Adam Grant
Wharton Organizational Psychologist | #1 New York Times Bestselling Author of Think Again & Hidden Potential | Top TED Speaker | Host of Re:Thinking
Research Director, AI Economics & Policy, Stanford Digital Economy Lab | Co-Author, Canaries in the Coal Mine? | Former Uber Economist | AI & Future of Work Expert
AI is already changing who gets hired, and Bharat Chandar has some of the strongest evidence to prove it. A Stanford labor economist and co-author of the landmark Canaries in the Coal Mine? study, he tracks AI's real effect on jobs using payroll data from millions of workers. His talks give leaders a clear picture of where their workforce is exposed and how to rebuild talent pipelines for an AI economy.
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Bharat Chandar is a labor economist at Stanford whose research has become a central reference point in the debate over how artificial intelligence is changing work. He is Research Scholar and Research Director for AI Economics and Policy at the Stanford Digital Economy Lab, part of the Stanford Institute for Human-Centered Artificial Intelligence (HAI).
Future of work speaker Bharat Chandar is best known for co-authoring, with Erik Brynjolfsson and Ruyu Chen, “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence.” Using high-frequency records from ADP, the largest payroll software provider in the United States, the study produced some of the earliest large-scale evidence that AI is already reshaping hiring. Since generative AI went mainstream, workers aged 22 to 25 in the most exposed occupations, such as software development and customer service, have seen a double-digit relative decline in employment, even after accounting for company-level shocks, while more experienced colleagues in the same roles have held steady or grown. Companies are adjusting through headcount rather than pay, and the declines cluster where AI automates work rather than augments it. The results hold even when technology firms and remote-friendly jobs are excluded. Updated as new data arrives, the findings have been covered by TIME, CBS News, Fortune, and Bloomberg.
His wider agenda asks how workers will adjust if AI changes who gets hired, how AI can help people learn new skills, and how its effects differ across countries. A recent study examines how AI adoption is changing labor demand across 41 countries, and his widely read survey, “AI and Labor Markets: What We Know and Don’t Know,” separates established findings from open questions.
Before his doctoral work, Chandar spent two years as an economist at Uber, studying how tipping, ratings, and behavioral nudges shape service quality, research later published in Management Science with Susan Athey and Juan Camilo Castillo. He holds a PhD in economics from Stanford Graduate School of Business, plus an MS in statistics and a BA in economics from the University of Chicago. He also writes for Project Syndicate and his Substack, What’s Next.
As a speaker, Bharat Chandar replaces speculation with evidence. He has presented at DLD Munich and advised business leaders and policymakers on the economic effects of AI, showing audiences which roles are most exposed, where AI automates tasks versus augments people, and how to redesign hiring, onboarding, and career paths before the entry-level pipeline thins out. Senior teams leave with a clear, data-grounded view of what AI is doing to their own workforce and what to do next.
Miners once carried canaries underground because the birds sensed danger before anyone else could. In this keynote, Bharat Chandar presents the labor market's equivalent: the early-career workers whose job prospects are showing the first measurable effects of generative AI. Drawing on his landmark Stanford research with Erik Brynjolfsson and Ruyu Chen, built on payroll records for millions of Americans from ADP, the country's largest payroll software provider, he walks audiences through the six facts that have reshaped the global debate on AI and work.
Leaders learn why the impact is concentrated among workers aged 22 to 25 in the most exposed occupations, why their more experienced colleagues have so far been spared, why companies are adjusting through hiring rather than pay, and why the declines appear where AI automates tasks rather than augments people. Chandar also shows how the findings hold up against alternative explanations, including company-level shocks, tech-sector dynamics, and remote work, and what the latest data reveals as the trend develops. Audiences leave with a rigorous, evidence-based reading of where AI is changing their own talent pipeline and which signals to watch next.
For generations, companies grew their future leaders the same way: hire at entry level, teach the fundamentals, promote from within. As AI absorbs more of the tasks that once filled junior roles, that model is starting to break. Chandar explains what the evidence shows about the shrinking first rung of the career ladder and introduces the career lattice, a structure in which people build skills across functions and advance through lateral as well as upward moves.
Designed for CHROs, CLOs, and leadership development teams, the session offers practical ways to rethink onboarding, mentorship, and rotational programs so organizations keep developing talent even as entry-level work changes.
AI's impact on work will not look the same in every economy. Based on his research on AI adoption and labor demand across 41 countries, Chandar compares how companies in different markets are using AI, which workers gain or lose ground, and why national context matters. He also lays out what researchers know with confidence and what remains genuinely uncertain, giving global leaders and policymakers a sober framework for planning workforce strategy across regions.
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