This interdisciplinary composition reflects AIEI\u2019s core premise: understanding the AI economy requires examining how AI capabilities move through institutions, reshape work and production, and inform policy. <\/p>\n\n\n\n
Cohort 3 marks a turning point in AIEI\u2019s 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.<\/p>\n\n\n\n Cohort 3 begins with a set of five priority research themes that define the initial question. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n In this way, Cohort 3 is both guided and adaptive:<\/p>\n\n\n\n The cohort is anchored in five interlocking themes: <\/p>\n\n\n\n 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.<\/p>\n\n\n\n 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? <\/p>\n\n\n\n This cohort moves beyond the question of whether<\/em> AI is being adopted to examine how the AI economy is becoming visible inside production systems, labor markets, and global infrastructure.<\/p>\n\n\n\n Cohort 3 represents a deliberate shift in emphasis: <\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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.<\/p>\n\n\n\n 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. <\/p>\n\n\n\n Even as models improve rapidly, adoption is constrained by economic and operational realities. The pace of diffusion reflects feasibility as much as progress. <\/p>\n\n\n\n Contributing Senior Fellows include:<\/strong>\u00a0<\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n Contributing Senior Fellows include:\u00a0<\/strong><\/p>\n\n\n\n A central question is whether individual productivity gains from AI scale into measurable firm-level outcomes. <\/p>\n\n\n\n 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.<\/p>\n\n\n\n Contributing Senior Fellows include:\u00a0<\/strong><\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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.<\/p>\n\n\n\n Contributing\u00a0Senior Fellows include:\u00a0<\/strong><\/p>\n\n\n\n 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: <\/p>\n\n\n\n By integrating the initial research themes with insights emerging from the Fellows\u2019 work, Cohort 3 provides a clearer, evolving picture of how AI is reshaping the economy. <\/p>\n\n\n\n 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\u2019s mission to build a rigorous, global understanding of the AI economy.<\/p>\n\n\n\n The 2026 cohort of the AI Economy Institute (AIEI) brings together researchers from across North America, Europe, the Middle East, Africa, and Asia, spanning: This interdisciplinary composition reflects AIEI\u2019s 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 […]<\/p>\n","protected":false},"author":39727,"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-content-parent":1151895,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13556,13548],"msr-locale":[268875],"msr-post-option":[],"class_list":["post-1177124","msr-blog-post","type-msr-blog-post","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-economics","msr-locale-en_us"],"msr_assoc_parent":{"id":1151895,"type":"group"},"_links":{"self":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/1177124","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post"}],"about":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-blog-post"}],"author":[{"embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/users\/39727"}],"version-history":[{"count":4,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/1177124\/revisions"}],"predecessor-version":[{"id":1177172,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/1177124\/revisions\/1177172"}],"wp:attachment":[{"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1177124"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1177124"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1177124"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=1177124"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"background](\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/wp-content\/uploads\/2026\/06\/header-1024x576.jpg\")
<\/figure>\n\n\n\nFrom Questions to Framework: How Cohort 3 Is Structured <\/h3>\n\n\n\n
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Priority Research Themes<\/h3>\n\n\n\n
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Beyond Adoption: Studying the AI Economy at the Frontier <\/h3>\n\n\n\n
A Shift in Focus: From Diffusion to the Frontier <\/h4>\n\n\n\n
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From Themes to Synthesis: Four Emerging Areas of Inquiry <\/h3>\n\n\n\n
1. The Adoption Frontier: What Governs the Speed of AI Uptake<\/h4>\n\n\n\n
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2. Uneven Diffusion: Why AI Does Not Spread Equally <\/h4>\n\n\n\n
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3. Inside the Frontier Firm: How Organizations Actually Change <\/h4>\n\n\n\n
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4. Agentic Labor Markets: When AI Becomes an Actor <\/h4>\n\n\n\n
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Interpreting the Frontier: Implications for Policy and Strategy<\/h3>\n\n\n\n
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Looking Ahead <\/h3>\n\n\n\n