There was a time when one of the biggest obstacles to making a good decision was simply getting enough information.

You needed access to information and the expertise to locate and make sense of it.

Sometimes you even needed what we used to call an “expert” – someone who had spent years mastering a certain skill.

That constraint is disappearing remarkably quickly.

Today, you can give AI details of your income, assets, expenditure, age, retirement goals and risk tolerance and ask it to help you think through your financial future.

Within seconds, it can produce projections, compare strategies, identify considerations you may have missed and construct something that looks remarkably like a financial plan.

And this isn’t some distant hypothetical.

Vanguard now describes AI as capable of analysing enormous datasets, optimising portfolios and updating financial plans in real time. The analytical work that once consumed enormous amounts of professional time is becoming increasingly automated.

That sounds like extraordinarily good news.

And in many ways, it is.

But it also exposes something we’ve misunderstood about difficult decisions for a very long time.

We Thought We Had an Information Problem

Think about how we usually respond when we’re uncertain about an important decision.

We research.

We read another article.

We watch another video.

We ask another expert.

We compare another option.

The assumption underneath all of this is perfectly reasonable:-

If I can just get enough information, the right answer will eventually become obvious.

For most of human history, that wasn’t an entirely bad assumption.

Information was scarce.

Expertise was expensive.

Analysis took time.

AI has changed all three.

Which creates an interesting test.

If lack of information were the primary reason intelligent people struggled to make good decisions, AI should be rapidly eliminating the problem.

Instead, many of us now have something quite different.

More answers than we know what to do with.

AI Has Made Answers Cheap

Ask AI whether you should put more money into equities.

You’ll get a perfectly plausible analysis.

Ask whether property should form part of your retirement strategy.

Another plausible analysis.

Ask about bonds, private markets, annuities, dividend investing, entrepreneurship or maintaining some form of earned income beyond traditional retirement.

Again, you can receive a sophisticated answer in seconds.

Then change one assumption.

Or ask the question differently.

Or introduce another objective.

Suddenly, another course of action may look equally reasonable.

This isn’t necessarily a failure of AI.

It’s the nature of the decision.

Because many important decisions don’t have a single objectively correct answer waiting to be discovered.

They involve trade-offs.

Risk.

Incomplete information.

Competing objectives.

And a future nobody can know with certainty.

AI can help us analyse those things.

It cannot make the uncertainty disappear.

More Information Doesn’t Necessarily Create More Certainty

This is where something counterintuitive happens.

Once we have access to almost unlimited analysis, we don’t necessarily make decisions more easily.

Sometimes decisions (in particular decisive ones) become much more difficult.

Every answer creates another question.

Every strategy has a counterargument.

Every opportunity has a risk.

And every confident prediction can be matched by someone—or increasingly, something—capable of constructing an equally convincing argument for the opposite conclusion.

So we keep looking.

Not because we lack information anymore.

Because we’re hoping the next piece of information will give us something information cannot provide…

certainty.

That’s a very different problem.

The Bottleneck Has Moved

For decades, knowledge was enormously valuable because acquiring it was difficult.

AI is rapidly changing the economics of knowledge.

That doesn’t make knowledge worthless. Far from it.

But it does change where the constraint lies.

When information becomes abundant, the scarce resource becomes the ability to decide what matters.

To distinguish evidence from prediction.

To recognise which assumptions should apply.

To understand the downside if you’re wrong.

To weigh competing objectives.

And eventually, to make a decision without pretending that things are no longer uncertain.

In other words:

While AI has made information cheaper. It has made good judgement more valuable.

Vanguard makes a related distinction in its work on AI and financial advice.

It argues that data gathering, portfolio construction and financial-planning simulations are increasingly susceptible to automation, while interpretation, behavioural guidance and understanding what actually matters to someone remain much more dependent on human judgement.

In my view, the implications go well beyond financial advice.

The Same Problem Appears Everywhere

Consider almost any important decision.

Should I leave my job?

Should we buy this business?

Should I invest in this opportunity?

Should I retire now or work another five years?

Should I start something of my own?

Should we enter this market?

AI can make you dramatically better informed before making any of those decisions.

That’s valuable.

But eventually you encounter the same boundary.

The available evidence ends.

The future begins.

And someone still has to decide.

Intelligence and Judgement Are Not the Same Thing

We tend to associate good decisions with intelligence.

Understandably so.

But intelligence gives us an unusual problem.

The better we are at analysis, the better we can become at constructing arguments for multiple possibilities.

We can see more variables.

More risks.

More scenarios.

More second-order consequences.

AI magnifies that capability enormously.

Give it one course of action and ask for the strongest argument against it.

Then ask it to rebut that argument.

Then ask for three alternative strategies.

Then ask what you’ve overlooked.

You could continue almost indefinitely.

At some point, more analysis stops reducing uncertainty.

It merely describes the uncertainty in greater detail.

That’s when judgement begins.

Good Decisions Have Never Required Certainty

This distinction matters enormously in finance because financial decisions often involve consequences that won’t become clear for years.

A good outcome doesn’t necessarily prove that the decision was good.

A bad outcome doesn’t necessarily prove that it was bad.

