Overview
Data-backed research on how AI adoption reshapes firms, labor, and economies
Beyond Adoption: Firms, Work, and Diffusion at the Frontier of the AI Economy gathers researchers from the third cohort of Microsoft's AI Economy Institute Senior Fellows Program to examine what happens inside firms, industries, and labor markets once AI moves from experiment to production. Edited by Microsoft's Chief Data Scientist Juan M. Lavista Ferres and Chief AI Economist Frank Nagle, this collection replaces speculation with early, data-backed evidence from organizations deploying AI at scale.
Each chapter investigates a specific dimension of AI's economic impact: compute contracts that lock out younger firms, missing digital infrastructure in developing regions, workforce skill gaps, and the uneven diffusion of productivity gains across small and large organizations. Contributors draw on methods spanning multiple geographies and sectors, analyzing how frontier firms have rebuilt operating models around intelligence on demand and what that restructuring means for hiring, productivity, and regional economies.
Readers will also find:
- Analysis of how general-purpose technology adoption patterns from past computing waves predict current AI diffusion trajectories across industries
- Research on the specific drivers and barriers to generative AI adoption across both formal and informal economies worldwide
- Evidence on how AI-first organizations restructure workflows, hiring practices, and productivity measurement when deploying at scale
- Examination of the widening distance between AI's raw capability and the organizational capacity firms need to depend on it
- Actionable insights for policymakers and institutional leaders seeking to close regional and sectoral AI adoption disparities effectively
Written for policymakers, educators, institutional leaders, and students who need rigorous evidence rather than hype, this volume delivers research on how AI adoption is transforming firm structure, labor markets, and economic geography. It equips readers with the data and frameworks to make informed decisions about AI's role in their organizations and regions.
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