During a panel moderated by Fortune’s Allie Garfinkle, Kindred Ventures founder Steve Jang and Sapphire Ventures partner Cathy Gao tackled the question dominating Silicon Valley: Are we in an AI bubble? The answer was, in short, maybe, but that’s the wrong question to ask.

“I think it is a bubble, but bubbles are good for innovation,” said Jang. He argued that the term “bubble” is often just finance shorthand for a “new technology wave” that occurs every five, six, seven years. According to Jang, this market heat is functionally necessary: “You need a bubble in technology and startups … to not only attract the world’s best talent to work on a certain set of problems but you also need the capital to fund them.”

Jang pointed to the exodus of top engineers from stable roles at tech giants like Google, Meta, and Uber to launch startups as a “good signal” rather than a warning sign. While admitting that “bubbles popping are bad,” Jang suggested that as long as the media continues to question the market, it helps “release pressure” and keeps the ecosystem healthy.

Gao agreed that in certain pockets, “valuations have far outstripped any sort of fundamental” metrics. However, she cautioned against dismissing the trend entirely, noting that the current growth curves “far outstrip the growth curves of companies we’ve ever seen before,” making the total addressable market difficult to calculate. “I don’t think we have a good sense of how big some of these companies can ultimately become.”

The Investment Playbook: Infrastructure vs. Workflow

Beyond the macroeconomic debate, the panelists outlined divergent strategies for surviving the pop, whenever it comes. Jang emphasized that in a true technology wave, “the whole stack changes,” creating opportunities from the bottom up. He noted that Kindred Ventures is focusing heavily on “accelerating and modernizing the AI infrastructure,” including chips, GPU marketplaces, and specialized frontier models. He observed that despite new entrants, margins remain high for cloud and chip providers, giving them “pricing power on all of the application layer companies.”

Gao, who focuses primarily on the application layer, offered a stricter framework for survival. “Let’s get real: AI is no longer a differentiator,” Gao said. She warned that “AI for X” companies are vulnerable. Instead, she said she looks for companies transitioning from simple features to complex workflows that embed deeply into an enterprise.

“In the future, it’s just going to be a customer support workflow tool, and every company will be powered by AI,” Gao said. She argued that despite the volatility, “first-mover advantage is actually real” in the enterprise sector, citing the enduring dominance of Salesforce and Workday that dates back to the cloud era.

Heartbreak Ahead for Robotics

The conversation turned darker regarding the future of robotics. Jang offered a “spicy” prediction for the sector, warning that many current startups are building on “primitive models” roughly equivalent to the “GPT 3.5 phase” of robotics.

“A whole bunch of robotics startups … are going to have a lot of heartbreak when the models improve and they’ve built for something sort of in the past,” Jang predicted. He added that many consumer robotics companies will likely “fall by the wayside” or shut down because the societal and governmental adoption cycles will be too long for startups to survive.

“We’re all going to be using robots on a daily basis,” Jang said. “Our kids are going to be riding in robots in a daily basis. That area is super exciting. But think about all of the startups building humanoids.” They will have to prove that their humanoids won’t, say, fall down or screw up or be buggy. “It’s going to move around in your office or household or on the street even,” he stressed, noting that every part of the physical world is going to have to prepare for humanoid robots potentially malfunctioning. “Think about that. And that is a deep tech problem.”

Looking toward 2026, Gao offered her own counter-intuitive forecast: despite better models, selling into the enterprise is “going to be even more difficult.” She cited unresolved issues regarding trust and visibility as hurdles that the industry has yet to clear. “People are going to be more focused on trust and visibility, and we haven’t really solved that problem yet.”

People have rightfully raised eyebrows as banks trim their workforces and funnel billions into AI capabilities. Businesses have already deployed the software in their operations, using monikers for AI tools like “Socrates,” performing hours worth of junior-level analyst tasks in just seconds. Simultaneously, a report from Citigroup has found that 54% of financial jobs “have a high potential for automation”—more than any other sector. But experts agree that AI-related layoffs have been insignificant, so far. This year’s flow of banking headcount reductions are a result of pandemic-era overhiring and economic uncertainty.

“If there’s a large company that might say, ‘Well, we’re not planning to hire as much because of AI,’ or maybe ‘We’re letting people go because of AI,’ I think there’s a little bit of smoke and mirrors there,” Robert Seamans, director of New York University Stern’s Center for the Future of Management, tells Fortune. 

“AI is often a scapegoat for things, because it’s easier to blame AI than it is to blame softening consumer demand, or uncertainty because of tariffs, or maybe poor HR strategy the past few years in terms of over hiring coming out of COVID,” he continues, adding that “there’s a lot less political risk than blaming the President’s tariffs.”

