Corporate Innovation Initiatives

What do two decades of innovation research reveal about staying power in a shifting world?   This year’s “Most Innovative Companies” report does more than spotlight today’s leaders. It explores what it takes to lead consistently through change, and how innovation excellence has evolved alongside digital disruption, AI acceleration, and growing geopolitical complexity. One of the many findings: Over the past two decades, #VentureCapital has served as an early signal for where technological disruption is heading. In 2005, #IoT led the pack. Today? #GenAI and broader AI applications have taken center stage, commanding the lion’s share of VC interest. Innovation capital is making a clear bet on AI’s disruptive power: ➡️ Agentic AI is rewriting the rules, performing complex tasks like debugging code or generating prototypes autonomously ➡️ Product development cycles are compressing, with some companies seeing up to a 60% faster time-to-concept ➡️ Software engineering is being redefined, as Satya Nadella notes: agents now write 30% of Microsoft’s code This isn’t just a tech trend, it’s a strategic signal for investors, corporates, and founders alike. And it’s redefining the innovation talent model and competitive tempo. What does it take for Europe to be at the forefront of this innovation? 🔗 Read more about it in our full report: https://on.bcg.com/44kEuw7 #Innovation #BCG

What should the composition of corporate venture capital (CVC) teams be?   In this LinkedIn series of posts, I am sharing the insights gained from my research on over 160 CVC units and from many workshops on corporate innovation and CVC that I conducted with large global corporations.   Most CVCs are small, lean organizations, with between three and nine investment professionals (fewer in the U.S., larger outside the U.S.). This corresponds well to the teams at a typical institutional VC firm. However, since CVCs invest in fewer companies than VC firms, an average CVC unit has only about five portfolio companies per each investment team member.    More surprising, and less efficiently, one-tenth of CVCs do not have a single person working full-time, evidencing lack of commitment by a corporate sponsor (these CVCs, not surprisingly, have a lower chance of survival).   Four of every ten CVCs have a business development team, which is in charge of connecting portfolio companies with the parent and helping them navigate corporate bureaucracy. Whether this arrangement is needed and whether it works will depend on the CVC’s objectives and on the types of investment the CVC makes (in the parent’s core industry, adjacent space, or elsewhere).   Should your CVC team be composed of insiders or outsiders? Successful CVCs seem to be uniquely positioned both “inside” and “outside” their organization. The most efficient CVCs include both executives with institutional VC experience (not necessarily in the exact domain of the parent company), who are deeply embedded in the innovation ecosystem, and ones with deep connections to the parent company and intimate knowledge of its culture. CVCs with only insiders have more trouble seeing the light of day when they build their deal flow or seek syndication with other investors.   Please share your CVC experience with the community here.   Check the previous CVC post about Parent norms if you missed it - https://lnkd.in/g2nedwT2 The next CVC post will be on CVC team compensation. Follow me to stay tuned.   This research has been supported by Venture Capital Initiative at the Stanford University Graduate School of Business. #stanford #stanfordgsb #venturecapital #startups #innovation #technology #corporateventure

Earlier today the UK Chancellor of the Exchequer Rachel Reeves outlined her growth strategy for the UK, presenting a vision for turning the country into "Europe's Silicon Valley." But to create genuine innovation ecosystems, we need to understand what made Silicon Valley successful in the first place. It wasn't just about reducing barriers - it was about decades of strategic (entrepreneurial) public investments actively shaping and creating markets. The UK has historically underinvested compared to its peers. Public investment has averaged just 2.6% of GDP over the last 25 years versus the G7 average of 3.5% and OECD average of 3.7%. While the UK has now reached the OECD average of 2.7% for gross domestic expenditure on R&D, the UK can and must do better to emulate Silicon Valley’s success. Tax breaks alone aren't enough - currently, the UK provides about twice as much tax relief as direct funding for business R&D. Recent lessons from the US demonstrate that public funding can be made conditional on business investment in areas like R&D, helping to de-financialize businesses that attempt to reap profits without real investment. But without the right institutions, it will be hard for the UK to compete with the US and China. We have relatively weak public financial institutions - nowhere near the scale of Brazil's BNDES or Germany's KfW (see my paper with Laurie Macfarlane below). Compare Germany's Fraunhofer system (€3.4bn/year, 32,000 staff, 76 centers) with the UK Catapult network (£1.6bn over 5 years). Real innovation ecosystems need sustained funding and institutional networks that connect research to markets. An entrepreneurial state isn't about top-down direction - it's about dynamic networks catalyzing innovation across entire value chains. ---- 🔗 The Entrepreneurial State: https://lnkd.in/eR_8pxiH 🔗 Industrial Policy with Conditionalities: https://lnkd.in/e-PrNF47 🔗 Mission-oriented development banks: https://lnkd.in/eEKrNcSC 🔗 Mission-oriented Industrial Strategy: https://lnkd.in/eHDNeiNu 🔗 Mission-oriented Policy Hub: https://lnkd.in/ePZtUTKg

