Good morning. Wharton professor Eric Bradlow, who serves as the vice dean of AI and analytics, calls AI the most consequential innovation of his lifetime. A computer scientist and statistician, he’s drawn to AI for its ability to sift massive data sets, solve complex problems in seconds, and democratize knowledge—especially in business.
In a video series by Wharton faculty on American business innovations, Bradlow discusses his viewpoint on AI and business: “We as humans are going to benefit a lot from artificial intelligence well before businesses make the type of transformations that everyone is predicting,” he said.
So I asked him what he thinks is the biggest bottleneck preventing companies from realizing AI’s potential—is it the technology itself, organizational change, incentives, regulation, or something else?
“I think it is organizational change, and still the need for humans in the loop,” he told me. “Organizations still don’t know how to incorporate AI in a holistic way.” The real constraint, he argues, isn’t the technology itself, but whether leaders can redesign work so humans and AI operate as partners.
Bradlow has been at Wharton for 30 years, has led a data science program for 20 years, and has focused on AI for the past decade. He is part of the research team that worked on the Wharton-Accenture Skills Index, an empirical benchmark that tracks more than 150 million unique U.S. profiles and 100 million job postings.
The rise of large language models is making deep expertise more—not less—valuable, according to Bradlow. Why? “Who’s going to train it? A person with deep skills,” he told Fortune. “Who’s going to assess whether it’s correct? Someone with deep skills.”
In Wharton’s video series, Bradlow also argues that in the age of AI, companies should redeploy employees to higher-value work: “The smart companies won’t get rid of people. The smart companies will redistribute talent.”
However, some companies have taken the position that true AI integration isn’t just automating tasks—it requires redesigning how work gets done, which may mean fewer people overall rather than simply different roles. I asked Bradlow about that viewpoint.
“The biggest opportunities with AI are not cost reductions, but revenue enhancement,” he said. “Firms will expand into entirely new business models, which will require the redistribution of talent among both existing and new employees.”
That also suggests a need for AI training and reskilling. As employees move into new roles, they’ll need new skills to succeed. In speaking with CFOs, I know training and reskilling in the age of AI is top of mind.
For leaders, the challenge is to invest in skills, governance and accountability as aggressively as they invest in models and infrastructure—otherwise, AI’s promise will remain stuck at the pilot stage instead of reshaping how the business grows.
Sheryl Estrada
sheryl.estrada@fortune.com
Leaderboard
Michael Keogh was appointed CFO of Ultra Clean Holdings, Inc. (Nasdaq: UCTT), effective Aug. 5. Keogh succeeds Sheri Savage. He brings more than 25 years of global financial and operational leadership experience. Most recently, Keogh served as CFO of Ford Model e and Integrated Services, where he was instrumental in shaping Ford's EV strategy. He previously served as CFO of Bright Machines. Earlier in his career, he held senior finance leadership positions at Apple, Stanley Black & Decker, and Intel.
Jay Green was appointed CFO of Trucordia, a U.S. insurance brokerage. Green joins Trucordia from Accelerant Holdings, a specialty insurance risk exchange, where he served as Group CFO. Previously, he was with Goldman Sachs, where he was a managing director and head of insurance structured finance within the investment banking division. Throughout his career, he has held senior finance and operational leadership positions in the insurance sector.
Big Deal
KPMG’s Global AI Pulse Q2 2026 report released this week finds organizations need clear ownership, decision rights, and governance structures that translate AI ambition into business results. Based on a survey of about 2,100 senior leaders across 20 countries, 75% say their CEO actively owns AI as a strategic priority—but accountability for AI outcomes remains less clear. In other words, many leaders “own” AI in theory, but few have decided who is on the hook when an AI-driven decision goes wrong.
Twenty-four percent of organizations identify the CEO or executive committee as ultimately accountable for AI-informed decisions, while 29% point to a named C-suite executive. Just 35% say they have “very clear” guidance on when humans should override AI outputs. Companies with clear executive accountability are more likely to strongly agree they can future-proof their AI strategy (60% vs. 22%), KPMG found.
Going deeper
"How global energy markets built the ‘Amazon of oil’ logistics to keep prices from spiraling" is a Fortune article by Jordan Blum.
Blum writes: "Businesses and governments managed to keep energy prices from skyrocketing as much as feared during the Iran war by leaning into a “just-in-time” delivery system that harnesses innovations in digital and satellite technology and that reduces the need to stockpile barrels of oil. Call it the “Amazon of oil,” said Jim Wicklund, a veteran oil analyst and managing director at the PPHB energy investment firm, comparing energy industry dynamics to the ecommerce giant’s famous mastery of inventory and logistics." Read more here.
Overheard
“Everyone is reluctant to say there should be regulation, but what we really have right now is regulation without transparent or complete rules. Without rules, businesses can’t plan.”
—Microsoft President Brad Smith weighed in on U.S. AI policy in a conversation with Fortune on the sidelines of the AI for Good Global Summit.
