The 2026 cohort of the AI Economy Institute (AIEI) brings together researchers from across North America, Europe, the Middle East, Africa, and Asia, spanning: 

• Economics and economic geography
• Organizational behavior and labor economics 
• Computer science and AI systems 
• Public policy and governance

This interdisciplinary composition reflects AIEI’s core premise: understanding the AI economy requires examining how AI capabilities move through institutions, reshape work and production, and inform policy. 

Cohort 3 marks a turning point in AIEI’s research trajectory. Cohort 1 examined how higher education can prepare people for an AI-enabled economy. Cohort 2 expanded the lens to education systems and institutional pathways for diffusion. Cohort 3 moves our point of inquiry to the frontier, asking how AI is reshaping firms, labor markets, and economic structure in real time.

From Questions to Framework: How Cohort 3 Is Structured 

Cohort 3 begins with a set of five priority research themes that define the initial question. 

From there, Fellows submit proposals that interpret and engage with these questions. While Fellows initially align to one or more themes, AIEI then reorganizes the research portfolio based on the insights that emerge. 

In this way, Cohort 3 is both guided and adaptive:

• The five themes establish the research agenda 
• The Fellows’ work reshapes that agenda into a more empirically grounded synthesis 

Priority Research Themes

The cohort is anchored in five interlocking themes: 

• Productivity at the Frontier and Firm-Level Transformation. How AI is reshaping production and organizational design 
• Occupational Change, Leadership Expectations, and Workforce Transformation. Evolving skills, roles, and leadership in an AI-enabled workforce
• Economic Geography and Diffusion. Regional and market-level spillovers
• When History Rhymes. GPT analogues and structural shifts 
• Forecasting the Frontier. Capabilities, diffusion, and labor market signals

Together, these themes explore the idea that AI’s economic impact will be determined not simply by technological advances, but by the deployment of capabilities within firms, across labor markets, and throughout global economic systems.

Beyond Adoption: Studying the AI Economy at the Frontier 

The central question for Cohort 3 is: if AI capability is advancing rapidly, what determines who adopts, how quickly, and with what consequences for firms, workers, and economic structure? 

This cohort moves beyond the question of whether AI is being adopted to examine how the AI economy is becoming visible inside production systems, labor markets, and global infrastructure.

A Shift in Focus: From Diffusion to the Frontier 

Cohort 3 represents a deliberate shift in emphasis: 

• From education systems → firms as the primary site of transformation 

• From access to AI → constraints on scaling and deployment 

• From potential impacts → observable organizational and labor market effects 

The operating premise is that AI diffusion is no longer hypothetical. It is fast, uneven, and empirically observable, particularly within frontier firms and early-adopting economies. 

From Themes to Synthesis: Four Emerging Areas of Inquiry 

As Fellows engaged with the five themes, their proposals surfaced common questions and shared lines of inquiry, reshaping the research into four empirically grounded streams of work.

1. The Adoption Frontier: What Governs the Speed of AI Uptake

AI adoption is not determined by capability alone. It depends on the conditions that make deployment feasible: infrastructure, compute, energy, and the structure of inference markets. 

Even as models improve rapidly, adoption is constrained by economic and operational realities. The pace of diffusion reflects feasibility as much as progress. 

Contributing Senior Fellows include: 

• Edoardo Maria Acabbi (University of Mannheim, Germany) and Luca Mazzone (University of Montreal, Canada) on supply constraints and the “feasibility frontier” 

• Caspar David Peter (Erasmus University, Netherlands) on historical analogues to technological disruption 

• Ilan Strauss (The AI Disclosure Project) on AI diffusion constraints, including affordability, demand, wage share, financing capacity, and capital intensity 

• Daniel Yue (Georgia Institute of Technology) and Frank Nagle (MIT) on competition and lock-in in inference markets 

2. Uneven Diffusion: Why AI Does Not Spread Equally 

AI does not diffuse evenly across firms, regions, or economies. Differences in capital, talent, institutions, and policy environments produce persistent gaps between frontier and lagging adopters. 

Diffusion is also shaped by less visible factors such as informal economies, cross-border networks, and firm-level relationships, which influence where and how AI takes hold. 

