AI Retirement Planner: Ask William If You're on Track

Twenty-three percent. In a PensionBee survey of 1,000 US adults who use chatbots for personal finance, that's how many said a chatbot had already given them wrong information about their money. In the same survey, 57% said they would act on chatbot money advice without checking it (PensionBee, September 2026). So if you're shopping for an AI retirement planner, here's the short answer. The chat is the easy part. What counts is what sits under it. A good planner runs your real numbers through a simulation engine and tells you the odds that your money lasts. A general chatbot writes the next sentence that sounds right. Those are two different jobs.

This guide covers how to tell them apart, how to check any AI's answer, and what to do once you have a number.

Why people are turning to AI for retirement questions

It's already common. A Credit Karma poll reported by CNBC found that 66% of Americans who have used generative AI say they've used it for financial advice, and about 85% of those people acted on it (Wealth Professional).

Trust hasn't caught up with use. The Nationwide Retirement Institute found that only 25% of investors trust financial advice from ChatGPT or other AI chatbots. Even so, 31% expect AI to give better advice than a human advisor within five years (401k Specialist).

That split makes sense. You can ask AI a question at 11 p.m. and it won't judge you for it. You just can't always tell whether the answer is right.

What an AI retirement planner should actually do

A useful AI retirement planner does three things:

1. Takes your actual numbers. At minimum, that's your age, what you've saved, and what you spend each month.
2. Runs them through a real model. A single average-return projection doesn't count. You want a simulation that shows how things go when markets go badly, and when they go badly at the worst possible time.
3. Explains the result in plain English. It should answer what you actually asked, like "Am I on track?" or "Can I retire at 62?", and show how it got there.

The third step is where AI earns its place. The first two are where general chatbots get into trouble.

Chatbot vs. dedicated planner

This isn't a knock on chatbots. Aon tested AI on real retirement cases and found material risks: wrong calculations, inconsistent recommendations, and speculation presented as fact (Corporate Adviser). Users on retirement forums report the same thing. They end up checking chatbot "Monte Carlo" results by hand against dedicated simulators (ChooseFI forum).

Monte Carlo, in plain English

"Monte Carlo" sounds technical. The idea is simple.

Don't assume markets return the same average every year. Instead, play out your retirement many times, each with a different mix of good years, bad years, and inflation. Then count how many of those futures end with money still in the account.

If 850 out of 1,000 simulated futures stay funded, your success rate is 85%. That's a probability, not a promise.

Why not use the average? Because averages hide the order of returns. A crash in your first year of retirement does more damage than the same crash fifteen years later, since you're drawing down a smaller pot while it recovers. Simulation shows that risk. An average never will.

That's also how serious research frames retirement income now. Morningstar's 2025 research puts the safe starting withdrawal rate at 3.9%, judged by whether money is still there in 90% of simulated outcomes over a 30-year retirement, not by an average return (Morningstar, The State of Retirement Income 2025, December 2025).

The three risks your plan has to survive

1. Living longer than you planned

According to Social Security Administration planning guidance, about one in three 65-year-olds may live to at least 90 (SSA, Retirement Information for Medicare Beneficiaries, 2026). A plan that stops at 85 quietly bets against a third of retirees.

2. Health care costs

Fidelity estimates that a 65-year-old retiring in 2025 will spend $172,500 on Medicare premiums, deductibles, and prescriptions over retirement. That figure leaves out long-term care entirely (Fidelity Investments, 2025 Retiree Health Care Cost Estimate, July 2025). It's a line item, not a rounding error.

3. Spending too fast

Your withdrawal rate is the share of your savings you take out each year. It's the lever you control most directly. Push it too high and early bad years can sink an otherwise solid plan.

When you compare tools, ask how each one handles all three. Ask how far out it plans, how it models health care, and whether it tests your spending against bad markets or just against the average.

How to check any AI's retirement answer

Whatever tool you use, run these checks before you trust a number:

• Ask the same question twice. If the answer changes much, the math isn't anchored to a model.
• Ask what assumptions it used. Returns, inflation, planning age, health care. If it can't tell you, treat the result as a guess.
• Look for a probability. "You'll have $1.2 million at 80" is one guess. "82% of futures stay funded" is a range of outcomes.
• Change one input. Raise monthly spending a little, or retire a year earlier, and re-run. The result should move in a sensible direction. If it doesn't move, or jumps wildly, be suspicious.
• Check the end date. Make sure the plan runs well past your mid-80s.

