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Daniel Rock

Assistant Professor, the Wharton School, University of Pennsylvania · Co-Founder and CTO, Workhelix · AI2050 Early Career Fellow, Schmidt Sciences

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Which parts of your workforce will AI actually change, and where will it pay off? Daniel Rock brings the data that separates the buzzwords from the business case.
Philadelphia, United States
Videos

Watch Daniel in Action

2025, Economics of Transformative AI Workshop, "Transformative AI and Firms"

Bio

About Daniel Rock

Daniel Rock, Ph.D., is an economist who studies artificial intelligence. He helps organizations understand AI's impact on business economics, the future of work and competitive strategy. "This set of new technologies present an absolutely massive opportunity," he says, but it is not one that comes for free: capturing the benefits takes work.

Rock's research examines which occupations are most exposed to machine learning, how to measure the value of AI skillsets, and why productivity growth must be reframed to account for intangible investments. His work has been featured in Bloomberg, Harvard Business Review and MIT Sloan Management Review. A former algorithmic trader at DRW Trading, he pairs an engineering mindset with a background in financial markets. "Getting down to the underlying algorithms that are used to train AI is the best way to understand what the economics of the models are going to be," he explains.

Topics

Daniel's Keynote Topics

It’s uncertain how AI will affect society, but one thing is sure – AI will have huge impacts on global economies and business competition. How can organizational leaders get up to speed now to bolster their company’s margins for years to come? According to Daniel Rock, Ph.D., Wharton School professor and Stanford Digital Economy Lab fellow, it’s vital for executives to understand where productivity in AI comes from. In this presentation, Rock leverages his unique engineering mindset and background in financial markets to provide leaders with an accessible primer on the effects of AI on monetary systems, both internally and externally. Explaining “what gets you paid in AI,” Rock presents practical tools for measuring and quantifying the real-world economic impacts of today’s leading technologies. Audiences will be empowered to make better decisions to get and stay ahead of competitors through strategic, financially sound AI investment and deployment.

It’s hard to keep up with all the catchphrases around artificial intelligence and the future of work. Between automation, augmentation, upskilling and reskilling, how can managers and executives break through the buzzwords to create a logical, AI-powered path forward for their organization and its workforce? According to Daniel Rock, Ph.D., Wharton School professor and Workhelix CTO, AI won’t become the wholesale labor market disruptor some predict, but it’s important for leaders to identify thoughtful implementation strategies. In this informative presentation, Rock outlines an empowering AI-enabled future of work by spotlighting types of occupations most exposed to disruption by machine learning, how to measure the value of AI skillsets, and why productivity growth must be reframed. Audiences will learn practical strategies for zeroing in on the best uses for technologies like generative and agentic AI, giving them a framework that supports both tech-enabled organizational efficiency and workforce-friendly jobs models.

Testimonials

The world is full of people…far too many, in fact...who claim they know what they’re talking about regarding generative AI and the implications it may have for organizations and the people working in them. The difference between those people and Dan is that he actually has the authority and credibility to say it. Nobody knows more about the topic than him, and nobody is a more delightful and engaging expert on the topic with which to work. In the first eight months of knowing him we put him in front of our entire firm, and on two occasions, our most senior clients. Every time we looked brilliant for doing so. Highly recommended.

Alan NelsonCRA Inc.
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