Contributing Senior Fellows include: 

• Pierre-Alexandre Balland and Laura Nurski (CEPS, Belgium)) on a “multi-AI economy” across cities 

• Nuriye Melisa Bilgin (Koc University, Turkey) and Gianmarco Ottaviano (Bocconi University), on governance and legal uncertainty as adoption barriers in emerging economies 

• Wesley Rosslyn-Smith (University of Pretoria, New Zealand) on informal economies 

• Johannes Wachs (Cornivus University, Hungary) on network connectivity 

• Nataliya Wright (Columbia University) on firm-level scaling and global diffusion 

3. Inside the Frontier Firm: How Organizations Actually Change 

A central question is whether individual productivity gains from AI scale into measurable firm-level outcomes. 

This work examines how AI reshapes teams and workflows, role design and task allocation, and the balance between human and machine capabilities. It also investigates whether AI introduces new coordination challenges alongside productivity gains.

Contributing Senior Fellows include: 

• Salman Khan and Mustafa Afcan (MBZUAI, UAE) on occupational restructuring (in collaboration with the World Bank) 

• Friederike Mengel (University of Essex, United Kingdom) and Christoph Siemroth (University of Exeter, United Kingdom) on team productivity and collaboration 

• Yingfei Wang (University of Washington) on learning-aware delegation 

4. Agentic Labor Markets: When AI Becomes an Actor 

AI systems are increasingly moving from tools to participants in economic activity. As they begin to hire, manage, and evaluate workers, they reshape core labor market functions. 

This raises new questions about firm decision-making, labor market dynamics, and governance and accountability. It also introduces risks related to transparency, bias, and worker agency.

Contributing Senior Fellows include: 

• Serena Booth (Brown University) on worker voice and governance 

• Meeyoung Cha (KAIST, South Korea and Max Plank Institute) on AI agents as employers 

• Brian Jabarian (Carnegie Mellon University), Luca Henkel (Erasmus University, Netherlands), and Pellumb Reshidi (Florida State University) on agentic hiring systems 

Interpreting the Frontier: Implications for Policy and Strategy

Taken together, the research suggests that the AI economy will not follow a single trajectory. Instead, it will be defined by a set of persistent tensions: 

• The gap between capability and deployability 

• Productivity gains alongside organizational fragility 

• Competition between open access and market concentration 

• Trade-offs between automation and human skill development 

• Uneven diffusion across firms and regions 

Looking Ahead 

By integrating the initial research themes with insights emerging from the Fellows’ work, Cohort 3 provides a clearer, evolving picture of how AI is reshaping the economy. 

The resulting body of research will inform policymakers, firms, and institutions seeking to make decisions in a rapidly changing technological and economic landscape, advancing AIEI’s mission to build a rigorous, global understanding of the AI economy.

The post Announcing the AI Economy Institute’s Third Cohort of Senior Fellows  appeared first on Microsoft Research.

Cohort Two 

The 2025 cohort brings together exceptional global expertise and diversity, with researchers from eight countries and leading institutions worldwide. Their work spans disciplines from economics and policy to engineering, education, and artificial intelligence, reflecting a truly multidisciplinary approach.

• Bashar Alhafni, Mohamed bin Zayed University of AI (MBZUAI), UAE
• Carolina Calvo, National Center for AI (CENIA), Chile
• Bharat Chandar, Stanford University
• Manuel Hoffmann, University of California, Irvine and Frank Nagle, MIT IDE
• Stephen Michael Impink, HEC Paris, France
• Jason Jabbari, Washington University, St. Louis
• Tingting Li, Washington State University
• Carolina Lopez, World Bank
• Laura Nurski, Centre for European Policy Studies (CEPS), Belgium
• Joseph Onderi Orero, Strathmore University, Kenya
• Sarah Rodriguez, Virginia Tech Foundation
• Robert Seamans, Stern School of Business, New York University and Arun Sundararajan, New York University
• Andrew Stokols, MIT/Singapore Management University, Singapore
• Inbal Talgam-Cohen, Tel Aviv University, Israel
• Skye Zhao, University of Manchester, England
• Sarayu Sundar, University of Colorado Boulder
• Wendy DuBow, University of Colorado Boulder

