• The S&P 500 has become a lopsided index, with the Magnificent Seven significantly increasing risk exposure for investors, according to Apollo chief economist Torsten Sløk. As the paths of the Magnificent Seven begin to diverge and the AI bubble swells, Sløk argues it’s time to begin questioning which AI companies to invest in.

It’s time to question the soundness of continued zealous investment in the Magnificent Seven, one top economist warns. 

The S&P 500 has become “extremely concentrated,” with the top 10 stocks contributing 54% of market returns since January 2021, Apollo chief economist Torsten Sløk said in a Friday blog post. With the cluster of tech stocks at the top beginning to unravel, he is pouring cold water on continued aggressive investment in the index and in the Magnificent Seven.

“The textbook idea that the S&P 500 gives you a diversified exposure to risk is just simply no longer the case,” Sløk told Fortune. “You are very focused and concentrated in a small group of names, in particular in tech, making up such a significant share of your overall risk exposure.”

The top 10 companies in the S&P 500 now prop up 40% of the index’s market capitalization—more than 30% of which is from the Mag Seven—meaning the fortune of the markets has become increasingly reliant on investor optimism about AI. Alphabet’s AI rally not only helped mint CEO Sundar Pichai as a billionaire, for example, but the Google parent’s earnings beat gave the S&P 500 its fourth consecutive record close on Thursday.

But as the AI bubble swells larger than the IT bubble a quarter-century ago, as Sløk has previously noted, the extreme hype around the technology risks creating even broader economic consequences than the dotcom crisis. To protect one’s individual investments, now is the time to reconsider pouring money into the Mag Seven, Sløk argued.

“One should have some exposure to the S&P 500 and should certainly also have some exposure to AI,” Sløk said. “But it’s very clear that [owing to] the market’s extreme focus and concentration on this story, this is the time to have a conversation around, What are the things I should be doing with my money?”

The Magnificent Seven becomes Six, becomes Five

Mounting concerns over the ramifications of a growing AI bubble coincide with the unraveling of the Magnificent Seven stocks.

“We’re beginning to have conversations about the ‘Magnificent Six,’ maybe it’s only five,” Sløk said. “This is also just telling you that the Magnificent Seven are seven very, very different companies that have very different businesses.”

Popularized in 2023 by Bank of America analyst Michael Hartnett, the “Magnificent Seven” term acknowledged a group of companies alike in their goal of pushing toward an AI future, but these seven firms, once in lockstep, are beginning to diverge in their levels of success and areas of investment. 

Apple, for example, has lagged behind competitors like Microsoft and Meta in developing AI products and services. With its stock down about 12% year to date, some market watchers have called for CEO Tim Cook to step down, despite Cook’s boosting the stock price by nearly 1,500% over the past decade-plus. 

Tesla has meanwhile failed to deliver on promises of autonomous driving, continuing this week its streak of sales misses and disappointing quarters. Tesla’s stock has fallen nearly 15% in 2025 as investor confidence in CEO Elon Musk continues to be tested.

Nvidia this month became the first publicly traded company with a more than $4 trillion valuation as its stock price surged by approximately 1,460% over the past five years. The company is expected to see strong sales growth, despite increasing competitive pressures.

Ahead of next week’s earnings reports for Meta, Apple, and Microsoft, analysts are continuing to scrutinize the pricing of these companies’ stocks, assessing if there are other options in the tech sector worth buying into.

“AI will continue to have a dramatic impact on all our lives,” Sløk wrote in his blog post. “But the question remains whether the Magnificent Seven are correctly priced, and if they will even be the best AI investments over the next five to 10 years.”

This story was originally featured on Fortune.com

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• Chipotle CEO Scott Boatwright said the burrito chain needs to work on selling itself as a bargain brand for jittery, budget-strapped consumers. The company reported on Wednesday a 4% same-store quarterly sales decline and cut its guidance for the rest of the year, citing poor consumer sentiment and economic uncertainty. 

As more Americans grow anxious about the economy and start pulling back on eating out, CEO Scott Boatwright wants consumers to give Chipotle some more credit for its low prices.