You can make a sensible decision based on the information available today and still experience an unfavourable result.

You can also make a reckless decision and get lucky.

That’s why I think one of the most useful disciplines is to judge a decision based on what was knowable at the time you made it, rather than rewriting the quality of the decision after you discover the outcome.

AI can increase what the span of what is knowable.

That is a tremendous advantage.

But it cannot turn the unknowable future into the knowable.

And we shouldn’t ask it to.

The Skill We May Need Most in the AI Age

Much of the discussion about artificial intelligence focuses on which human skills AI will replace.

I suspect an equally interesting question is which skills become more valuable because AI exists.

Judgement may be one of them.

Not intuition masquerading as judgement.

Not confidence.

Not prediction.

The disciplined ability to gather the available evidence, understand the assumptions, assess the downside, recognise what remains unknowable and still make a considered decision.

Because the strange consequence of having nearly unlimited access to answers is that answers themselves become less valuable.

The ability to know what to do with them becomes more valuable.

AI can give us more information than any generation in history has possessed.

It can help us model possibilities our grandparents couldn’t have calculated in a lifetime.

It can challenge our assumptions and expose things we’ve overlooked.

We should use it.

But perhaps the greatest mistake we could make is assuming that better answers eliminate the need to become better decision-makers.

They don’t.

They make it more important.

Because AI may eventually make information almost unlimited.

Our ability to act intelligently when certainty is unavailable will remain scarce.

For most of our working lives, Generation X was given a fairly simple set of instructions about retirement.

Work hard.

Build a career.

Save part of what you earn.

Invest it.

Let compound returns do their work.

And, eventually, accumulate enough that you can stop working.

It wasn’t bad advice.

But as more of us enter our fifties and retirement stops being something that happens to other people, there’s an uncomfortable question worth asking:

What if saving enough isn’t the only problem we need to solve?

For much of the last century, retirement planning rested on what was often called the “three-legged stool.”

One leg was your pension. One was government retirement benefits. The third was your own savings.

Together, they were supposed to provide the income you needed after your salary stopped.

But for many Gen Xers, one of those legs has largely disappeared.

Defined-benefit pensions have become increasingly rare, replaced by retirement arrangements that put much more responsibility on us to accumulate and invest our own money.

So we’ve responded in the most obvious way.

We’ve tried to make the savings leg bigger.

Save more.

Invest more.

Make additional contributions.

Spend less now so we’ll have more later.

Again, none of this is bad advice.

Time Changes the Mathematics

But there’s a problem that becomes increasingly difficult to ignore as you get older.

Time changes the mathematics.

If you discover at 30 that you’re a long way behind where you’d like to be at retirement, you have decades to do something about it.

Even relatively modest additional savings have years to compound.

Discover the same gap at 50 and the available solutions begin to narrow.

You can save considerably more.

You can try to earn higher investment returns, usually by accepting greater risk.

You can reduce the lifestyle you’re planning for.

You can postpone retirement.

Or you can reconsider one of the assumptions sitting quietly underneath the entire calculation.

That the day you retire from your career is also the day your ability to produce income falls to zero.

The Assumption Hidden in Our Retirement Plans

I’ve come to think this is one of the strangest assumptions in conventional retirement planning.

For thirty or forty years, our greatest financial asset has been our ability to produce income.

We apply our knowledge, experience, relationships and judgment to something valuable, and someone pays us for doing so.

We use part of that income to accumulate assets — shares, funds, property, retirement accounts — so that one day, when the salary stops, those assets can produce the income we need instead.

And that’s where an odd assumption creeps into the conventional retirement model.

We assume that when the salary stops, our ability to produce income stops with it.

At some predetermined age, the model effectively assigns our future income-producing capacity a value of zero and expects the assets we’ve accumulated to take over the entire job.

There were good reasons for thinking this way when retirement commonly meant leaving a physically demanding job after forty years of work.

I’m less convinced it makes sense for a modern executive in their fifties.

What Happens to 30 Years of Experience?

Someone at that stage of life could plausibly have another thirty years of productive life ahead of them.

More importantly, they possess something their 25-year-old self didn’t.

Decades of experience.

Accumulated knowledge.

Professional judgment.

Relationships.

Credibility.

Skills that may have taken half a lifetime to acquire.

Yet when we calculate whether we’re “ready” for retirement, we routinely assign almost no economic value to any of it.

We ask:

How large is your portfolio?

Perhaps we should also be asking:

What is your capacity to continue creating income?

Working in Retirement Isn’t the Same as Having to Work

That doesn’t mean working until you die.

Quite the opposite.

There is an enormous difference between working in retirement and having to work in retirement.

The first can be a choice.

The second is an obligation.

And I suspect this distinction matters particularly to people who have spent decades building successful careers.

Most of the executives I know don’t dream of reaching a particular birthday and becoming permanently unproductive.

They still want to build things. Solve problems. Help people. Learn. Teach. Contribute.

What they’re tired of isn’t necessarily work.

It’s everything that came attached to the particular form of work they’ve been doing.

The meetings.

The commute.

The politics.

The targets.

The hierarchy.

