant date. Country of origin refers to the country of residency of the first-named applicant in the application. Taiwan (Chinese Taipei): data compiled by TIPO using data supplied by international patent offices (USPTO, JPO, EPO, KIPO, SIPO).

1.3.5 AI-related patent publications

WIPO Statistics Database

AI-related patent publications. (Direct and PCT national phase entries) by applicant’s origin. Three year average to reduce volatility. Country of origin refers to the country of residency of the first-named applicant in the application.

1.3.6 Robots in Education and R&D

World Robotics

International Federation of Robotics (IFR)

Industrial robot as defined by ISO 8373:2012: an automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which can be either fixed in place or mobile for use in industrial automation applications.

The primary source is data on robot installations by country, industry and application that nearly all industrial robot suppliers worldwide report to the IFR Statistical Department directly. Several national robot associations collect data on their national robot markets and provide their results as secondary data to the IFR. This data is used to validate and complete the IFR primary data.

IFR Statistical Departments estimates the operational stock assuming an average service life of 12 years with an immediate withdrawal from service afterwards.

1.3.7 AI articles

Scopus

Annual count of the number of articles in Scopus using the keyword artificial intelligence, by author’s institution, per capita.

Regulatory framework

2.1.1 Starting a business

Doing Business 2020 - World Bank

The distance to frontier score aids in assessing the absolute level of regulatory performance and how it improves over time. This measure shows the distance of each economy to the “frontier,” which represents the best performance observed on each of the indicators across all economies in the Doing Business sample since 2005. This allows users both to see the gap between a particular economy’s performance and the best performance at any point in time and to assess the absolute change in the economy’s regulatory environment over time as measured by Doing Business. An economy’s distance to frontier is reflected on a scale from 0 to 100, where 0 represents the lowest performance and 100 represents the frontier. For example, a score of 75 in DB 2016 means an economy was 25 percentage points away from the frontier constructed from the best performances across all economies and across time. A score of 80 in DB 2017 would indicate the economy is improving. In this way the distance to frontier measure complements the annual ease of doing business ranking, which compares economies with one another at a point in time.

2.1.2 Enforcing contracts

Doing Business 2020 - World Bank

The distance to frontier score aids in assessing the absolute level of regulatory performance and how it improves over time. This measure shows the distance of each economy to the “frontier,” which represents the best performance observed on each of the indicators across all economies in the Doing Business sample since 2005. This allows users both to see the gap between a particular economy’s performance and the best performance at any point in time and to assess the absolute change in the economy’s regulatory environment over time as measured by Doing Business. An economy’s distance to frontier is reflected on a scale from 0 to 100, where 0 represents the lowest performance and 100 represents the frontier. For example, a score of 75 in DB 2016 means an economy was 25 percentage points away from the frontier constructed from the best performances across all economies and across time. A score of 80 in DB 2017 would indicate the economy is improving. In this way the distance to frontier measure complements the annual ease of doing business ranking, which compares economies with one another at a point in time.

2.1.7 AI policies passed into law

Digital Policy Alert

Capital

Total active mobile 5G subscriptions, excluding broadband connections on dedicated data SIM cards or USB dongles. Data given as a percentage of the total mobile market. Technology

Cumulative count of AI related bills passed into law.

2.2.1 IT & media stock market capitalization

Refinitiv - used to be Thomson Reuters - Thomson One banker

Datastream Telecom, Media and IT (TMT) Market Value in national currency. Calculated as a percentage of Datastream Total Market Value in national currency. Figures for close-of-business on the 29th March each year.

2.2.4 Country credit rating

Fitch, Moody’s and S&P

IMD WCC created index of the three country credit ratings Fitch, Moody’s and S&P. Each rating, including the outlook, is converted to a numerical score from 20-0 and totalled for each country.

2.2.6 Investment in Telecommunications

Passport, Source: © Euromonitor International

National sources

Investment refers to as the annual capital expenditure; this is the gross annual investment in telecom (including fixed, mobile and other services) for acquiring property and network. The term investment means the expenditure associated with acquiring the ownership of property (including intellectual and non-tangible property such as computer software) and plant. This includes expenditure on initial installations and on additions to existing installations where the usage is expected to be over an extended period of time. Note that this applies to telecom services that are available to the public, and exclude investment in telecom software or equipment for private use.

2.2.7 AI private investment

Quid via Stanford AI Index Report

Annual private investment in artificial intelligence. Includes companies that received more than $1.5 million in investment. This data is expressed in US dollars.