The Newport Beach, California-based burrito-bowl chain reported sagging earnings Wednesday, including a 4% same-store sales decline and 4.9% dip in quarterly traffic. While Chipotle saw a 3% total revenue increase to $3.1 billion, the company cut its guidance, now expecting flat same-store sales growth for the year compared to its previous prediction of a low single-digit increase.

Chipotle CEO Scott Boatwright attributed the rough quarter—Chipotle’s second consecutive sales decline—in part to rocky economic conditions leading consumers to pull back. Chipotle’s same-store sales improved in June, and that’s likely to be the case for July as well, according to the company, but lackluster sales in April and May correlated with “consumer sentiment bottoming around that time.” 

Boatwright added consumers have seemingly forgotten that Chipotle, compared to its fast-casual rivals, is a bargain.

“I don’t think we’re getting credit with the consumer today,” Boatwright told investors on Wednesday. “So what I talked to the team about internally is, How do we better communicate our value proposition and center around the core equities of the brand?”

“I think we’ve got to figure out a way we can communicate value for the consumer and showcase the value we are to [quick-service restaurants] and fast-casual,” he added.

Boatwright claimed in the earnings presentation Chipotle is 20% to 30% cheaper than comparable fast-casual restaurants. He told Fortune in April the chain wouldn’t increase prices due to tariffs because “it’s unfair to the consumer to pass those costs off…because pricing is permanent.”

Changing perceptions of value

The CEO was firm in attributing Chipotle’s sales slump to external macroeconomic factors, telling investors, “There’s no smoking gun here that says we’ve had a misstep.” However, he said low-income consumers in particular are looking for value when choosing where to dine.

“Look no further than what’s going on with our competitors with snack occasions or five-dollar meals, and that’s where the consumer is drifting towards…because of low consumer sentiment.”

Indeed, fast-food giants like McDonald’s are continuing to offer meal deals amid softening sales, particularly as these restaurants have seen more traffic from high-income consumers while those on a budget pull away. As Chipotle similarly tries to compete in an environment of cautious consumers, it will need to focus on its public perception and sell itself as an affordable option, according to Raymond James restaurant analyst Brian Vaccaro.

“Over the last two years, the industry has gotten more aggressive on value promotions and messaging,” Vaccaro told Fortune. “There are certain brands that have a strong value proposition in the mind of the average consumer. But they didn’t effectively message that, and it caused them to lose some mind share.”

Olive Garden suffered this fate in 2024, Vaccaro said, when the fast-casual Italian chain’s parent company Darden Restaurants reported a pull back from customers making less than $75,000. 

“That could be something that’s happened to Chipotle, where their value almost gets taken for granted a little bit,” Vaccaro said.

In March, Olive Garden announced the return of its “buy one, take one” promotion—essentially a buy one, get one free deal—for the first time in five years. The restaurant group attributed a modest earnings beat in June in part to the return of the offer.

“Everyone knows Olive Garden is a good value,” Vaccaro said. “But if you’re not reminding the guests of that, they could get distracted and wooed away by all of these value promotions that are floating around.”

This story was originally featured on Fortune.com

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• AI tools don’t always boost productivity. A new study from Model Evaluation and Threat Research found that when 16 software developers were asked to perform tasks using AI tools, the they took longer than when they weren’t using the technology, despite their expectations AI would boost productivity. The research challenges the dominant narrative of AI driving a workplace efficiency boost.

It’s like a new telling of the “Tortoise and the Hare”: A group of experienced software engineers entered into an experiment where they were tasked with completing some of their work with the help of AI tools. Thinking like the speedy hare, the developers expected AI to expedite their work and increase productivity. Instead, the technology slowed them down more. The AI-free tortoise approach, in the context of the experiment, would have been faster. 

The results of this experiment, published in a study this month, came as a surprise to the software developers tasked with using AI—and to the study’s authors, Joel Becker and Nate Rush, technical staff members of nonprofit technology research organization Model Evaluation and Threat Research (METR).

The researchers enlisted 16 software developers, who had an average of five years of experience, to conduct 246 tasks, each one a part of projects on which they were already working. For half the tasks, the developers were allowed to use AI tools—most of them selected code editor Cursor Pro or Claude 3.5/3.7 Sonnet—and for the other half, the developers conducted the tasks on their own.

