Jeffrey Peo
Doctoral Candidate in Management
Saïd Business School, University of Oxford
My research examines how firms build and renew capabilities as technological change introduces new forms of expertise. In my thesis, I study how organizations integrate data science and artificial intelligence by reshaping collaboration, careers, and authority.
Research Summary
My research examines how firms build and renew capabilities as technological change alters both the expertise they need and the organizational systems through which that expertise is deployed. My current work examines three interrelated processes: sustaining collaboration across knowledge domains, embedding professionals whose skills are highly portable, and reallocating authority as new forms of expertise gain market value.
JOB MARKET PAPER
Getting Familiar: Epistemic Hybrids and the Reproduction of Collaboration
How can organizations sustain collaboration across knowledge divides? Using 1,331 AI-enabled consulting engagements, I find that teams including epistemic hybrids are more likely to collaborate again and accumulate familiarity through repeated interaction, which is associated with stronger project performance.
Making Portable Expertise Stick: Retention and Advancement among Data Scientists in Professional Service Firms
How can firms retain strategically valuable employees whose expertise is highly portable? Using work histories of 243 junior data scientists, I find that greater exposure to the firm’s core non-AI work is associated with lower exit risk without a corresponding penalty to advancement.
Shifting Boundaries: External Valuation and the Reshaping of Internal Jurisdiction
How does new expertise gain authority over work historically controlled by established professionals? I find that clients are more likely to reengage partners with data science backgrounds, including for non-AI work, creating an asymmetric expansion of their access to traditional consulting engagements.