• An employee from Berkshire Hathaway’s pilot training company FlightSafety International had a near flawless record guessing NCAA men’s college basketball games, with the defeat of Xavier at the hands of Illinois being the sole mistake. For 10 years, Buffett had tried to award a winner, relaxing the rules until he finally could declare one.

Closing the game out by sinking eight of his last nine shots from the field, six-foot-nine Canadian wing Will Riley led the Fighting Illini to a comfortable victory over Xavier University in the first round of the NCAA Championship. 

In theory, at least it shouldn’t have come as a surprise for the sixth-seeded Illinois. And yet it was the only one out of 32 games that an employee of Berkshire Hathaway guessed wrong when predicting the outcome of the initial slate of do-or-die games that eventually crown the best U.S. college men’s team to grace the basketball court.

No matter—the unnamed individual working at FlightSafety International, a pilot training company acquired by Berkshire Hathaway, will now walk away a million dollars richer. At least before taxes.

He or she won Warren Buffett’s March Madness giveaway, beating out 11 runners-up who astonishingly were almost but not quite as prescient. They, too, had gotten 31 games right, only their string didn’t last as long as the first 29.

It didn’t stop there either, as the FlightSafety worker later put the icing on the cake with a continued demonstration of their oracular abilities in the field of college football. 

“The winner’s credentials were further burnished on Saturday and Sunday by the prediction of 13 straight winners and bringing the winner’s overall record for the first 45 games to 44 winners and one loss,” Berkshire Hathaway said in a statement on Monday, singling out the Xavier defeat as the only game to besmirch this otherwise flawless record.

The other 11 runners-up will receive a further $100,000 each.

‘I want to give away a million dollars to somebody while I’m still around’

Eleven years ago, Berkshire Hathaway started its March Madness bracket challenge, granting $1 billion to whoever predicted all 67 games correctly. Since then, Buffett has tweaked the rules in the hopes of eventually landing a winner.

This year, he made it easier still—easier in the loosest sense of the word, at least. To win, any employee of a Berkshire Hathaway company had to pick the winners of at least 30 of the first 32 games from the first round of tournament action. 

“I’m getting older,” the 94-years-young Buffett told the Wall Street Journal. “I want to give away a million dollars to somebody while I’m still around as chairman.”

It’s no surprise there hasn’t been a winner. A layman without any deep understanding of the competition or its teams would not stand even the remotest of chances predicting as many correctly as the anonymous victor.

Mathematically speaking, the odds of correctly guessing a coin flip 31 times out of 32 are roughly 1 in 134 million.

This story was originally featured on Fortune.com

• As Tesla faces backlash over its CEO Elon Musk’s personal politics, longtime investor Cathie Wood says falling sales could be part of the broader economic concerns. A series of auto industry headwinds are hitting Tesla while Musk’s political involvement stirs up widespread protests. Despite these struggles, the future of the company remains: a new, affordable EV model and the promise of perfecting self-driving cars. 

Ark Invest CEO Cathie Wood believes part of the recent “demand hit” Tesla’s taken could be because of broader fears about the economy. 

“Now, clearly the political dynamics of the last few months are hitting demand,” Wood said in a video posted to Ark Invest’s website on March 14. “We also would suggest that the economic outlook is hitting demand—not just for Tesla—but for all auto manufacturers.” 

She added it was challenging to parse out which was hurting Tesla’s sales more. 

“It’ll be difficult to discern how much of the demand hit is due to a political attack and how much is economic,” Wood said. 

In recent weeks, Tesla dealerships and cars have been vandalized in various parts of the country. Earlier this month at a Tesla showroom in New York City, a peaceful protest became heated, leading to the arrests of nine people. Across the country, other people have been arrested for vandalizing Tesla locations. 

Tesla’s market share in Europe has taken a hit, as some people who disagree with Musk’s politics have stopped buying his company’s cars. In China, one of Tesla’s biggest markets, the company faces stiff competition from local rivals. Here in the U.S., drivers reportedly traded in Teslas at record rates over the last two months. 

At the same time, the broader auto industry is floundering. Nissan laid off 9,000 employees in December and Volkswagen closed factories in its native country Germany. In the U.S., the big three carmakers—Ford, GM, and Stellantis—stumbled when EV sales slowed, after they had spent billions diversifying away from gas-powered cars. Now those companies have to reckon with the Trump administration’s new blanket tariff policy, which could hit the import-heavy auto business especially hard. 

Across the broader economy, consumer confidence has been falling since the start of the year, now sitting at a yearlong low. Plus, major banks have increased their recession risks. 

Despite both Tesla’s own challenges and the possibility of an economic downturn, Wood remains extremely bullish on Tesla. In an interview with Bloomberg on Monday, Wood said she expected Tesla’s stock to reach $2,600 in five years. That would be roughly 10 times its current share price of $275.93.

Tesla and Ark Invest did not respond to Fortune‘s request for comment.

In Wood’s view, Tesla’s prospects hinge on releasing its new, lower-priced model and on perfecting its self-driving technology. Tesla and Musk have been touting a cheaper EV in the $25,000 range for several years. In January, Tesla told investors it should expect the model in the first half of this year. In the past, though, similar plans had been scrapped, dampening investor hopes this time around. 

However, if Tesla were to develop a truly autonomous vehicle, then it would find itself less reliant on car sales, instead turning into a software business. Much of Wood’s thesis relies on the notion that if—or in her mind when—Tesla finally launches a self-driving vehicle, it will instantly create a fleet of robotaxis from the millions of Tesla’s already on the road. 

“That same asset that already exists with no incremental cost change, just a software update, [will] now have 5 times or more the utility than they currently have,” Musk said on Tesla’s earnings call in January. 