The calendar that somehow belongs to everybody except them.

Perhaps, then, the objective of retirement planning shouldn’t necessarily be to accumulate a magical sum of money that means we never have to earn another dollar.

Perhaps the objective is to reach the point where earning money becomes optional — and happens on our terms.

It sounds like a small distinction.

Financially, it can be enormous.

A Small Amount of Income Can Change the Equation

Suppose you believe you’ll need $100,000 a year to live the life you want after leaving your career.

If you assume you’ll never earn another dollar, your investments have to provide the entire $100,000.

But suppose you can create $20,000 or $30,000 a year doing something you enjoy, on a schedule you control.

The amount your investments have to provide changes.

If you can create $50,000, it changes again.

And if you enjoy what you’re doing and choose to continue doing it, the boundary between “working” and “retirement” begins to look rather arbitrary anyway.

Suddenly the question isn’t simply:

How large a pile of money can I accumulate before I stop working?

It’s:

How many different ways can I create the life I want after I leave my career?

That’s a very different question.

It’s a question about optionality.

And perhaps that’s what the traditional retirement model is missing.

Perhaps We Need a Fourth Leg

If the old retirement model had three legs — pension, government benefits and personal savings — perhaps the modern version needs a fourth.

An income-producing asset you control.

That doesn’t necessarily mean another job.

It could be consulting.

Intellectual property.

A small business.

A digital business.

Royalties.

A portfolio of income-producing assets.

Or something else entirely.

Don’t Start With the Vehicle

I’m deliberately not prescribing the vehicle, because I think that’s where another mistake begins.

The moment someone decides they need another source of income, the obvious question is:

What should I do?

And the internet has no shortage of answers.

Property.

Consulting.

E-commerce.

Affiliate marketing.

Courses.

Trading.

Franchises.

Whatever technology happens to be transforming the world at the time.

There will always be another opportunity.

And there will always be someone completely convinced that this one is the answer.

At 50, a Bad Decision Costs More Than Money

But if you’re in your fifties, choosing the wrong one can be considerably more expensive than it was when you were 25.

Not simply because you can lose money.

You can make more money.

The scarcer resource is time.

Evidence Before Commitment

That’s why I don’t think the answer to discovering a retirement gap is to panic and start a “side hustle.”

I’d begin somewhere else entirely.

I’d begin with evidence.

Is there a genuine problem I can solve?

Are there identifiable people who want that problem solved?

Will any of them actually pay to solve it?

Can I test that proposition without risking a significant amount of capital?

Can I gather evidence that it works before committing years of my life to it?

Those aren’t particularly exciting questions.

But they’re considerably more useful than asking which business opportunity happens to be popular right now.

Because the objective isn’t to find the next big thing.

It’s to create another option.

Maybe We’ve Been Using the Wrong Scoreboard

For decades, we’ve been shown a retirement scoreboard with essentially one number on it.

How much have you accumulated?

If the number is large enough, you’re doing well.

If it isn’t, you’ve fallen behind.

And if you reach your fifties without the retirement portfolio you thought you would have, it’s very easy to look backwards.

I should have started earlier.

I should have saved more.

I shouldn’t have bought that house.

I should have made different investments.

Perhaps some of those things are true.

Thinking about them now is also largely useless.

You cannot go back and change what you saved twenty years ago.

You can’t know what markets will return over the next twenty.

You can’t know what inflation will be.

You can’t know what interest rates will be.

You can’t know precisely what governments will do with taxes, pensions or retirement benefits.

And you certainly can’t know whether the investment everybody is excited about today will still look clever a decade from now.

Those things sit on the other side of an uncomfortable boundary between what we can control and what we can’t.

You Can’t Change the Past. You Can Still Build the Future.

But you can still decide what you build from here.

You can build skills.

You can build relationships.

You can build assets.

You can build the capacity to produce income independently of an employer.

And, crucially, you can test those things while you still have an income, rather than discovering whether they work only after you desperately need them to.

Maybe Retirement Requires Two Kinds of Assets

Perhaps that’s the part of the retirement conversation Generation X has been missing.

We spent decades being told to prepare for the day when our salaries stopped by building a sufficiently large pile of money.

Maybe we should have been preparing in two ways.

Build assets that can produce income.

And preserve the ability to produce income ourselves.

The objective isn’t to work forever.

It isn’t even necessarily to earn more.

It’s to arrive at the next stage of life with as many choices as possible.

To be able to work because the work is interesting, rather than because the mortgage payment is due.

To be able to walk away from something that no longer suits you without wondering whether doing so will destroy your financial future.

To be able to use thirty years of accumulated experience rather than treating it as an asset that mysteriously expires on your retirement date.

And, perhaps most importantly, to retain some control over a future in which so much else cannot be predicted.

A Better Question to Ask About Retirement

So I’m no longer convinced that the most important retirement question for someone in their forties or fifties is:

“Have I saved enough?”

It’s an important question.

But I’d put another one beside it.

“What can I build now that gives me more choices later?”

Because ultimately, the retirement I want isn’t one in which I never work again.

It’s one in which whether I work, what I work on, who I work with, and when I work are decisions I still get to make.