What a success rate can't tell you

Monte Carlo is better than a straight-line projection. It still isn't a crystal ball.

Research from Income Lab, written up by Kitces, found that Monte Carlo simulations showed significant error against real-world results. The error was worse when one fixed set of capital market assumptions (the assumed returns and inflation) was used for the whole plan (Kitces). Baird makes a similar point. Don't treat the success percentage as the final word (Baird).

The honest takeaway is to treat your success rate as a dashboard reading, not a verdict. It's most useful for comparing options: retiring at 62 versus 64, or spending a bit more versus a bit less. It's least useful as a single number you check once and forget.

What to do after you see your number

Most tools stop at the score. The useful part comes next.

• If your success rate is high, look at what's behind it. Is it built on spending you'll actually stick to? Does it run long enough?
• If it's lower than you'd like, test the levers one at a time: monthly spending, retirement age, savings. Often a modest change to one of them moves the odds more than you'd expect.
• Plan to adjust spending as you go. Many retirees spend a little less after bad market years and a little more after good ones. A plan you can adjust is sturdier than a fixed one.
• Re-run it regularly. Markets move, health changes, and spending drifts. Kitces recommends revisiting results continually rather than treating them as settled.

When to bring in a human

AI planning software is good at fast, repeatable "what if" questions. Some decisions benefit from a professional who can see your whole situation:

• Managing tax brackets across several account types in retirement
• Deciding when to claim Social Security, especially for married couples
• Choosing between a pension lump sum and monthly payments
• Large or complicated estates, business ownership, or significant long-term care concerns

There's no conflict between the two. You can run your numbers first, then bring better questions to the meeting.

Ask William if you're on track

This is the gap we built Monte Climb to fill. You enter three numbers: your age, what you've saved for retirement, and what you spend each month. We run them through 1,000 simulated futures with our Monte Carlo retirement calculator, the same engine behind the app, and give you one clear answer: how many of those futures stay funded.

Then you can ask William, our AI planner, what that number means. "Am I on track?" "Retire at 62?" "What's a sustainable spend?" Talk to him like you would a friend.

A few details matter here. The plan you build runs to age 95 by default, and you can push it further. The engine charges Medicare premiums and income-based surcharges (higher premiums for higher earners) year by year, instead of using a flat guess. It runs in your browser, and nothing is saved until you say so. It's planning software, not advice.

Fewer than half of workers have done this step. EBRI's 2025 Retirement Confidence Survey found that 48% of workers have never estimated how much monthly income they'll need in retirement (EBRI/Greenwald, Retirement Confidence Survey 2025, Fact Sheet 3). Three numbers is a reasonable place to start.

Show my answer → You can try the full app for 7 days for $1.

Frequently asked questions

What is an AI retirement planner?

It's software that lets you ask retirement questions in plain language, like 'Am I on track?' or 'Can I retire at 62?' The best ones answer by running your actual numbers through a simulation model. A general chatbot answers from text generation alone.

Can I use ChatGPT as a retirement planner?

It can help you learn concepts and come up with questions. Testing by Aon found AI tools made wrong calculations and presented speculation as fact on real retirement cases, though. For the numbers themselves, use a tool built on a real simulation engine, and check any chatbot math against one.

What does a Monte Carlo success rate mean?

It's the share of simulated futures in which your money lasts for the whole plan. If 850 of 1,000 futures stay funded, the success rate is 85%. It's a probability, not a promise. It's most useful for comparing options, not as a one-time verdict.

What is a safe withdrawal rate for retirement?

Morningstar's 2025 research, The State of Retirement Income 2025, puts the safe starting withdrawal rate at 3.9%. That rate held up in 90% of simulated outcomes over a 30-year retirement. Your own safe rate depends on your age, savings, spending, and how long the plan has to last.

Does an AI retirement planner replace a financial advisor?

No. AI planning software is good for fast 'what if' testing. A professional can add value on tax-bracket management, Social Security claiming strategy, pension lump-sum decisions, and complicated estates. Monte Climb describes itself as planning software, not advice.