The problem isn't making a five-year plan, it's assuming the fifth year is as certain as the first.

Recently, I came across an image in the Harvard Business Review that was published years ago. It was taken from Amy Webb's article, "How to Do Strategic Planning Like a Futurist."

The image conveyed a simple but powerful message: as we move towards the future, time increases, but the data, evidence, and certainty we have decrease.

In the immediate context, we can talk about tactics. A little further on, strategy comes into play. Further on, there's vision, and beyond that, there are assumptions about how the system might evolve.

I believe that the approach Webb put forward in 2019 is even more important today. Because back then, the main problem with strategic planning was uncertainty. Today, uncertainty is compounded by the speed of change. AI, geopolitical tensions, new regulations, shifts in customer behavior, and technological breakthroughs can change the rules of the game for an industry several times in a five-year period. Harvard Business Review

However, when you look at the strategy documents of many companies, you see an interesting paradox.

The revenue target for 2027 is set.

2028 EBITDA is known.

The number of countries we will be in by 2029 is known.

The market share for 2030 is set.

Sometimes the numbers are even precise, down to the decimal place.

As we move towards the future, uncertainty increases, but the certainty in the PowerPoint presentation increases rather than decreases.

Perhaps the problem isn't making a five-year plan. The problem is planning the fifth year as if it were as certain as the first.

For a long time, the basic assumption in the world of strategy was roughly this: if we analyze the future well enough, make accurate predictions, and create a good plan, we can manage the organization according to that plan.

Therefore, the process generally worked like this:

Analyze → Plan → Execute → Review.

Once a year, a strategy was developed, budgets were allocated, goals were assigned, and the organization would implement it. The following year, they would reconvene.

However, the fundamental challenge facing strategy today is no longer simply "making the right plan."

Being able to recognize when the assumptions that formed the basis of the plan become invalid.

Boston Consulting Group's AI-first strategy study, published in 2026, clearly illustrates this transformation. According to BCG, the main potential of AI in the strategy function is not to speed up presentation preparation or analysis; it is to change the way companies develop strategies. "Always-on strategy," a constantly updated flow of information, and more dynamic resource allocation are important components of this. BCG also notes that much of the work traditionally done by strategists is open to automation or augmentation by AI. BCG Global

An important distinction needs to be made at this point.

Dynamic strategy doesn't mean changing strategy every week.

A company constantly changing direction is not agility, but often strategic indecision.

I define this as Stable Direction + Dynamic Path .

Your direction may be relatively stable.

Your North Star may not be easily replaced.

But the assumptions you make, the methods you use, your resource allocation, and your strategic choices to achieve that goal must be adaptable.

In other words:

The horizon can stay fixed. The assumptions cannot be made.

For example, a company might aim to be one of the top three players in a particular area of Europe by 2030. This strategic direction could remain valid for several years.

However, which products to bring, which markets to enter first, which technologies to use, which competencies to develop internally, and which to purchase externally can be constantly re-evaluated.

Because strategy consists of choices , not goals.

This is where artificial intelligence begins to play a much more interesting role.

McKinsey says AI can be used in different roles in the strategy process, such as researcher, interpreter, thought partner, simulator, and communicator. In particular, the simulation of different scenarios and the monitoring of early market signals are poised to change the way strategy is developed. McKinsey & Company

In my opinion, the next step is even more important.

AI will not only be a tool that performs analysis faster.

AI will be part of the strategy's learning mechanism.

Therefore, I believe the traditional strategy cycle also needs to change.

Sense → Interpret → Choose → Execute → Learn → Reallocate → Choose Again.

First we see the signals in the environment.

Then we make sense of what these things mean to us.

We are developing strategic options.

We are making a choice.

We are implementing it.

We learn from the results.

We are redistributing our resources.

And we reconsider our decision if necessary.

This means a great deal.

Because in the past, one of the biggest problems in strategic planning was a lack of information. Today, however, we are increasingly moving towards a different problem: an excess of information.

Thousands of signals.

Hundreds of trends.

Opponent moves.

Customer reviews.

Macroeconomic indicators.

Technological advancements.

New initiatives.

Patents.

Regulations.

Social media.

AI can read all of this.

But the fundamental question a leader must answer remains the same:

"Which of these is really important to us?"

Therefore, I believe that the task of a future strategist will not be limited to simply preparing plans.

Yesterday's strategist was making plans.

Tomorrow's strategist will manage an options portfolio.

Because in an uncertain world, one of the most valuable strategic assets is not just having the right position, but the capacity to act when necessary.

Optionality.

Having a choice.

A technology you may not be using yet, but could use if needed.

An alternative supplier.

An option to enter a new market.

A startup worth buying.

A diverse, cultivated talent pool.

A new business model.

Therefore, in the future of strategic planning, assumptions will matter more than predictions, options more than definitive decisions, and triggers more than annual reviews.

We need to determine in advance which indicator should alert us when one of our assumptions changes.

For example:

"What will we do if Chinese competitors' price advantage exceeds 20%?"

"If AI halves product development time in our industry, how will we transform our organization?"

"If customers' purchasing behavior shifts from distributors to direct digital, which of our channels will we downsize?"

"If the new regulation changes the economics of our current business model, what alternative model will we switch to?"

This is where the strategy begins to cease being just a document.

Strategy is becoming a living decision-making system.

I call this an AI-Powered Dynamic Strategy .

And for me, the difference lies in this sentence:

Planning organizes the chosen future.

Strategy chooses which future we will pursue.

AI-powered dynamic strategy makes this selection continuously smarter.

The word "continuously" is important here.

Because AI won't determine the future.

He won't tell us what 2030 will be.

It will not give the exact date of a geopolitical crisis.

He won't be able to perfectly predict what decision an opponent will make.

But it can enable us to recognize signals of change earlier, test our assumptions faster, evaluate more scenarios, and better simulate the potential consequences of our decisions.

Therefore, in the age of AI, competitive advantage may not belong to the company that predicts the future most accurately.

It will belong to the company that realizes its mistake earliest and learns the fastest.

Therefore, I believe the questions we ask at strategy meetings in the coming years also need to change.

The question, "What is our goal for 2030?", is of course still important.

But now we need to add some other questions:

On what assumptions did we base this strategy?

Which of these assumptions have begun to change?

What early warning signs are we monitoring?

Which alternative futures did we consider?

Which strategic options are we keeping open?

And perhaps most importantly:

What development would force us to reconsider the strategy we currently believe to be correct?

Because the strategic organization of the future may not be the one with the best plan.

It could be the organization with the best learning system.

Strategy used to be a plan.

Then it became a choice.

In the AI age, strategy becomes a learning system.

Now, let me leave you with just one question for your own company:

If which three assumptions in your 2030 strategy were to change today, your strategy would also have to change?

The answer to this question is probably more valuable than many of the KPIs in your strategic plan.