Believing the AI tools would make them more productive, the software developers predicted the technology would reduce their task completion time by an average of 24%. Instead, AI resulted in their task time ballooning to 19% greater than when they weren’t using the technology.

“While I like to believe that my productivity didn’t suffer while using AI for my tasks, it’s not unlikely that it might not have helped me as much as I anticipated or maybe even hampered my efforts,” Philipp Burckhardt, a participant in the study, wrote in a blog post about his experience.

Why AI is slowing some workers down

So where did the hares veer off the path? The experienced developers, in the midst of their own projects, likely approached their work with plenty of additional context their AI assistants did not have, meaning they had to retrofit their own agenda and problem-solving strategies into the AI’s outputs, which they also spent ample time debugging, according to the study. 

“The majority of developers who participated in the study noted that even when they get AI outputs that are generally useful to them—and speak to the fact that AI generally can often do bits of very impressive work, or sort of very impressive work—these developers have to spend a lot of time cleaning up the resulting code to make it actually fit for the project,” study author Rush told Fortune.

Other developers lost time writing prompts for the chatbots or waiting around for the AI to generate results.

The results of the study contradict lofty promises about AI’s ability to transform the economy and workforce, including a 15% boost to U.S. GDP by 2035 and eventually a 25% increase in productivity. 

But Rush and Becker have shied away from making sweeping claims about what the results of the study mean for the future of AI.

For one, the study’s sample was small and non-generalizable, including only a specialized group of people to whom these AI tools were brand new. The study also measures technology at a specific moment in time, the authors said, not ruling out the possibility that AI tools could be developed in the future that would indeed help developers enhance their workflow.

The purpose of the study was, broadly speaking, to pump the brakes on the torrid implementation of AI in the workplace and elsewhere, acknowledging more data about AI’s actual effects need to be made known and accessible before more decisions are made about its applications.

“Some of the decisions we’re making right now around development and deployment of these systems are potentially very high consequence,” Rush said. “If we’re going to do that, let’s not just take the obvious answer. Let’s make high-quality measurements.”

AI’s broader impact on productivity

Economists have already asserted that METR’s research aligns with broader narratives on AI and productivity. While AI is beginning to chip away at entry-level positions, according to LinkedIn chief economic opportunity officer Aneesh Raman, it may offer diminishing returns for skilled workers such as experienced software developers.

“For those people who have already had 20 years, or in this specific example, five years of experience, maybe it’s not their main task that we should look for and force them to start using these tools if they’re already well functioning in the job with their existing work methods,” Anders Humlum, an assistant professor of economics at the University of Chicago’s Booth School of Business, told Fortune.

Humlum has similarly conducted research on AI’s impact on productivity. He found in a working study from May that among 25,000 workers in 7,000 workplaces in Denmark—a country with similar AI uptake as the U.S.—productivity improved a modest 3% among employees using the tools. 

Humlum’s research supports MIT economist and Nobel laureate Daron Acemoglu’s assertion that markets have overestimated productivity gains from AI. Acemoglu argues only 4.6% of tasks within the U.S. economy will be made more efficient with AI.

“In a rush to automate everything, even the processes that shouldn’t be automated, businesses will waste time and energy and will not get any of the productivity benefits that are promised,” Acemoglu previously wrote for Fortune. “The hard truth is that getting productivity gains from any technology requires organizational adjustment, a range of complementary investments, and improvements in worker skills, via training and on-the-job learning.”

The case of the software developers’ hampered productivity points to this need for critical thought on when AI tools are implemented, Humlum said. While previous research on AI productivity has looked at self-reported data or specific and contained tasks, data on challenges from skilled workers using the technology complicate the picture.

“In the real world, many tasks are not as easy as just typing into ChatGPT,” Humlum said. “Many experts have a lot of experience [they’ve] accumulated that is highly beneficial, and we should not just ignore that and give up on that valuable expertise that has been accumulated.”

“I would just take this as a good reminder to be very cautious about when to use these tools,” he added.

This story was originally featured on Fortune.com

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