10 𝗜𝗻𝘀𝘁𝗿𝘂𝗺𝗲𝗻𝘁𝘀 𝗳𝗼𝗿 𝗙𝘂𝘁𝘂𝗿𝗲 𝗦𝗲𝗻𝘀𝗲𝗺𝗮𝗸𝗶𝗻𝗴 Navigating uncertainty isn’t just a challenge—it’s an opportunity for visionary leaders. By leveraging foresight-driven sensemaking, you can anticipate change more effectively, develop highly adaptive and antifragile strategies, and unlock transformative innovations in an early stage. Here are 10 essential, field-proven instruments to enhance your foresight and ability to shape a thriving future for you and your organization: 1️⃣ 𝗛𝗼𝗿𝗶𝘇𝗼𝗻 𝗦𝗰𝗮𝗻𝗻𝗶𝗻𝗴 – Detect early signals of emerging trends, risks, and opportunities to stay ahead of the curve. 2️⃣ 𝗧𝗿𝗲𝗻𝗱 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 – Identify ongoing trends, their drivers, and potential impacts on industries and societies. 3️⃣ 𝗖𝗿𝗼𝘀𝘀-𝗜𝗺𝗽𝗮𝗰𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 – Evaluate how different trends, events, or factors influence each other over time. 4️⃣ 𝗪𝗲𝗮𝗸 𝗦𝗶𝗴𝗻𝗮𝗹𝘀 & 𝗪𝗶𝗹𝗱 𝗖𝗮𝗿𝗱𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 – Recognize early indicators of change (weak signals) and prepare for high-impact, unexpected events (wild cards). 5️⃣ 𝗙𝘂𝘁𝘂𝗿𝗲𝘀 𝗪𝗵𝗲𝗲𝗹 – A visual brainstorming tool to map out direct and indirect consequences of a change or event. 6️⃣ 𝗗𝗲𝗹𝗽𝗵𝗶 𝗠𝗲𝘁𝗵𝗼𝗱 – A structured forecasting technique that gathers expert consensus to enhance decision-making. 7️⃣ 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 – Develop multiple plausible future scenarios to prepare for uncertainty and explore strategic options. 8️⃣ 𝗖𝗮𝘂𝘀𝗮𝗹 𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 (𝗖𝗟𝗔) – A deep analysis framework that uncovers different layers of meaning, systemic causes, and underlying worldviews. 9️⃣ 𝗧𝗵𝗿𝗲𝗲 𝗛𝗼𝗿𝗶𝘇𝗼𝗻𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 – Helps decision-makers think about present and future simultaneously by categorizing innovation and change into three time-based horizons. 🔟 𝗕𝗮𝗰𝗸𝗰𝗮𝘀𝘁𝗶𝗻𝗴 – Starts with a desirable future vision and works backward to identify necessary steps to achieve it. In an era of constant change and opportunity, these tools help you and your organization move beyond short-term thinking and develop long-term strategic foresight to drive imagination, innovation, and antifragility. 👉 Follow Ewa Lombard, PhD, and Sebastian Baumann for more insights on foresight, visionary leadership, and future-fit decision-making. Press 🔔 to stay updated on upcoming posts, articles, and our peer-reviewed papers on these topics. 👉 Find more info on our 2025 special 𝗙𝗨𝗧𝗨𝗥𝗘 𝗨𝗡𝗙𝗢𝗟𝗗𝗜𝗡𝗚 - exclusive visionary leadership retreats and trainings - at Gravity & Grandeur

