Daniel Rock

Daniel Rock is one of the world’s leading voices on the economics of artificial intelligence. As an Assistant Professor at the Wharton School of the University of Pennsylvania, he studies how digital technologies transform business performance, labour markets and competition. Known for making complex ideas accessible, Daniel helps organisations cut through the noise and understand what AI really means for their future.

After graduating summa cum laude from the University of Pennsylvania, Daniel went on to earn his master’s and Ph.D. at MIT’s Sloan School of Management, where he specialised in the economics of information technology and intangible assets. Before returning to academia, he worked as an algorithmic trader at DRW Trading, giving him first-hand experience of how data and automation reshape markets. Today, in addition to his role at Wharton, Daniel is Co-Founder and CTO of Workhelix, a workforce AI start-up he launched with Erik Brynjolfsson and Andrew McAfee, guiding companies through the challenges and opportunities of AI adoption. He also holds positions as a Fellow at the Stanford Digital Economy Lab and Digital Fellow at the MIT Initiative on the Digital Economy, cementing his place at the heart of the global AI research community.

Daniel’s academic work has been widely cited for its impact on how we measure and understand AI-driven change. His co-authored study on the ‘Productivity J-Curve’ has become a landmark, showing why new general-purpose technologies such as AI take time to deliver visible returns in national statistics. He has also produced pioneering research on the labour market impacts of machine learning, the economic value of AI skillsets, and the intangible assets that underpin successful digital transformation. His insights have been published in leading journals and featured in The New York Times, Bloomberg, the Wall Street Journal, Harvard Business Review, and Sloan Management Review. Recognised for his contributions, Daniel is an AI2050 Early Career Fellow at Schmidt Sciences and recipient of research grants from Google and the MIT-IBM Watson AI Lab.

On stage, Daniel translates deep research into clear and actionable insights. He equips leaders with practical frameworks for identifying “what gets you paid in AI,” how to measure productivity gains, and where to focus investment for long-term advantage. His presentations on finance, competition and the future of work resonate across industries, offering both clarity and vision. Audiences consistently value his authority, evidence-based approach, and ability to bring optimism and rigour to one of the most important economic shifts of our time.