Professor of the practice Rama Ramakrishnan recommended breaking tasks up into small, discrete parts, and then considering the potential costs of using AI to do them. "Some tasks, like writing ad copy, product descriptions, or a movie plotline, have slightly more room for error. Uses that require logical reasoning or factual knowledge; encompass cause-and-effect relationships; or have high stakes, like medical care, demand more accuracy," he explained.

Research scientist Christian Catalini said: "The binding constraint on growth is no longer intelligence. It is human verification bandwidth. The only A.I. that's useful is the A.I. that is verified."

News about a company's earnings for the quarter will always mention whether it beat analysts' predictions. Sell-side analysts at brokerages and investment banks who follow these companies are the ones setting these expectations, said professor Eric So. "Data providers like FactSet, Bloomberg, and LSEG average those forecasts into a consensus estimate. That consensus is the benchmark people mean when they say a company beat or missed," So explained.

Professor of the practice Gary Gensler joined "Closing Bell Overtime" to talk about the amicus brief he filed on sports betting regulation, the state of sports betting regulation, and perpetual futures.

A research briefing by research scientist Ina Sebastian and co-authors argued that leaders should determine the role of AI based largely on two factors: the ambiguity of a decision and the risk of getting it wrong. The briefing, based on interviews with executives across nine global organizations, identifies four broad categories of decisions: routine, consequential, exploratory, and strategic.

Professor Retsef Levi said: "I think that the first question is, what can we do to actually prevent these problems at the source?" Levi said that with new remote surveillance and blockchain technologies, the agricultural system could be better monitored, and therefore problems could be more quickly caught at the source. "Technology can help. Data can help. Processes can help. But at the end of the day, we need to have a strong fundamental culture of food safety," he said.

Research by professor Sinan Aral and co-author suggested that personalizing AI to fit the individual may be one of the most consequential design decisions a business can make. The paper is the first of its kind to test systematically how AI personalities interact with human personalities in a controlled experimental setting.

Visiting professor Gilbert Metcalf said: "On the supply side, it's not going to lead to any more diesel coming online, all it does is change some of the diesel that's out there to be usable by anyone. On the demand side, if we shift some of that diesel into road use, what does that mean? It means that the diesel is going to be more expensive for farmers and other off-road use, like construction."

"A lot of our digital lives are built on the infrastructure of foreign-made components and goods assembled abroad, and that's not going to change anytime soon," said principal lecturer Ben Armstrong. "We just don't know how to make them in the U.S. So, there will be a learning curve, and during that learning curve process, the price will be high," he said.

Distinguished senior lecturer Robert Pozen and co-author wrote: "The SEC is moving in the wrong direction by allowing mutual funds to charge one-sided performance fees and encouraging Wall Street to sell more private assets to unsophisticated buyers. Instead, the SEC should bolster investor protections by increasing the criteria for accredited investors to reflect inflation, and by ensuring all retail investors fully understand the risks in buying funds holding illiquid securities of private companies."

Jonah Prousky (PhD candidate) wrote: "I grade a lot of essays as a teaching assistant at MIT. With few exceptions, I've found that the students who use AI the least, or not at all, tend to score the highest. Not because we dock marks for using AI — we don't. In fact, students in the MBA class I support can use large language models (LLMs) as they see fit, provided they explain how they did so in an addendum. But there is something about using AI as a writing companion that seems to be keeping students from producing their best work."

At the Universo TOTVS 2026 event in São Paulo, senior lecturer George Westerman gave an interview to CNN Cast to discuss how artificial intelligence is affecting the corporate world and the job market. "AI doesn't produce value in companies on its own," he said. According to him, what AI does is enable businesses to operate differently — and that's the truly critical part of the transformation.

"I would encourage people to use AI to explain and define," said associate professor Taha Choukhmane. "If you're interested in knowing what the stock market is, what the difference between a mutual fund and an index fund is. Using AI to explain these concepts can be very useful because it can empower people to get the most out of these methods." Choukhmane also recommends asking AI to provide references to trusted sources to verify the information provided.

Professor Scott Stern explained that research accumulated over the past 20 years has shown that industrial clusters influence business activity, startups, innovation, and regional economic performance. However, he argued that the benefits of geographical proximity lead to actual growth not merely by gathering companies in one place, but only when people move within that space, technology and infrastructure are shared, and they become mutual customers and suppliers.

Professor Emilio J. Castilla emphasized that employee experience should not be measured solely by how people feel, but also by the real opportunities they have to join, learn, contribute, receive recognition, and advance. "When employees have real opportunities to contribute, learn, and exercise their judgment, organizations create better conditions for delivering higher-value experiences to their customers," he said.

According to lecturer Lars Frølund, Yucatán faces the challenge of moving from recognizing its strengths to turning them into concrete opportunities for innovation, entrepreneurship, and economic growth. The question, from his perspective, is not only what technology Yucatán can adopt in the face of the transformation driven by artificial intelligence, but also what advantage the state has and how it can turn it into an innovation platform capable of generating growth and opportunities.