Can AI help you figure out how much money you need to retire?

People are using artificial intelligence today for a range of tasks, from preparing work presentations and shopping to conducting scientific research. But is AI also useful in tackling the most consequential and complicated calculation a worker is ever likely to face: Can they afford to retire?

Americans are already turning to AI for financial advice, with about 20% saying they use chatbots for this purpose, according to a September study by AI company Pearl. About half of those who already use AI at work also use it for retirement planning — double the rate among workers who don’t use AI, MissionSquare Research Institute found in a separate study.

The need for retirement advice is real: Americans now say they expect to work four years longer than they’d like due to rising living costs and inadequate savings. The median balance for workers with retirement plans is $40,000, far short of the $1.5 million they say they need to retire comfortably. 

Meanwhile, Social Security — the financial backstop millions are counting on in retirement — could cut monthly benefits by as much as 20% in just six years, unless lawmakers take action to shore it up. 

Given those facts, it’s tempting to turn to ChatGPT or Claude and ask, “Here’s what I have saved so far. Will I be able to retire at 65?” 

Some experts say AI offers a good starting point for answering basic retirement questions.

“I’ll say, ‘Come up with some financial planning ideas or even run a Monte Carlo simulation to see how much I can spend every year,’ and it might not be perfect yet, but it’s starting to be able to get to a place where it’s producing some pretty valuable output that I think will be beneficial to people,” said Luke Delorme, director of financial planning and a Certified Financial Planner at Tableau Wealth in Great Barrington, Massachusetts.

A Monte Carlo simulation is a mathematical model that runs through thousands of potential outcomes for an individual retirement portfolio, factoring in best- and worst-case scenarios, such as the impact of a bear market. The model then projects the likelihood that a person’s retirement savings will last throughout their life.

Such simulations “are the perfect thing for a computer program to do. Eventually, I think that those tools will also become pretty powerful,” Delorme told CBS News.

Yet while generative AI may have value for basic financial planning, experts caution that so-called large language models aren’t ready for prime time when it comes to untangling the complex knot of retirement issues that will face a typical worker, ranging from tax impacts to longevity risk

Noted Boston University economist and retirement expert Laurence Kotlikoff told CBS News that AI may do more harm than good in dispensing retirement advice. Such apps not only struggle to grasp the nuances of Social Security and other retirement issues, but are also based on what he views as flawed traditional financial planning advice, he said.

“It’s being trained on Wall Street’s guidance, and Wall Street’s guidance is all about maintaining and collecting and expanding its assets under management, so that has nothing to do with proper economic-based advice,” said Kotlikoff, who himself has developed a retirement planning tool called MaxiFi.

For instance, AI programs will estimate your retirement savings based on expected longevity, a typical framework for financial planners. Yet retirement planning should be based on a person’s maximum life expectancy to guard against outliving their money, Kotlikoff said. 

He’s also found that AI often provides incorrect information in projecting Social Security scenarios, which can be highly complex given the federal program’s 22,000 pages of rules.

“Then you are off to the races of having the wrong analysis done for you,” Kotlikof said. AI “is like the hottest new thing — you can’t criticize it because otherwise you don’t sound cool or you are defending your job or company.” 

But “I don’t give a s*** about feeling cool — I’m here to make people feel safe,” he added.

Andrew Lo, a finance professor at the MIT Sloan School of Management, told an MIT publication in April that AI struggles with tax optimization, doesn’t understand regulatory nuance and — unlike a human financial adviser — isn’t subject to legal requirements, such as acting in a client’s best interest. 

Lo also stressed that it’s important to ask critical questions when using AI for retirement advice, such as prompting an AI to say where it might be wrong and to list its assumptions and uncertainties.

For instance, consider a hypothetical 50-year-old single woman with an annual income of $70,000. She has a median retirement savings of about $185,000 for someone her age, mostly invested in S&P 500 index funds. She’s contributing 12% of her income to retirement, and at her full retirement age of 67, will receive about $2,400 a month in Social Security benefits. 

CBS News asked Anthropic’s Claude app, OpenAI’s ChatGPT and Perplexity whether the woman can afford to retire comfortably at age 65 and what advice the chatbots would give her. 

Claude and ChatGPT had similar responses: She can retire, but it’ll be tight — and under some circumstances she risks running out of money in retirement. Perplexity was more pessimistic, saying that she likely cannot retire comfortably at 65 without significantly cutting her spending or boosting her income. 

Asked about their assumptions, the AI chatbots noted that they are basing their models on the woman living to age 90, versus a possible maximum lifespan of 100, and that they aren’t modeling exact tax implications. Notably, the apps also revealed that they aren’t assessing the potential cost of long-term care, which can be substantial.

The chatbots then walked back some of their original conclusions, with Claude specifically noting that its original planning horizon was too short. It changed its conclusion to “a tight but doable retirement” to “meaningfully underfunded without course correction.”

When it comes to retirement planning, a bigger issue may be that many people fear investing. That can lead to mistakes, such as keeping savings in cash or CDs, which often have returns lower than inflation, Delorme noted. That means their savings will be eroded over time, heightening the risk of running out of money in retirement.

Delorme thinks AI could help the roughly two-thirds of Americans who don’t work with financial planners begin to understand these concepts. But he also expressed skepticism that AI alone can overcome the anxieties many people have about engaging with financial issues.

“It’s much more behavioral than it is a technical lack of knowledge,” Delorme said. “I don’t know if today that’s going to help people overcome their fears of things, like the fear of investing, which is such a huge obstacle.”

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