Job Market Paper
1. When AI Meets Entrepreneurship: Evidence from the Commercialization of ChatGPT (with Sixun Tang)
Abstract: This paper examines how the commercialization of generative artificial intelligence influences new firm creation, leveraging the release of ChatGPT as an exogenous shock to AI accessibility. We develop a novel industry-level measure of AI compatibility that captures the extent to which AI tools can support early-stage entrepreneurial tasks. Using a difference-in-differences design, we find that industries more compatible with AI experienced an increase of over 10% in firm formation following ChatGPT’s release. To investigate why, we examine three mechanisms: reduced experimentation costs, capital reallocation, and human capital complementation. While we find no evidence supporting the latter two, we show that the increase in firm formation is concentrated in industries where AI can effectively assist and experimentation is critical—evidence consistent with a reduction in the cost of experimentation as the key driver. Moreover, new firms created after ChatGPT’s release in AI-compatible industries are more likely to survive, grow faster, and attract more educated workers. Taken together, the mechanism and quality results suggest that AI lowers the cost of experimentation in a way that disproportionately benefits high-ability entrepreneurs, leading to both greater and higher-quality firm formation.
Awards: Best Doctoral Student Paper in Financial Technology and Data Science in Finance, SWFA 2026.
Presented: SWFA (scheduled); Loyola Quinlan (02/2026); Fordham Gabelli (01/2026); HEC Paris Entrepreneurship Workshop (12/2025); Roundtable for Engineering Entrepreneurship Research Conference (11/2025); Chicago FED seminar (11/2025); Inter-Finance PhD Seminar (10/2025); Chicago Booth Finance Lunch Seminar (09/2025); Revelio Labs Seminar Series (06/2025); 3rd Chicago Entrepreneurship Workshop (05/2025); Chicago Booth Corporate Finance Working Group (04/2025); Chicago Booth Finance Student Brownbag (11/2024); Chicago Booth Corporate Finance Working Group (10/2024).
Abstract: This paper examines how the commercialization of generative artificial intelligence influences new firm creation, leveraging the release of ChatGPT as an exogenous shock to AI accessibility. We develop a novel industry-level measure of AI compatibility that captures the extent to which AI tools can support early-stage entrepreneurial tasks. Using a difference-in-differences design, we find that industries more compatible with AI experienced an increase of over 10% in firm formation following ChatGPT’s release. To investigate why, we examine three mechanisms: reduced experimentation costs, capital reallocation, and human capital complementation. While we find no evidence supporting the latter two, we show that the increase in firm formation is concentrated in industries where AI can effectively assist and experimentation is critical—evidence consistent with a reduction in the cost of experimentation as the key driver. Moreover, new firms created after ChatGPT’s release in AI-compatible industries are more likely to survive, grow faster, and attract more educated workers. Taken together, the mechanism and quality results suggest that AI lowers the cost of experimentation in a way that disproportionately benefits high-ability entrepreneurs, leading to both greater and higher-quality firm formation.
Awards: Best Doctoral Student Paper in Financial Technology and Data Science in Finance, SWFA 2026.
Presented: SWFA (scheduled); Loyola Quinlan (02/2026); Fordham Gabelli (01/2026); HEC Paris Entrepreneurship Workshop (12/2025); Roundtable for Engineering Entrepreneurship Research Conference (11/2025); Chicago FED seminar (11/2025); Inter-Finance PhD Seminar (10/2025); Chicago Booth Finance Lunch Seminar (09/2025); Revelio Labs Seminar Series (06/2025); 3rd Chicago Entrepreneurship Workshop (05/2025); Chicago Booth Corporate Finance Working Group (04/2025); Chicago Booth Finance Student Brownbag (11/2024); Chicago Booth Corporate Finance Working Group (10/2024).
