Citadel Securities founder Ken Griffin spoke with Bloomberg’s Dani Burger at our recent Future of Global Markets Conference. Ken and Dani discussed the transformative potential of artificial intelligence, and how investors are becoming more discerning in this rapidly growing market. Read the key takeaways below.
1. Artificial Intelligence: Transformative Potential and the Future of Work
- The advancement in AI models over just the past year has been absolutely tremendous. In a number of fields, AI is literally game-changing. Work that used to take our PhDs and master’s-level employees four to six weeks can now be completed in a matter of hours.
- There are three implications:
– For workers: AI poses a real threat to certain white-collar jobs. We need to embrace reskilling in a profound way. There’s plenty of talk about it, but very little action.
– For corporate America: Competitive moats are being filled in by bulldozers. Companies will need to innovate faster, create more customer value and take costs out faster. That’s ultimately a win for the American consumer.
– For entrepreneurs: This is a golden era for new business formation. Startups will unleash products we’ve never even thought of and create opportunities for people who don’t have perfect pedigrees to build successful careers.
- The history of our free market is that we go through transitions like this. They’re challenging for incumbents and difficult for workers, but ultimately our lives are better.
2. AI Markets: Investors Are Becoming More Discerning
- For the last several years, investors have largely bought into the AI theme: We’re going to spend hundreds of billions or trillions on data centers and compute. Buy the hyperscalers, buy the chip companies, buy the entire supply chain.
- Now we’re reaching a point where people are becoming more discerning. Who actually earns the economic rents? Where are the real supply constraints? How long will today’s extraordinary margins persist?
- GPU overcapacity is a significant risk. GPUs have very low marginal operating costs, much like airlines. When capacity exceeds demand, pricing can go into freefall. We saw a similar dynamic during the telecom buildout in 2000, when excess fiber capacity drove telecommunications prices sharply lower.
- Investors are also reconsidering the useful life of GPUs. Five- or six-year-old chips may command extraordinary pricing today, but that doesn’t mean those economics will persist for another five or six years. Revenue and valuation assumptions for years seven, eight and nine need to be reconsidered.
- Corporate America is becoming much more sophisticated about extracting value from AI. Companies are asking where they truly need expensive, state-of-the-art models from OpenAI and Anthropic, and where open-source models can do the job at a fraction of the cost.
- There is a tension between the enormous spending ambitions of foundational model companies and their customers’ efforts to maximize returns and control costs. The question is whether these models become so indispensable—potentially by solving problems like curing cancer—that customers will pay almost any price.
3. Is AI a Bubble?
- There are almost certainly bubbles within this moment in time. Radical transformations of our economy are generally intertwined with bubbles.
- Think about the internet in 1999 and 2000. Some companies had pretty fanciful business models, but the internet fundamentally transformed our lives. I just wish I’d kept my Amazon stock.
- We’ve seen this with other transformative technologies, including the railroads. What’s left in the wake of these bubbles is often game-changing for the world, and the companies that emerge on the other side can be market leaders for decades.
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