The Magnificent Seven companies alone accounted for over half of the S&P 500’s annual gains last year, just as AI-driven companies now make up over a third of the index’s companies. That means the same AI boom putting pressure on some entry-level jobs is also lifting the index funds, 401(k)s, and brokerage accounts on which many retirees rely. Morningstar data shows the 10 largest 401(k) mutual funds now average a 38% allocation to tech and communication services—a concentration that would have been considered aggressive speculation a decade ago.

But retirees are not passive beneficiaries since they face a mirror-image version of the same risk: less time to recover if the AI trade reverses. A sequence-of-returns shock in a tech-heavy portfolio at age 67 is not the same as a drawdown at 32. The upside and the fragility are two sides of the same coin.

The entry-level squeeze

A Stanford study found a 13% decline in employment for workers ages 22 to 25 in the most AI-exposed jobs, just as the leaders of those AI companies themselves warn of upcoming job displacement. Goldman Sachs estimates AI is eliminating roughly 16,000 net U.S. jobs per month, with entry-level workers absorbing the largest share. Entry-level job postings have fallen nearly 35% since January 2023, according to Revelio Labs, and among young software developers specifically, employment has dropped close to 20%. 

The Brookings Institution has documented that AI productivity gains are flowing disproportionately to workers earning around $90,000 or more, while lower-wage and early-career workers face the greatest displacement risk. As a result, the economy is becoming increasingly tilted toward those who already own assets like stock portfolios, index funds, and real estate, which appreciate as AI drives corporate margins higher.

Baby boomers, who make up roughly 20% of the U.S. population, hold more than $85 trillion in assets and control 54% of all U.S. stocks, which are worth more than $25 trillion. Gen Z, which makes up a comparable share of the population, holds just $6 trillion in total wealth. Market veteran Ed Yardeni has coined a term for what that imbalance produces: a “Gen-shaped economy,” in which boomer spending and boomer asset appreciation drive macroeconomic conditions while younger generations are largely spectators. 

For the lucky few, a ‘have your cake’ moment

For younger workers, AI can be “incredibly dangerous” because it may threaten their job, said Jonny Jonson, senior vice president and wealth advisor at Compound Planning, a tech-enabled registered investment advisor and digital family office that surpassed $5 billion in assets under management in April 2026. But for older investors, he said, it could be “actually great” if it keeps equity markets rising.

Jonson said although this applies across the board, it’s particularly apparent for tech workers. “Depending on when they joined, some employees are sitting on pretty remarkable paper gains, in some cases 20x or more,” Jonson told Fortune. “Liquidity events provide them opportunities to secure financial independence, pay off the house, pay for college, diversify, and still have some upside.”

A young employee at a major AI company may have a salary, bonus, career path, and stock compensation all tied to the same market narrative. If that worker also has a large amount of company stock, the risk is not just that the market sours, but that their job and their portfolio fall at the same time.

But for a lucky few, he said, “it’s truly a have your cake and eat it too moment.”

However, not everyone is in that position. Employees who joined later may be facing a much more emotional calculation. “We’ve seen the narrative shift over the past few months with OpenAI and Anthropic, and employees are worried it could be a winner-take-all situation,” Jonson said. “That can make equity feel less like guaranteed upside and more like a concentrated emotional bet, which carries a lot of psychological weight.”

That’s where Jonson says financial planning matters, saying it’s not whether AI will keep winning, but rather, how much of someone’s financial life is tied to that outcome.

“One way to potentially spin it is: You have a million dollars of your company stock. Should I just sell and put it in a high-yield savings account?” Jonson said.

Risk ability vs. risk tolerance

For Jonson, he said investors should answer that question and look at it at an angle less of risk tolerance and more of what he calls “risk ability.”

“Risk tolerance, I think, gets a bit overused in the industry, but I think it’s not married enough to risk ability. Like, what is your ability to take risk?”

Risk tolerance is how much volatility someone thinks they can handle. Risk ability is whether their actual life can absorb the hit. A 28-year-old with a stable job, emergency savings, and decades before retirement may be able to ride out a market selloff. A 28-year-old whose paycheck, stock grants, and career prospects are all tied to one AI-heavy employer may not have the same cushion, even if they feel comfortable taking risk.

“I think risk tolerance is so much confined to, like, I don’t understand risk. And once you can understand risk, then I think your risk tolerance gets closer to your risk ability, because you understand why,” Jonson said. “I think that’s where we as an industry can do a better job of helping people think about risk ability more at the forefront.”

Take previously considered “safe bets” as a prime example. Bonds, money-market funds, and high-yield savings accounts no longer look as irrelevant as they did during the zero-rate era. For a tech worker sitting on concentrated company stock, moving some money into safer assets may not be a bearish call on AI, but diversification.

Retirees seem to face the opposite problem: Though they may not face the same job risk from AI—and may actually benefit if AI keeps lifting corporate profits and stock prices—they also have less time to recover if the AI trade reverses.

AI is also changing how his own clients approach financial advice. “We’re seeing clients, including employees at AI companies, use AI more and more as a first pass for major financial decisions,” Jonson said. “This can naturally help inform them, but they still come to us as advisors to help contextualize that information into their situation and implement the right strategies.”

In one case, Jonson pointed to a client who used AI to evaluate a tender offer and initially felt confident in the answer. After advisors added a broader planning lens, including taxes, concentration risk, liquidity needs, and long-term goals, the client brought that framing back to the AI tool, which recognized that the added context changed its initial analysis.

“AI is a good validator,” Jonson said. “But the quality of the answer depends on the quality of the framing.”