Artificial intelligence adoption and the demand for managerial expertise, Strategic Management Journal
with Jose Azar (IESE), Mireia Gine (IESE), and Sampsa Samila (IESE)
Abstract: This paper examines how firms' adoption of artificial intelligence (AI) relates to the demand for managers and managerial skills. Using a skills-based measure of AI adoption derived from Lightcast job postings, we show that firms with greater AI adoption post more managerial vacancies and a higher share of such vacancies than less intensive adopters. These relationships are strongest in manufacturing and among firms with higher research and development intensity. Greater AI adoption is also associated with shifts in managerial skill requirements toward interpersonal and growth-oriented skills, including stakeholder management, creativity, and sales management, and away from routine administrative skills such as budgeting, planning, staff management, and customer service. Overall, the results suggest a reconfiguration of managerial roles toward capabilities facilitating scaling, coordination, and adaptation in AI-enabled environments.
The Demand for AI Skills in the Labor Market, Labour Economics
with Jose Azar (IESE), Mireia Gine (IESE), Sampsa Samila (IESE), and Bledi Taska (Burning Glass)
Abstract: Using detailed data on skill requirements in online vacancies, we estimate the demand for AI specialists across occupations, sectors, and firms. We document a dramatic increase in the demand for AI skills over 2010-2019 in the U.S. economy across most industries and occupations. The demand is highest in IT occupations, followed by architecture and engineering, scientific, and management occupations. Firms with larger market capitalization, higher cash holdings, and higher investments in R&D have a higher demand for AI skills. We also document a wage premium of 11% for job postings that require AI skills within the same firm and 5% within the same job title. Managerial occupations have the highest wage premium for AI skills. Firms demanding AI skills more intensively also offer higher salaries in non-AI jobs.
AI Adoption and Firm Performance: Management versus IT (Permanent Working Paper)
with Mireia Gine (IESE), Sampsa Samila (IESE), and Bledi Taska (Burning Glass)
Abstract: We examine the impact of AI adoption on firm growth, productivity, and investment decisions and explore whether the impact on firm size and policies stems from AI adoption among management ranks or IT specialists. We measure the firm-level AI adoption using the demand for AI-related skills in online job postings. First, we document a positive association between the firm-level AI adoption and the firm's size, Capex, R&D, and total investments. We do not find robust relationships with productivity measures. Second, we find that the adoption of AI skills among managers drives the positive association with growth in sales and market capitalization, as well as with R&D and Capex. AI adoption among IT specialists does not show any robust association with firm outcomes.
From In-person to Online: The New Shape of the VC Industry (R&R)
with Silvia Dalla Fontana (ESCP Business School), Caroline Genc (Michigan State University, Eli Broad College of Business), Hedieh Rashidi Ranjbar (University of Melbourne, Melbourne Business School)
Abstract: This paper asks whether geographical clustering and in-person interactions are still essential features of the venture capital (VC) industry in the age of online communications. Through event study and difference-in-differences analyses, we show that VCs break their traditional norm and invest in more distant startups, following an interruption of in-person interactions. This evolution goes along with changes in selection criteria and VCs' syndication process. Overall, our study reveals that online interactions cannot perfectly substitute for in-person meetings and helps us understand how VCs revisit their investment model and balance out the risks of remote investing.
Presentations: Imperial College London Seminar*, WEFI Fellows Meeting, IESE Business School Seminar, SFI-USI Summer School*, WEFI PhD Seminar*, Seminar at Paris Dauphine University*, Finance PhD Workshop at HEC Paris*, Remote Work Conference (Stanford University), AFA Poster Session* (January 2023), PE Conference, PhD Workshop* (Columbia University, March 2023), 5th Future of Financial Information Conference at HEC, Paris (poster session, May 2023), Private Capital Symposium at LBS* (May 2023)
The Look of Success: Face-Based Trait Impressions and Venture Financing
with Silvia Dalla Fontana (ESCP Business School), Caroline Genc (Michigan State University, Eli Broad College of Business), and Lin Peng (Zicklin School of Business, Baruch College, City University of New York)
Abstract: This study provides the first large-scale analysis of face-based impression factors in venture capital. Using machine learning to extract Trustworthiness, Dominance, and Attractiveness factors from founder photos across 63,251 U.S. startups, we find that these factors significantly predict initial VC funding decisions, with magnitudes comparable to founder education and prior experience. Their relative importance varies by founder gender, team composition, industry, and VC experience. The factors persist as predictors of longer-term outcomes, including follow-on financing and successful exits, suggesting that facial cues function as informative signals of venture success, even among experienced investors.
Presentations: PERC Oxford Symposium 2026, Workshop on Entrepreneurial Finance and Innovation Fellows (WEFI) Conference at Columbia University, Fall 2025 Labor and Finance Group Conference (Berlin), HEC Paris Entrepreneurship Workshop, DePaul Behavioral Finance and Accounting Conference, and seminars at ESCP Business School, the University of Lugano, Baruch College, KU Leuven, Michigan State University, and Yeshiva University; SMS Annual Conference (scheduled for October 2026), FMA Annual Meeting (scheduled for October 2026)
Abstract: This paper examines the extent to which the matching between startups and venture capitalists' investment styles accounts for financing disparities between female- and male-founded companies. Analyzing initial venture capital (VC) rounds for comparable founders and startups, the study documents that the gender financing gap can be attributed to the sorting of female-founded ventures into VCs with smaller investment cheques, as large-cheque investors are less likely to fund "typical female-founded" startups. The findings suggest that the lower predicted growth prospects of such businesses may contribute to their mismatch with large-cheque VC investors.
Presentations: SEI Consortium (ESSEC, Paris), Bordeaux School of Economics Seminar, WEFI Fellows Meetings, KTO PhD Workshop (SKEMA), IESE Business School Seminar, KU Leuven Seminar, Tilburg University Seminar
Common Ownership in Fintech Markets
with Jose Azar (IESE) and Anna Tzanaki (Lund University)
Abstract: We investigate the extent and impact of common ownership in fintech companies. We document a range of empirical facts about common ownership patterns in fintech markets around the world and discuss their implications for competition law enforcement. Specifically, fintech firms are often not publicly listed companies, and the largest owners in this type of firms are venture capital and other types of private equity investors, as opposed to large asset management firms, which are often the largest owners in publicly listed companies. We show that the extent of common ownership is generally low among privately held fintech start-ups. However, it grows substantially with the fintech firms going public. More dynamic and larger fintech markets are characterized by lower levels of common ownership, while smaller national and product markets show substantially higher ownership overlaps. Accordingly, the estimated effects of common ownership in private fintech firms, measured by the lambdas, are higher in the smaller markets. Yet, these are still relatively very low compared to empirically observed common ownership in public fintech firms in oligopolistic markets. Finally, we comment on how the specific ownership and governance structures of fintech firms may materially influence the magnitude and systemic nature of effects associated with common ownership.