Can AI Plan Your Retirement? What It Gets Right, and Where It Goes Wrong

What AI is genuinely good at

Most of what makes retirement planning hard isn't the arithmetic. It's the vocabulary, the way decisions connect, and the fact that nobody explains it at your pace. That part suits a language model well.

• Explaining in plain English, as many times as you need. Ask what the "ACA subsidy cliff" is, then ask again with your own income, then ask what happens if your spouse keeps working one more year. A good explanation that you can interrupt is worth a lot, and you won't feel silly asking the fourth follow-up.
• Connecting decisions that live in different places. A Roth conversion this year raises this year's tax, can cost you health-insurance subsidy before 65, and can raise your Medicare premium two years later. Those three effects are usually explained in three different articles. AI is good at holding them in one answer.
• Turning a worry into a question you can test. "What if one of us needs long-term care?" becomes "run the plan with a care event at 82 and see what happens to the survivor's income." That translation is often the most useful thing in the conversation.
• Summarizing for someone else. Putting your plan into a page your spouse will actually read, or into a list of questions for an advisor.

Where it goes wrong

The failures are specific, and none of them looks like a failure. They all arrive in the same confident tone as the correct answers.

• It can write a number without computing one. A language model produces likely text. Asked for "my odds of not running out of money," it can produce something that reads like a Monte Carlo result without having run a single simulated market. A real success rate means taking your plan through a thousand or so randomized sequences of returns, year by year, with taxes, Social Security and required withdrawals applied in each one. Text prediction doesn't do that, however fluent it sounds.
• The rules change every year, and its training doesn't. Contribution limits, tax brackets, Medicare surcharge tiers and health-subsidy percentages are all reset annually. A model trained on last year's internet can state last year's figure with total confidence. We caught our own AI Advisor doing exactly this once, quoting a prior-year IRS limit as current. The fix was to give it the current figures directly and add a check that fails if an old one comes back.
• It only knows what you typed. A chatbot sees the message in front of it. It doesn't know that your state exempts your pension but not your IRA, that your spouse is six years younger, or that your 401(k) balance includes an old Roth account, unless you say so. It won't always ask.
• It may be working for someone else. Some AI tools sit in front of a product: an annuity, a managed account, an advisory service. That isn't automatically bad, but you should know whether the tool can recommend something its owner sells.

Ask any AI retirement tool one question first: where do your numbers come from?

The design that works: the engine computes, the AI explains

The way to get AI's strengths without its weaknesses is to stop asking it to do the math. A calculation engine, which is ordinary, tested software, computes every figure. The AI is handed those results along with your plan and asked to explain them. If it tells you your success rate is 84%, it's because the engine computed 84%, not because 84% sounded right.

That is how the app is built, so here is what it looks like in practice:

• The engine does the numbers. A seeded Monte Carlo simulation runs your plan through 1,000 market futures, with federal and state income tax computed year by year, Social Security claiming rules, required minimum distributions, Medicare surcharges and pre-65 health-subsidy math. Every figure on screen comes from there.
• The AI Advisor reads those results. It's built on Anthropic's Claude and receives your plan and the engine's computed results, so it answers about your actual numbers rather than a generic 60-year-old.
• It suggests; you decide. When it recommends a change, it shows up as a button. Nothing in your plan changes until you click it. It can also take you straight to the input or card it's talking about.
• It doesn't recommend products. No funds, brokerages, annuities or advisors. It explains principles and trade-offs, and it points to the IRS, the SSA and published research when the question is about the rules.
• It's tested against the live model. A set of 109 test questions checks that it cites the engine's figures, declines product recommendations, and sends you to the right place in the app. Every AI bug we find becomes a permanent test. The details are on our trust page.

None of this makes the AI infallible. Tests catch patterns, not every sentence. The numbers on screen are the source of truth, and the AI's job is to explain them, not to replace them.

A conversation and a full analysis are different tools

A conversation is for questions: "why does my tax jump at 75?", "what if I retire a year earlier?" A deep analysis is one structured read of a whole part of your plan, and there's one for each tab of the app:

• Results — Deep Plan Analysis. The overall read of your plan: what's working, what's at risk, ranked by how much it matters, plus an AI Plan Score.
• Stress Test — Stress Test Synthesis. Which of the bad scenarios actually hurt your plan, and what they have in common.
• Projection — Plan Timeline Synthesis. Your plan year by year, read as phases: the years before Social Security, when required withdrawals start, where the pinch points are.
• Compare — scenario comparison. The real trade-off between the versions of your plan you've saved, and the question that decides between them.
• Progress — Plan Trajectory Synthesis. What has changed across your check-ins, and whether you're drifting.
• Optimize — Optimization Review. Where the real leverage is across the whole plan, in order, and where you're already fine and should leave things alone.

Each one can be added to your PDF report, where it sits next to the numbers it describes. So the report you hand to an advisor or your spouse carries both the projection and a plain-English read of it.

Six questions to ask any AI retirement tool

1. Where do the numbers come from? A calculation engine you can inspect, or the model itself?
2. Does it see my actual plan, or only what I type?
3. Is it current on this year's limits and brackets? Ask it for this year's 401(k) limit and check the answer against the IRS.
4. Can it recommend specific products, and who benefits if it does?
5. What happens to my data? Where it's sent, whether it's stored, whether it's used for anything else.
6. How is it tested? "We use the latest model" is not an answer.

What AI shouldn't do for you

An AI isn't a licensed advisor or a fiduciary, and it doesn't know your health, your family or what you care about leaving behind. It's an excellent way to understand your own plan and to see the trade-offs clearly. For the big decisions that are hard to undo, like taking a pension as a lump sum, choosing when to claim Social Security, or buying an annuity, it's worth having a professional look at your numbers. A good AI tool makes that meeting shorter and better, because you arrive knowing what to ask.

Common questions