Date: 11 February 2026, Wednesday
\nTime: 10.30 \u2013 11.30
\nPlace: MA-330<\/p>\n
\u201d AI Regulation, Startup Financing, and Talent Allocation\u201d<\/p>\n
by
\nJunida Mulla
\nSaid Business School- Oxford<\/p>\n
Abstract
\nGovernments are rapidly adopting artificial intelligence (AI) regulations to balance societal risks against potential productivity gains. Using a difference-in-differences design that exploits the staggered introduction of AI-related bills across 28 U.S. states, I find that proposed regulation reduces the annual probability that an AI startup secures funding and increases the likelihood of acquisition. The effects are concentrated in rules that restrict which AI systems can be built or deployed (\u201cconstraining\u201d rules). By contrast, documentation, auditing, and disclosure requirements (\u201cprocedural\u201d rules) dampen these effects, consistent with standardized disclosure reducing information frictions around opaque AI technologies. Hiring patterns show that constraining rules increase demand for AI governance roles and shift technical effort from frontier AI research toward deployment of existing systems, while procedural rules have the opposite effect. Startups also reallocate AI-related jobs to non-regulated states.<\/p>\n
Bio
\nJunida Mulla is a DPhil candidate in Finance at the University of Oxford\u2019s Sa\u00efd Business School. Her research lies at the intersection of corporate finance, entrepreneurial finance, and artificial intelligence, with a particular focus on AI regulation, startup financing, and talent allocation. Her job market paper has received the Oxford Sa\u00efd Foundation Research Award for Best Doctoral Student Paper in Finance. Junida holds an MPhil in Economics from Oxford and a BSc (Hons) in Economics from the University of Warwick.<\/p>\n","protected":false},"excerpt":{"rendered":"
Date: 11 February 2026, Wednesday Time: 10.30 \u2013 11.30 Place: MA-330 \u201d AI Regulation, Startup Financing, and Talent Allocation\u201d by Junida Mulla Said Business School- Oxford Abstract Governments are rapidly adopting artificial intelligence (AI) regulations to balance societal risks against potential productivity gains. Using a difference-in-differences design that exploits the [\u2026] <\/p>\n