While AI isn’t capable of replacing bankers and consultants just yet, there could be trouble on the horizon for marketers and accountants, experts tell Fortune. And elite business degrees are still worth their while; the vast majority of top MBA students are still locking in job offers soon after graduation. But prospects are dwindling, and banking headcounts could stagnate for years as AI drives a massive productivity boom.

AI is stifling hiring in the banking industry—and it could last for years

Despite Wall Street making headlines for its relentless string of layoffs this year, headcounts across banking and finance have actually been relatively steady.  

“I think the general [headcount] trend in the banking industry over the last decade is stable to slightly declining. I don’t see that changing anytime soon,” Pim Hilbers, a managing director working with banking and talent at BCG, tells Fortune. “That doesn’t mean that everybody just stays in their job for life. I think we see a lot more mobility than we saw in the past.”

So far, America’s largest financial institutions haven’t been making deep workforce cuts. Bank of America employed just four fewer workers at the end of the third quarter this year, compared to 2024. In that same time period, JPMorgan saw its headcount climb by 2,000 employees, and more than a third of the new staffers were brought onto corporate operations. Even Goldman Sachs, which implemented multiple rounds of layoffs this year, employed 48,300 this September—around 1,800 staffers higher than the year before. 

Banks aren’t ready to shed staffers just yet; experts tell Fortune they’re pulling back on headcount growth for as long as possible, leaning on AI efficiency gains until they’re forced to add more humans to payroll. They predict this sluggish period of hiring could last for years. 

“Many of the banks I talked to will say, ‘Look, I want to get the productivity so that I don’t have to hire the next 100 people to put on another billion dollars of loans.’ That’s probably [what] the majority of thinking is: I just won’t have to hire for 24 months, because I can get the productivity,” Mike Abbott, industry group lead for Accenture’s banking and capital markets, tells Fortune. 

“As attrition flows through, you don’t have to hire as many, but then eventually you hit a point where you’re going to have to hire again.”

Top MBA students are still succeeding—but job offers are declining

MBA graduates are already feeling the hiring tremors in lieu of strong employment rates. Around 92% of the class of 2025 students from Columbia Business School received job offers, as did 86% of this year’s NYU Stern MBA graduates. Last year, 93% of Wharton students reported receiving work opportunities, and at Duke, 85% nailed down an offer letter. 

However, professors at these top business schools caution that the statistics aren’t a reflection of all MBA programs. Columbia and NYU Stern, for example, are nestled in the epicenter of U.S. finance: New York City. Additionally, these elite universities have more resources to skill students and boost their market value. Columbia Business School associate professor of business Daniel Keum tells Fortune that Python is an “almost required” class for all MBA pupils at the university. 

And while MBA job offer rates remain high, take a peek under the hood, and the prospects aren’t as plentiful. Job placement outcomes at every single one of America’s “magnificent seven” elite MBA programs—including Northwestern, MIT, Stanford, and Harvard—have declined since 2021, according to a Bloomberg analysis. In 2021, only 4% of Harvard’s MBA students received no job offer within three months of graduation; by 2024, that figure swelled to 15%. MIT saw a similar change, with its share of offer-less graduates climbing from 4.1% to 14.9% in a matter of three years. 

The finance roles that are still safe—and the ones most at risk

As AI has evolved to take on the grunt work—preparing slideshow presentations, synthesizing client data, and balancing checkbooks—it’s been feared that all junior-level analysts would soon get the boot. But not all jobs in the financial industry rely on the same core skills, and experts tell Fortune there are a few endangered roles in the era of AI disruption.

Surprisingly, the entry-level financial workers paying their dues and tediously crafting bespoke powerpoint presentations won’t be the first ones out the door. Keum tells Fortune that consulting and banking jobs “resist automation quite robustly.” He explains that their job tasks have little margin for error, as clients will not tolerate even the smallest mistake. Plus, every business deal is different; no two acquisitions are exactly alike, making it difficult to automate human critical thinking needed for the job. 

“Banking consulting [is] actually not doing too bad. Think about compliance issues where that 1% mistake is not tolerated. It cannot be accepted,” Keum says. “That’s why a lot of analyst jobs at McKinsey and Bain are automated, but it’s still extremely human intensive.”

Simultaneously, Abbott predicts an industry-wide surge in tech hiring. Around 76% of banks expect to increase their tech headcount because of agentic AI, according to Accenture data shared with Fortune. But human staffers in a few vulnerable roles might see the adverse effect of AI’s gains. It’s estimated that 73% of working time spent by U.S. banking employees has high potential to be impacted by generative AI, according to a 2024 Accenture report, improving the productivity of early AI-adopters by 22% to 30% over the next three years. Keum sees accounting and marketing roles being hit the hardest.

“Accountants are not doing well,” Keum told Fortune. “For accounting, it was, ‘Let’s make sure that your numbers are correct based on physical receipts inputted. Now, AI can do that very well…They’re hiring a lot less. So only the extremely senior people survive.”