Technological framework

2.3.2 Mobile broadband subscribers Fitch Solutions - used to be Business Monitor International

2.3.3 Wireless broadband

Passport, Source: © Euromonitor International

The penetration rates of wireless broadband is calculated by dividing the number of Wireless Broadband subscribers by the total population and multiplying by 100. Wireless-broadband subscriptions refer to the sum of satellite broadband, terrestrial fixed wireless broadband and active mobile-broadband subscriptions to the public Internet. The indicator refers to total active wireless-broadband Internet subscriptions using satellite, terrestrial fixed wireless or terrestrial mobile connections. Broadband subscriptions are those with an advertised download speed of at least 256 kbit/s. In the case of mobilebroadband, only active subscriptions are included (those with at least one access to the Internet in the last three months or with a dedicated data plan). The service can be standalone with a data card, or an add-on service to a voice plan. The indicator does not cover fixed (wired)-broadband or Wi-Fi subscriptions. Both residential and business subscriptions should be included.

2.3.4 Internet users

World Development Indicators (World Bank)

National sources

Average of available sources

2.3.5 Internet bandwidth speed

Broadband Speed League

Ookla

SpeedTest Pro

Average connection speed in Mbps: data transfer rates for Internet access by end-users. Values presented are an average compiled from three different sources: Broadband Speed League (Jun. 2024); Ookla (Jan. 2025); and SpeedTest Pro (Feb. 2023)

2.3.6 High-tech exports (%)

World Development Indicators (World Bank)

National sources

High-technology exports are products with high R&D intensity, such as in aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery.

2.3.7 Secure internet servers

Netcraft (http://www.netcraft.com/) and World Bank population estimates.

publicly-trusted TLS/SSL certificates, Netcraft Secure Server Survey

Future readiness

Adaptive attitudes

3.1.1 E-Participation UN E-Government Knowledge Database

The e-participation index (EPI) measures the use of online services to facilitate provision of information by governments to citizens (“e-information sharing”), interaction with stakeholders (“e-consultation”), and engagement in decision-making processes (“e-decision making”).

3.1.2 Internet retailing

Passport, Source: © Euromonitor International National sources

Retail Value excluding sales tax. Iceland Based on data from Centre for Retail Studies Iceland. Total turnover in online retail with Icelandic cards.

3.1.3 Tablet possession

Passport, Source: © Euromonitor International

Percentage of households having at least one item. Portable, usually battery-powered, and very thin personal computer contained with a touchscreen panel.

3.1.4 Smartphone possession

Passport, Source: © Euromonitor International National sources

Percentage of households having at least one item. A smartphone is a cellular telephone with an integrated computer and other features not originally associated with telephones, such as an operating system, Web browsing, music and movie player, camera and camcorder, GPS navigation, voice dictation for messaging, the ability to run software applications, etc.

3.2.2 World robots distribution

World Robotics

International Federation of Robotics (IFR)

Industrial robot as defined by ISO 8373:2012: an automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which can be either fixed in place or mobile for use in industrial automation applications.

The primary source is data on robot installations by country, industry and application that nearly all industrial robot suppliers worldwide report to the IFR Statistical Department directly. Several national robot associations collect data on their national robot markets and provide their results as secondary data to the IFR. This data is used to validate and complete the IFR primary data.

IFR Statistical Departments estimates the operational stock assuming an average service life of 12 years with an immediate withdrawal from service afterwards.

3.2.6 Entrepreneurial fear of failure

Global Entrepreneurship Monitor

Percentage of 18-64 population perceiving good opportunities to start a business who indicate that fear of failure would prevent them from setting up a business.

3.3.1 E-Government

UN E-Government Knowledge Database

The E-Government Development Index presents the state of E-Government Development of the United Nations Member States. Along with an assessment of the website development patterns in a country, the E-Government Development index incorporates the access characteristics, such as the infrastructure and educational levels, to reflect how a country is using information technologies to promote access and inclusion of its people. The EGDI is a composite measure of three important dimensions of e-government, namely: provision of online services, telecommunication connectivity and human capacity.

3.3.4 Software piracy

BSA Global Software Survey

The BSA Global Software Survey calculates unlicensed installations of software that runs on PCs — including desktops, laptops, and ultra-portables, such as netbooks. A key component of the BSA Global Software Survey is a global survey of more than 20,000 home and enterprise PC users, conducted by IDC. In addition, a parallel survey was carried out among 2,200 IT managers in 22 countries. Please consult the original report for a more detailed explanation of the methodology.

3.3.5 Government cyber security capacity

Varieties of Democracy (V-Dem)

Digital Society Project

Does the government have sufficiently technologically skilled staff and resources to mitigate harm from cybersecurity threats?

0: No. The government does not have the capacity to counter even unsophisticated cyber security threats.

1: Not really. The government has the resources to combat only unsophisticated cyber attacks.

2: Somewhat. The government has the resources to combat moderately sophisticated cyber attacks.

3: Mostly. The government has the resources to combat most sophisticated cyber attacks.

4: Yes. The government has the resources to combat sophisticated cyber attacks, even those launched by highly skilled actors.

3.3.6 Privacy protection by law exists

Digital society project

Question: Does a legal framework to protect Internet users’ privacy and their data exist?

Responses: 0: No. 1: Yes

Index to Criteria

The first number indicates the Competitiveness Factor, the second number indicates the sub-factor and the third number indicates the criterion number.

B

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