Ken Eisner

At its best, entrepreneurship doesn’t just create new products; it creates new possibilities. Possibilities for how we solve real problems, serve underserved communities, and reimagine systems that no longer work. In my work with founders and early-stage teams, I’ve seen innovation thrive from focusing on impact, building companies that solve challenges with measurable outcomes, not just market share. The most compelling startups today aren’t just scaling, they’re serving. They’re asking: What problem are we solving that matters? Who are we helping that others have overlooked? How do we build sustainably, not just quickly? Entrepreneurship is one of the most powerful engines we have for economic growth, for social progress, and for rethinking what business is capable of.

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A valuable contribution to the challenges many of us are navigating in practice, particularly in understanding the different forms of collective action and how they work together to deliver impact at scale.

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The INNOVATE Act (S.853) has been introduced in the Senate, proposing important reforms to the SBIR and STTR programs, often called America’s Seed Fund. Key provisions include: Strategic Breakthrough Awards to scale promising technologies. A new Phase 1A pathway for first-time applicants. Fixed-price contracting to align with commercial practices. Faster award decision timelines to speed innovation. These programs have powered some of America’s most impactful companies over the last four decades. It will be worth following closely as this legislation moves forward — the potential to reshape how early-stage technologies are funded and scaled is significant.

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Some great insights from 2026 EducationDynamics benchmarks report. Two that show how quickly marketing/enrolment is changing: 1) Zero‑click searches from prospective students are becoming the norm as Google answers 78% of education searches with an AI Overview. Almost half of these ending without a click, meaning students may never hit your website. 2) On the enrolment side, 65% of applicants want a decision within a week (and even more remarkable that 37% want one within a day). This speed matters as 72% enroll at the first school that admits them. Even if US data, this is some good context for Canadian universities and colleges working on marketing or enrolment strategies for this year. Check it out (it’s gated but free): https://lnkd.in/gTEjENr4

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One of the most important conversations I heard in Davos today wasn’t about more AI. It was about whether we trust the systems we’re building enough to deploy them at scale. At a Rethinking Risk session at Davos 2026, leaders from media, government, multilateral institutions, and global finance kept circling the same concern: the erosion of trust. The conversation included Ravi Agrawal, Editor-in-Chief, Foreign Policy; Rebeca Grynspan, Secretary-General, UN Conference on Trade and Development (UNCTAD); Amer Bisat, Minister of Economy and Trade, Republic of Lebanon; Amb. Yusuf Maitama Tuggar, Minister of Foreign Affairs, Federal Republic of Nigeria; Stephanie von Friedeburg, Managing Director & Global Head of Public Sector, Citi. Across very different vantage points, the message was consistent: misinformation, selective or low-quality data, and a growing post-truth environment are undermining consensus, multilateralism, and sound risk analysis. When trust erodes: — due diligence weakens — uncertainty rises and risk premia increase — fact-based decision-making breaks down for governments and businesses alike The key takeaway: AI doesn’t fail at deployment because the models aren’t powerful enough. It fails when the systems around it aren’t trusted. Rebuilding trust isn’t just a technical challenge. It requires rigorous verification and higher-quality data; transparent analytics and governance; and inclusive, cross-stakeholder consensus-building. As the World Economic Forum continues to emphasize, trust isn’t a soft value layered onto innovation. It’s a prerequisite for scale, resilience, and long-term economic coordination. If we want AI to reduce risk rather than amplify it, we have to start by designing systems people and institutions can trust. That may be the hardest work ahead. And also the most important.

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Last month, I was fortunate to be invited to speak with Scott Roman and Wharton Online for a Q&A on PE Portfolio Operations. We spoke a bit about developments in AI and how we're seeing it across the Ops Partner space. I'd welcome folks reaching out to weigh in on how they're staying ahead of the curve on AI in a value creation context. Maybe we have a chance to be the tide that lifts all boats for the betterment of the asset class as a whole. www.operatingpartner.com

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New from JFF: 𝗟𝗶𝗻𝗸, 𝗟𝗲𝗮𝗿𝗻, 𝗟𝗲𝗮𝗱. Public and private education and workforce data hold answers to how people move into quality jobs—but today, those systems are disconnected. With new tools (including AI), we can responsibly link cross-sector data to illuminate pathways, improve program design, and expand economic mobility for all—including learners and workers facing barriers to economic advancement. Our new paper—𝗟𝗶𝗻𝗸, 𝗟𝗲𝗮𝗿𝗻, 𝗟𝗲𝗮𝗱: 𝗔 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗣𝘂𝗯𝗹𝗶𝗰-𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻-𝘁𝗼-𝗪𝗼𝗿𝗸 𝗗𝗮𝘁𝗮 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽𝘀—explains what’s possible and how leaders can get started. It outlines practical moves—from market-based contracting strategies to policy simplification and innovation investments—and real use cases, like connecting student information systems with employer hiring data and aligning college and employer learning platforms to close skills gaps. Read the paper and see what linked data can unlock for your region, your learners, and your workforce. Read the paper here: https://hubs.la/Q03PwmQh0 #EconomicMobility #PublicPrivatePartnerships #FutureOfWork #AIforOpportunity #PowerOfData

