Hello and welcome to Eye on AI. In this edition….Insights from Fortune Brainstorm AI San Francisco…Disney invests $1 billion in OpenAI and licenses its IP to the company…OpenAI debuts GPT-5.2 in effort to silence concerns it’s trailing rivals…Oracle stock takes a tumble.
Hi, it’s Jeremy here. I’m still buzzing from Fortune Brainstorm AI San Francisco, which took place earlier this week. We had a fabulous lineup including Brad Lightcap, OpenAI’s chief operating officer, Google Cloud CEO Thomas Kurian, Intuit CEO Sasan Goodarzi, Exelon CEO Calvin Butler, Databricks CEO Ali Ghodsi, Rivian CEO RJ Scaringe, Insitro CEO Daphne Koller, and many more. We also had a thoughtful conversation on AI’s impacts with actor, director, and increasingly AI thought leader Joseph Gordon Levitt, as well as a scream of a session with actor, comedian and AI CEO Natasha Lyonne. Today, Sharon Goldman, Bea Nolan, and I are going to share a few highlights and personal impressions.
For me, there was a notable vibe this year that a lot of companies are substantially further along in implementing AI across their organizations, including using AI agents in some limited, but important, capacities. Many audience questions, especially in some of the breakout sessions, were around governance and orchestration methods for an increasingly hybrid workforce where AI agents will be completing tasks alongside employees.
Still, it was striking to hear Butler, the Exelon CEO, say that his company is moving cautiously. When the consequence of getting something wrong is literally lights out, security and reliability have to take precedence over everything else. And so Butler said he was happy not to be a “first mover” but instead a “fast follower” when it came to AI implementations. Let other people take the hit and learn from their mistakes, seems to be his view.
And this wasn’t the only place where speakers were seeking to tamp down hype. It was refreshing to hear Michael Truell, the cofounder and CEO of hit coding assistant Cursor tell me that he didn’t think software engineering would ever be fully automated in the way that OpenAI CEO Sam Altman sometimes talks about. Instead Truell said that while the amount of time that coders spent on “compilation” of code would continue to shrink, he saw a continued need for humans to make design decisions around “how should the software work.”
Similarly, Vidya Peters, from DataSnipper, said she thought there would still be a role for qualified accountants within finance organizations, even if they were increasingly being assisted with AI tools such as the one her company makes. She also said she thought that applications geared specifically for a particular industry or job—especially in regulated industries—would continue to win out over more general purpose AI models, even as the big AI companies are increasingly targeting specific professional use cases for their general purpose models.
A panel that Sharon moderated on the “new geography of data centers” was fascinating. The message was that right now, data centers are going where the power is. But increasingly data centers are going to be looking to build their own power on site and possibly even become net contributors to the grid. And Jason Eichenholz, the CEO of Relativity Networks, said that as AI inference workloads come to eclipse AI training workloads, there will be an increasing need to bring data centers close to major population centers, but that most cities in the U.S. are power constrained. How are we going to get these urban centers the tokens they need at the speed at which they need them? That’s anyone’s guess right now, Eichenholz says—although his company builds the fast fiber that will carry those tokens from the data centers to end users.
Finally, I enjoyed hearing Dayle Stevens from Telstra explain why her company chose to form a joint venture with Accenture to deliver its AI stragegy, rather than simply hiring the consulting firm under a traditional service contract. Stevens said the joint venture has enabled the company to move much faster than it would have otherwise and to tap expertise, including starting an AI innovation hub in Silicon Valley, that would have been hard to implement otherwise.