New streaming data sources and AI’s use of them have revitalized the real-time event stream processing market and boosted revenue. Product leaders can use this research to assess how real-time data, analytics and AI can enhance and differentiate their offerings and adjust their roadmaps to leverage this potential. Gartner recommends that product leaders: 🔵 Allocate a portion of the engineering budget to evaluate the accessibility and applicability of real-time data and analytics that can impact desired business outcomes. Do so by experimenting with new data streams and event logs to understand their ability to inform and adapt products and services. 🔵 Work with engineering teams to design an architecture that can leverage real-time event stream data by identifying technology and requisite technology partnerships to consume the data within the reasonable confines of your product’s existing architecture. 🔵 Demonstrate the positive effect on decision quality and outcomes that result from including real-time contextual data in your products and services. Do so by measuring the accuracy of models that either predict outcomes or recommend actions, as well as embedding the best models in decision workflows. I asked Kevin R. Quinn, Vice President, Analyst - Technical Product Management, Gartner why he believe this research matters: 💡 "AI is accelerating every aspect of business. Decisions can’t just be based on what happened, but need to account for what is happening right now." 💡"Real-time data enables timely decision-making, enhances responsiveness, improves operational efficiency, and provides a competitive edge in rapidly changing environments." Our research shows how the market for real-time streaming data is changing, and how it is more accessible and relevant for providers and end-users, than ever before. Check out the insights from Kevin R. Quinn and myself (David Pidsley) which is exclusively available to Gartner clients who are product leaders subscribed to our "Emerging Technologies and Trends Impact on Products and Services" research. ▶️ "Emerging Tech: Revolutionize Your Products With Real-Time Data and AI" [Published 31 January 2025] 🔗 https://lnkd.in/ev7nk82R (requires client login) #DecisionIntelligence #RealTime #Data #AI #RealTimeData #StreamingData #StreamingAnalytics #StreamAnalytics #EventStream #EventStreamProcessing

Fascinating Anthropic Economic Index report on "𝗨𝗻𝗲𝘃𝗲𝗻 𝗴𝗲𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰 𝗮𝗻𝗱 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻" released today representing the rapid, yet 𝘶𝘯𝘦𝘷𝘦𝘯 adoption of AI across the world. In the United States alone, it only took two years for 25% of the U.S. population to adopt AI. ➡️ Even the internet took five years to hit the adoption rates that AI reached in two years. ➡️ Electricity took over 30 years to reach farm households after urban electrification. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁 𝘀𝗵𝗼𝘄𝗲𝗱: 🚀 AI adoption is surging: In the US, 40% of employees now use AI at work, doubling over two years. Unlike past technologies, AI diffuses rapidly thanks to its ease of use and digital infrastructure fit. 🌍 Adoption is uneven: The Anthropic AI Usage Index reveals that advanced economies like Singapore, Canada, Israel, and the US see much higher per-capita AI usage compared to emerging economies, with income and digital infrastructure driving these differences. 🇺🇸 In the U.S., local economy factors shape patterns of use: DC leads per-capita usage (3.82x population share), but Utah is close behind (3.78x). For example, elevated use for IT in California, for financial services in Florida, and for document editing and career assistance in DC. 🇻🇳 The United States, Brazil, Vietnam, and India represent the countries with the highest total usage within a given Anthropic AI Usage Index tier 🇧🇷 In Brazil, translation services and language learning has been driven by the country's judicial system being an early adopter of AI. 🏢 Enterprise deployment is automation-heavy: Businesses integrating AI via API primarily automate specialized tasks (77% are automation patterns), especially coding and admin work. Cost per task matters less than model capabilities and context availability, indicating AI’s economic impact hinges on organizational investments and restructuring. ⚡ Implications for productivity & inequality: Productivity gains may concentrate in already-prosperous regions and automation-ready sectors—potentially increasing inequality. 🧠 High AUI regions are seeing more diverse, augmented human-AI collaboration, while lower-AUI countries focus on directive, automated use. 𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: The economic impacts of AI are still unfolding, with early signs of both transformative potential and the risk of widening digital divides. Policymakers and business leaders need to act so these gains benefit all, not just the already-advantaged. Check out the full report for data, maps, and policy questions: https://lnkd.in/gTJAniWg #AI #Anthropic #EconomicIndex #DigitalTransformation #TechAdoption #FutureOfWork #Inequality

The successful adoption of legal technology requires a methodical approach that balances innovation with practical implementation. Key elements include: 1) Strategic Process Mapping Understanding your current workflow forms the foundation of effective digital transformation. Begin by documenting how your team actually works—not how they should work on paper. This means tracking time allocation across tasks, identifying repetitive processes, and gathering direct feedback from clients about service delivery pain points. By mapping these workflows to strategic objectives, firms can identify where technology can create the most significant impact. 2) Outcome-Based Goal Setting Move beyond abstract objectives by establishing concrete, measurable targets that link directly to business outcomes. Rather than pursuing technology adoption for its own sake, focus on specific improvements in service delivery. For example, reducing contract review time from four hours to one hour per document provides a clear metric for success. 3) Rigorous Solution Evaluation Have your team (and likely key users) test potential solutions using their most challenging matters and complex workflows. Further test solutions through sandboxes and proof of concept excercises. This practical evaluation approach helps ensure that selected tools address real needs rather than creating additional complexity. 4) Structured Implementation Planning Successful technology adoption requires dedicated leadership and clear accountability. Develop a phased rollout plan that designates practice group champions and establishes regular review cycles. These champions should have allocated time for implementation oversight, and the firm should conduct formal assessments at 30, 60, and 90-day intervals to measure adoption progress and address emerging challenges. Note: I've already shared in a prior post another critical element - change management. The link to it is in the comments. #legaltech #innovation #law #business #learning