So far, Tesla’s self-driving systems can’t yet drive entirely without human supervision. But the company has long considered it a priority. 

“Autonomous taxi networks represent the biggest AI project in the world,” Wood said. “Elon himself is focused on any bottleneck, anything that is hampering progress or slowing Tesla down.”

This story was originally featured on Fortune.com

Hello and welcome to Eye on AI. In this edition: A new study suggests AI can be a team player…OpenAI promotes its COO while CEO Sam Altman shifts focus…Apple shakes up its AI team amid frustration over delayed Apple Intelligence features…a revolutionary new AI weather forecasting method…and AI transforms architecture.

Evidence of AI’s positive impact on productivity continues to mount. But while many executives view AI as ultimately a substitute for human labor, hoping it will eventually fully automate tasks and save on headcount, the data suggests that this is not the best way to think about the technology. Yes, in a few cases, AI can fully automate some tasks. But in most cases, today’s AI systems—including the so-called “AI agents” from the likes of Salesforce, ServiceNow, Microsoft, and Google—aren’t yet capable or reliable enough to do this. Instead, AI systems should be thought of as a complement to human labor—a way to lift the performance of people, not to replace them.

The latest support for this view comes from a fascinating study by a group of researchers—from Harvard, the University of Pennsylvania’s Wharton School of Business, ESSEC Business School in France, and consumer products giant Procter & Gamble—and published as a working paper on the research repository SSRN. (The authors include Wharton’s Ethan Mollick, who has attracted a huge social media following for his tips on how to use AI effectively in business.)

In 2024, the researchers conducted a one-day virtual product development workshop at P&G, with the process designed to mirror the one that consumer products behemoth famously uses—except this time with an AI twist. In particular, this workshop involved the “seed” stage of product development—which is about brainstorming lots of possible new product ideas and incubating them to the point where a decision can be made on whether to test them at a larger scale. P&G normally assigns two-person teams consisting of one Commercial operations person and one R&D expert to work together on brainstorming ideas. In this case, the researchers took 776 P&G employees from Commercial and R&D and randomly assigned them to do one of the following: work alone; work alone but with access to a generative AI assistant based on OpenAI’s GPT-4 model; work in the usual two-person brainstorming team consisting of one Commercial and one R&D person; or work in the usual two-person configuration but with access to the AI assistant.

The groups were then tasked with coming up with new ideas for consumer products in the various P&G divisions in which they worked (baby care, feminine care, grooming, and oral care). These ideas were then assessed by human judges with both relevant business and technology expertise.

AI lifts individual performance—by a lot 

Two heads are generally better than one, so it is perhaps not surprising that individuals working alone and without access to AI did the worst. But it turned out that individuals assisted by AI performed, on average, better than two-person teams without AI. In fact, the performance of these AI-assisted individuals was not statistically better than two-person teams working with AI. This might lead one to conclude that AI can indeed be a good substitute for human labor—enabling a company like Procter & Gamble to reduce its two-person product teams to just single individuals brainstorming with the help of AI. 

There were some other big benefits to the individuals working with AI, too. Individuals working with AI were able to work faster—taking more than 16% less time to come up with an idea compared to people working without AI, while teams working with AI were about 12% faster. 

Working with AI was also better than “bowling alone”—individuals reported more positive emotions and fewer negative ones during the product ideation process than the unassisted lone wolves.

Importantly, people working alone tended to come up with ideas that fit primarily into their professional silos—commercial people favoring product innovations that were mostly about novel commercial ideas (changes in branding, packaging, or marketing strategy) while the R&D specialists favored technological innovations. But when assisted by AI, these individuals achieved blended approaches, combining both technical innovation and commercial innovation—just like the human-human pairings did. “This suggests AI serves not just as an information provider but as an effective boundary-spanning mechanism, helping professionals reason across traditional domain boundaries and approach problems more holistically,” the researchers wrote.

Helping teams to be extraordinary

But, before you jump to the conclusion that AI should be used to reduce team sizes, it is important to point out perhaps the most interesting finding of the whole study: The two person teams working with AI produced far more ideas that the human experts rated as “exceptional”—the 10% that they judged most likely to lead to truly breakout products. And the human teams assisted by AI also reported the most enjoyment from working on the task, compared to the other groups.

Blogging about the findings, Mollick wrote that “organizations have primarily viewed AI as just another productivity tool, like a better calculator or spreadsheet,” but that employees were often using “AI for critical thinking and complex problem solving, not just routine productivity tasks.” AI could be seen as another member of the team—as a collaborator—not just another tool, he wrote. “Companies that focus solely on efficiency gains from AI will not only find workers unwilling to share their AI discoveries for fear of making themselves redundant but will also miss the opportunity to think bigger about the future of work,” he wrote. He encouraged organizations to reimagine work and management structures, not just seek to automate existing processes.

I am sure this is correct. Unfortunately, the temptation for many managers will be to grab at the obvious labor and time savings AI offers, since there is an obvious and immediate pay-off in labor savings. It will take braver executives to argue for keeping people in place but using AI to empower them to be exceptional.

With that, here’s the rest of this week’s AI news. 

Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn

Before we get to the news, if you’re interested in learning more about how AI will impact your business, the economy, and our societies (and given that you’re reading this newsletter, you probably are), please consider joining me at the Fortune Brainstorm AI London 2025 conference. The conference is being held May 6-7 at the Rosewood Hotel in London. Confirmed speakers include Cohere CEO Aidan Gomez, Mastercard chief product officer Jorn Lambert, eBay chief AI officer Nitzan Mekel, Sequoia partner Shaun Maguire, noted tech analyst Benedict Evans, and many more. I’ll be there, of course. I hope to see you there too. You can apply to attend here.

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This story was originally featured on Fortune.com