Opportunity, Education, and Work

This cohort explores how AI adoption varies across regions and sectors, what barriers and accelerators exist, and how education and workforce systems must evolve to keep pace with technological change. Researchers will investigate: 

• National Diffusion Differences: Comparative studies of AI strategies and adoption in East and Southeast Asia, Latin America, Europe, and Africa.
• AI and Education: The impact of AI on K-12 teaching, teacher training, and game-based learning, with a focus on equity and innovation.
• AI and Entry-Level Jobs: Labor market impacts, mentorship, and the emergence of new apprenticeship models in the digital economy.
• Community, Technical, and Vocational Colleges: Pathways for high-impact AI transitions, workforce development, and regional innovation.

Spotlight: People and Projects

Apprenticeships

Dr. Impink’s research at HEC Paris explores how digital tools are paving the way for white-collar apprenticeship programs. The project assesses whether successful European models can be adapted for the U.S. and other developed markets, highlighting the risks of relying solely on private investment in education and guiding future workforce policy.

The Two-Year Educational Platform

Sarah Rodriguez’s work focuses on community, technical, and vocational colleges as engines of equitable AI adoption. Her research informs strategies for workforce development and educational reform, ensuring that AI-driven change benefits learners from all backgrounds.

UAE and Singapore: National Diffusion Leaders

Projects from the United Arab Emirates and Singapore analyze why these countries lead in AI adoption—over 56% of their working-age populations actively use AI tools. Decades of strategic investment in digital infrastructure, education, and policy have accelerated responsible diffusion, offering actionable insights for nations seeking to close the AI adoption gap.

Continuity and Progress: Building on AIEI’s Inaugural Cohort

Cohort two’s work reflects AIEI’s commitment to continuity and progress. Last year, our researchers illuminated how AI diffusion is shaped by human agency, creativity, and the urgent need for educational transformation. This year, we look earlier in the educational pathway and deepen our inquiry—tracking how diffusion unfolds globally, and how local choices and partnerships drive real change.

Shaping the Economic Future by Design

AI’s diffusion will shape whether its benefits are broad and transformative or concentrated among a few. Inclusive and ethical design—through policies, infrastructure, and governance—ensures that AI advances human values while driving productivity and innovation. As this cohort begins its work, we look forward to the insights that will inform policy, guide educational reform, and inspire innovation across sectors and geographies, helping shape our economic future.

The post Education in the AI Economy: the AI Economy Institute’s 2025 Fall Cohort appeared first on Microsoft Research.

The rhythm of business is the rhythm of knowledge 

Twice a year, AIEI issues themed Calls for Proposals (CFPs), inviting scholars and practitioners worldwide to explore the economic and social transformations driven by artificial intelligence. These CFPs are more than academic invitations—they are the heartbeat of a global community committed to building an inclusive, trustworthy AI economy. 

From these proposals emerge cohorts of senior fellows who engage in collaborative research, peer-reviewed scholarship, and practical writing. Each cohort contributes to a growing body of knowledge through journal articles and trade books designed for real-world audiences. This work comes alive through virtual and in-person workshops where Microsoft subject matter experts and external thought leaders refine insights and translate them into actionable strategies—ensuring research informs policy, investment, and practice rather than remaining theoretical. 

From insight to impact 

Each cohort embarks on a six-month journey culminating in peer-reviewed articles and a trade book, with every fellow contributing a chapter for practical audiences. These publications are not endpoints—they are catalysts. Workshops convene fellows with experts to challenge, refine, and transform insights into strategies that shape decisions across sectors. 

AIEI’s cadence fosters both depth and diffusion. From proposal review to manuscript submission, every phase builds knowledge that is rigorous, relevant, and ready to inform real-world decisions. External reviewers and advisory fellows ensure scholarly excellence and global representation, while Microsoft SMEs provide thought partnership to bridge research and implementation. 

Building a community of inquiry 

This rhythm creates more than outputs—it builds a community. AIEI is cultivating a living network of inquiry, where each cohort adds to a growing archive of evidence and insight. Through this model, we are not just studying the AI economy—we are shaping it. Fellows tackle urgent topics such as AI’s impact on education, workforce development, and human agency, offering solutions that help institutions and communities adapt and thrive. 