Working Papers
2. The Dark Side of AI: Data Centers, Resource Diversion, and Local Entrepreneurial Outcomes
Abstract: The emergence of Artificial Intelligence (AI) as a viable business solution has led to a massive increase in the demand for computing power. While the direct benefits of the inclusion of AI technologies in day-to-day business operations are rather clear, much has to be learned regarding the spillovers coming from this new type of technology. Leveraging the geographical dispersion of data centers in the state of New York, I study how the local entrepreneurial environment is affected by an increase in the rise of AI's popularity. Preliminary estimates show that the rise of AI usage leads to fewer businesses being started in areas where data centers are located, more businesses getting dissolved and a net negative effect on the total stock of firms. The mechanism relating demand for AI services and sluggish business creation is one entailing resource diversion: when demand for AI services is high, the computational burden placed on data centers is also higher, causing an increase in the demand for electricity. The heightened electricity demand puts upward pressure on prices, discouraging entrepreneurial activity in the affected areas.
Presented: 2nd Chicago Entrepreneurship Workshop (06/2024); Chicago Booth Finance Student Brownbag (04/2024); Chicago Booth Corporate Finance Working Group (04/2024).
3. Local Infrastructure, Search Costs, and Private Capital Deployment
Abstract: The lack of appropriate local infrastructure acts as a friction preventing the flow of private capital within and across countries due to, among other factors, the heightened search costs to source deals. This friction is particularly prevalent in emerging economies, where local infrastructure are still being developed. I use the arrival of high-speed internet connectivity in Africa to proxy for a relaxation of these infrastructural tensions and show that the number of venture capital and private equity (VCPE) transactions, as well as the total value of deals, both increase. I then identify the mechanism through which better local infrastructure promotes private capital deployment: a reduction in search costs. A battery of robustness tests solidifies the idea that the estimators are not capturing demand side effects and that the mechanism at play works through a supply side channel: the reduction of informational barriers.
Presented: Chicago Booth Finance Student Brownbag (02/2024); 15th Annual Private Equity Research Symposium, UNC (11/2023); 2023 Annual FMA New Ideas (11/2023).
Abstract: The emergence of Artificial Intelligence (AI) as a viable business solution has led to a massive increase in the demand for computing power. While the direct benefits of the inclusion of AI technologies in day-to-day business operations are rather clear, much has to be learned regarding the spillovers coming from this new type of technology. Leveraging the geographical dispersion of data centers in the state of New York, I study how the local entrepreneurial environment is affected by an increase in the rise of AI's popularity. Preliminary estimates show that the rise of AI usage leads to fewer businesses being started in areas where data centers are located, more businesses getting dissolved and a net negative effect on the total stock of firms. The mechanism relating demand for AI services and sluggish business creation is one entailing resource diversion: when demand for AI services is high, the computational burden placed on data centers is also higher, causing an increase in the demand for electricity. The heightened electricity demand puts upward pressure on prices, discouraging entrepreneurial activity in the affected areas.
Presented: 2nd Chicago Entrepreneurship Workshop (06/2024); Chicago Booth Finance Student Brownbag (04/2024); Chicago Booth Corporate Finance Working Group (04/2024).
3. Local Infrastructure, Search Costs, and Private Capital Deployment
Abstract: The lack of appropriate local infrastructure acts as a friction preventing the flow of private capital within and across countries due to, among other factors, the heightened search costs to source deals. This friction is particularly prevalent in emerging economies, where local infrastructure are still being developed. I use the arrival of high-speed internet connectivity in Africa to proxy for a relaxation of these infrastructural tensions and show that the number of venture capital and private equity (VCPE) transactions, as well as the total value of deals, both increase. I then identify the mechanism through which better local infrastructure promotes private capital deployment: a reduction in search costs. A battery of robustness tests solidifies the idea that the estimators are not capturing demand side effects and that the mechanism at play works through a supply side channel: the reduction of informational barriers.
Presented: Chicago Booth Finance Student Brownbag (02/2024); 15th Annual Private Equity Research Symposium, UNC (11/2023); 2023 Annual FMA New Ideas (11/2023).
Other Writings
Middle-Market Buyouts (2025) (with Young Soo Jang) [Palgrave Encyclopedia of Private Equity, pp. 737-741, Cham: Springer Nature Switzerland]