Nations’ capabilities in frontier technologies will drive their fortunes. There is deep danger of this accentuating global wealth polarization, but there is also a real opportunity for developing countries to accelerate faster than the leaders. An excellent UN Trade and Development (UNCTAD) report on frontier technologies globally lays the current state and how we can shape a more inclusive global future. (Link in comments) Some of the key points: 🌍 $16 Trillion Prize, Running Fast Frontier‑tech revenue is set to jump from $2.5 trillion in 2023 to $16.4 trillion by 2033, with AI alone reaching $4.8 trillion and IoT $3.1 trillion. For developing countries, that growth window is large but time‑bound; early adoption can secure export niches before global standards solidify. ⚠️ Innovation Bottleneck Just 100 firms command over 40% of global business R&D, and half of that spend is in the United States. Such dominance skews AI toward capital‑intensive models, risking a loss of labor‑cost advantage for lower‑income economies. 🔧 Three Levers for Catch‑Up UNCTAD highlights a feedback loop: better compute and connectivity enable bigger data sets; richer data improve local algorithms; skilled talent then scales usage, justifying more infrastructure outlays. Grounded national plans should target these levers in parallel, not sequentially. 🤝 Practical Adoption Rules Field cases distil four rules: design for weak infrastructure; mine non‑traditional data; keep user interfaces simple; and form partnerships for expertise and finance. Examples range from offline crop‑diagnosis apps in Colombia to battery‑powered X‑ray units in South Sudan. 🚀 Evidence of Momentum Brazil, China, India and the Philippines already punch above their income class on UNCTAD’s readiness index, while developer numbers in Nigeria, Ghana and Indonesia are growing 30–45 % a year. Coupled with broader calls for inclusive AI governance, these signals show that emerging economies are positioned not just to adopt AI but to help shape its global uptake.

🎯 Product Innovation Secret: Your Users Are Already Building Your Next Big Feature Dream11 SVP of Product Vaibhav Kokal revealed how their most successful feature came from an unexpected place: their users were already building it on Telegram. Their popular "Guru" feature wasn't conceived in a boardroom or through complex market research. The inspiration? Their own users... on Telegram! 🤯 Here's why this is brilliant: 1.Dream11's users were creating informal prediction communities on Telegram 2.Instead of fighting this behavior, they turned it into their "Guru" feature 3.Result: Massive engagement boost and organic user acquisition 🎯 Key Takeaways: • Your best product ideas might be hiding in plain sight • Innovation often means observing and adapting, not inventing • Users will find ways to fulfill their needs - your job is to make it easier 🔍 Real-World Application: → Check your app's Reddit/Discord/Telegram communities → List the top 3 unofficial workarounds users have created → Evaluate which one could become your next native feature 💡 This reminds me of how Instagram stories came from observing how people were using Snapchat, or how Twitter's hashtags emerged from user behavior. 👉 Watch the full breakdown on my Behind The Featuren YouTube Channel: Link in comments #ProductInnovation #UserBehavior #ProductStrategy #FeatureDiscovery #ProductGrowth #GameDesign #GrowthStrategy

I’m pleased to share WIPO’s new Innovation Economics and Policy Design webpage. A great resource curated by our Innovation Economics team for policymakers, entrepreneurs and researchers. This platform is designed to provide you with the latest economic insights and innovation trends to help you understand how innovation can elevate income, boost economic growth and improve standards of living. It breaks down complex economic insights into concise, easy-to-digest articles. Key highlights include: -      The role of innovation capabilities: How strategic policy design and smart specialization can transform innovation ecosystems. -      Policy impact: How government policies influence innovation. -      Resources Hub: A collection of datasets, economic papers and guidelines to help you conduct your own analysis. Explore the webpage here: https://lnkd.in/esGmUNJV One of the highlights is our latest World Intellectual Property Report (WIPR), a flagship WIPO publication that focuses on how policymakers can make innovation policy work for development. You can explore the full report or explore specific insights: https://lnkd.in/gCAGtnFT The IP and Innovation Ecosystem sector also assists countries develop National IP Strategies that align with economic goals, boost entrepreneurship and industrial growth, and help countries specialize in high-value industries. Explore the new webpage and join us in driving the future of innovation policy. #InnovationEcosystem #WIPO #WorldIPReport #InnovationCapabilities #SmartSpecialization #NationalIPStrategies #IPforDevelopment #Policymaking #InnovationEconomics #PolicyDesign