Dual Pathways to Knowledge 

Research awards and trade book contributions serve distinct yet complementary purposes within AIEI’s rhythm. Research awards fund deep, rigorous inquiry—giving scholars the time and resources to explore complex questions and produce peer-reviewed scholarship that advances the field. Trade books, by contrast, offer a real-time platform for dialogue and synthesis. Each fellow contributes a chapter, not as an isolated academic exercise, but as part of a collective voice reflecting shared learning. These books are designed for accessibility and impact, ensuring insights move beyond the academy to inform practitioners, policymakers, and the public. Together, these outputs embody AIEI’s dual mission: to generate knowledge and share it widely. 

Workshops: the connective tissue 

Workshops transform individual scholars into a true cohort—a community that learns, debates, and innovates together. These sessions are active laboratories where fellows test ideas against one another and with Microsoft subject matter experts. This dynamic exchange sharpens arguments, surfaces new perspectives, and ensures research is grounded in both academic rigor and practical relevance. By fostering collaboration and intellectual challenge, workshops make the think tank more than a collection of projects—they make it a living network of ideas. 

An economic future by design 

Ultimately, AIEI is about designing the future with intention. No single entity has all the answers to the questions AI poses. But by convening diverse voices, supporting actionable research, and sharing what we learn, we are building a think tank that is both reflective and responsive—a place where scholarship meets strategy and the future of work, education, and opportunity is imagined and built. 

Our goal is ambitious yet clear: to create an economic future by design. Through scholarship, engagement, and knowledge sharing, AIEI offers critical analysis and thought leadership at a moment when societies worldwide are grappling with profound change. We believe the future belongs to those who use AI thoughtfully—deepening human creativity and solving complex problems. By investing in research and convening global expertise, AIEI is charting a path toward purposeful transformation. 

The post Informing the design of tomorrow’s economy appeared first on Microsoft Research.

To quote Microsoft Vice-Chairman and President Brad Smith, “the most important work ahead isn’t just about building smarter machines—it’s about helping people thrive alongside them”, encapsulating the Institute’s mission to put humans at the center of AI-driven economic transformation.

The pilot cohort 

AIEI’s inaugural cohort launched in early 2025 with an initial point of inquiry focused on how AI can transform and enhance higher education – curriculum development, institutions, and specially computer science. 14 proposals were selected to investigate how generative AI can be effectively integrated into colleges and universities to drive innovation in teaching, learning, and workforce preparation.

These inaugural research projects span critical questions – for example, evaluating the real-world labor market value of AI skills and micro-credentials, and exploring how generative AI can spur academic innovation across disciplines. The goal of this first cohort is to produce actionable insights for educators, policymakers, and industry, guiding how we adapt to AI in education and ensuring those insights feed back into Microsoft’s own initiatives (like the Elevate skilling programs) to prepare people for the AI economy. So, while these scholars are producing peer-reviewed research, they are also providing real-time expertise at the speed of the AI Economy.

The AI Economy Institute and its inaugural cohort reflect Microsoft’s commitment to proactively shape an inclusive, opportunity-rich AI economy – one where AI’s benefits are broadly shared and humanity “thrives” alongside advancing technology. 

How AI can transform and enhance higher education? —curriculum development, institutional models, and workforce preparation.

AIEI’s inaugural cohort is leading on integrating generative AI into colleges and universities to drive innovation in teaching, learning, and credentialing. This translates to: 

Actionable Research for Education 

• Providing evidence-based insights on integrating generative AI into higher education that helps universities adapt curricula to meet AI-driven workforce needs, creates a network of thought leaders shaping AI’s role in education and economic opportunity. 

Understanding Direct Impact on Skills & Employability 

• Evaluating current labor market value of AI skills and micro-credentials, guiding educators and employers to support inclusive pathways for students and workers to thrive in the AI economy. 

Humanist AI 

• AI is at its most useful when it is an augmentation for human creativity and innovation. This cohort’s research draws attention to the necessity of deep learning and thinking as core to the educational experience. 

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