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Understanding the Impacts of Generative AI Use on Children | WP1 Surveys | prepared by: The Alan Turing Institute The mission of this report is to critically examine the transformative role of generative artificial intelligence on children’s cognitive, social, and educational development, providing evidence-based guidance for policymakers, educators, and caregivers. It seeks to illuminate both the unprecedented opportunities for personalized learning and the emergent risks associated with unregulated exposure, establishing a framework for responsible governance of AI technologies in formative contexts. This investigation is positioned at the intersection of behavioral economics, developmental psychology, and digital ethics, emphasizing strategic foresight in AI integration. The survey findings reveal that children interacting with generative AI exhibit a 14–18% acceleration in problem-solving efficiency and a 12–15% increase in adaptive learning retention relative to traditional learning environments. Notably, structured parental and educational supervision increases cognitive ROI by approximately 16%, while unsupervised exposure correlates with a 9% rise in risk of attention and behavioral disruption. The data further demonstrate that equity in access to AI-enhanced learning tools improves educational resilience by 22% across socio-economic cohorts, signaling critical implications for inclusive policy design. Analysis of these outcomes underscores a nuanced risk-reward calculus. Institutions implementing guided AI usage report ROE improvements of up to 11% in educational outcomes per unit of investment, reflecting both direct learning gains and longer-term socio-emotional benefits. Conversely, unregulated adoption presents measurable downside exposure, including reduced attention spans and early digital dependency, which may depress long-term efficiency by 7–9%. These insights demonstrate that strategic governance, rather than wholesale avoidance, maximizes the net social and financial return of AI interventions for child development. In conclusion, the integration of generative AI in children's learning environments represents a high-stakes frontier of human capital development, where careful calibration of access, supervision, and ethical frameworks can materially enhance cognitive ROI, equity, and systemic resilience. Policymakers and educators are thus tasked with orchestrating AI adoption not merely as a technological upgrade, but as a strategic investment in the next generation, with measurable returns in both individual capability and societal welfare. #GenerativeAI #ChildDevelopment #CognitiveROI #AIethics #EducationalResilience #DigitalGovernance #PolicyInnovation #ResponsibleAI #AIinEducation

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“The American Dream feels increasingly out of reach.” That’s the sobering opening line of Michael Ellison’s recent essay for the Milken Institute, and it hits hard. With nearly 40% of adults unable to cover a $400 emergency expense, and AI poised to disrupt 85 million jobs by 2027, the urgency to rethink our workforce systems is undeniable. Traditional education models, especially in technical fields, often lag behind industry needs, leaving graduates underprepared and underemployed. Meanwhile, companies struggle to find talent equipped with the skills required in an AI-driven economy. So, how do we bridge this gap? At CapSource we believe in transforming education through experiential learning. By integrating real-world projects into academic curricula, we provide students with hands-on experience that aligns with current industry demands. This approach not only enhances employability but also ensures that learning is dynamic and relevant. The Milken Institute emphasizes the need for unprecedented collaboration to rewrite the social contract for the future of work. We’re committed to being part of that solution, fostering partnerships between academia and industry to prepare a workforce ready for the challenges and opportunities of an AI-driven economy. Let’s work together to make the American Dream attainable once again. #FutureOfWork #AIinEducation #ExperientialLearning #CapSource #WorkforceDevelopment #HigherEdInnovation #EconomicMobility https://lnkd.in/gXW9CU5x

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Excited to see how the Advancing Regional Innovation Economies (ARIE) initiative is reshaping access to venture capital and growth finance for entrepreneurs from emerging markets! ARIE—launched by the Nasdaq Entrepreneurial Center in collaboration with Heartland Forward and Penn State University’s Evidence-to-Impact Collaborative, with support from JPMorganChase and Nasdaq—blends applied research, data-driven practices, and cross-sector policy action to boost inclusive growth in regional innovation hubs. Their latest findings show that just 20 metro areas anchor around 60% of ACA-recognized angel groups and lead in U.S. SBA 504 lending, demonstrating how talent inflows and higher education power innovation across both Main Street and tech-driven sectors. Kudos to the coalition working to map opportunity, break barriers, and strengthen entrepreneurial ecosystems nationwide. If you’re an ecosystem builder, policymaker, investor, or educator committed to inclusive innovation, check out the latest research and resources from ARIE. #Innovation #Entrepreneurship #RegionalEconomies #VentureCapital #InclusiveGrowth #ARIE Learn more: https://lnkd.in/gb9d_vuQ ***

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