Built to Last in an Age of Continuous Change

Editor's Note: This is the second essay in Strategy After Intelligence, a four-part Founding Fuel series by Debleena Majumdar and Arjo Basu exploring how AI is reshaping strategy, governance and leadership. In When More Intelligence Makes Strategy Harder, they examined why strategy may become harder as intelligence becomes more abundant. Here, they turn to a different challenge: how leaders distinguish between what must change and what must endure.

There was a brief period during the pandemic when the future of education appeared almost settled.

Schools and colleges had shut their gates, classrooms had moved onto video calls, and millions of students were attending lessons from home. Every week seemed to bring another funding announcement for an education technology company. User numbers were climbing at extraordinary rates, investors were pouring in capital, and it wasn't difficult to find predictions that traditional educational institutions had reached the beginning of the end.

Imagine sitting inside the strategy meetings of two companies during that period.

The first discussion would have sounded entirely reasonable. “Online education is the only way forward now. Schools and colleges are history.”

In another room at another company, the discussion would go differently: “I say it’s temporary. This closure. Learning won’t happen without the institutions. Let’s continue partnering with them.”

Looking back, the interesting part is that both had access to the same customer data, the same market research and the same growth curves. The difference lay elsewhere.

One strategy was anchored to what had changed. The other was anchored to what it believed would remain true long after the disruption had passed.

That distinction is easy to recognise in hindsight. It is much harder to recognise while living through the disruption itself. It’s a pattern that has repeated itself from railroads and the internet to cryptocurrencies, the metaverse and now artificial intelligence.

The Pattern Beneath Every Disruption

Every generation believes it is living through a uniquely transformative moment. In many ways, it is. New technologies genuinely reshape industries, create new business models and redefine competitive advantage. Yet history suggests that while the technologies are different, the narratives surrounding them are remarkably familiar.

The pattern reflects more about enduring human behaviour than technology. Faced with something genuinely new, we tend to assume that everything else must change with it.

Business history is filled with examples.

Hype and What Survives It

But during every wave of disruption, we tend to confuse the technology with the human need it serves. And that core human need is far less susceptible to change.

How, then, should leaders navigate strategy through such periods of disruption? And what role is AI playing in that equation today?

What Leaders Need to Do

AI is posing two questions for leaders today.

First, almost every company, faced with the rising AI narrative, is trying to develop its own AI strategy. We identified three types of emerging AI organisations in this context in our earlier essay on AI archetypes.

From a strategic lens, this creates a hierarchy of questions leaders need to answer:

a) Is AI creating new sources of competitive advantage?

b) Is AI enabling an entirely new business model?

c) Is AI threatening the company’s growth—or even its existence?

Most companies will find themselves in the first bucket, where AI can create some degree of competitive advantage. The task is to carefully prioritise where to invest without getting caught up in the all-or-nothing rhetoric.

Very few companies will find themselves in the third bucket, despite the fear and FOMO generated by today's AI doomsday predictions.

Some companies, especially new and emerging challengers, may find themselves in the second bucket—using AI-first business models to challenge incumbents and create real impact for customers.

But as companies identify the role AI can play for them, one distinction is critical: having an AI strategy is not a substitute for having strategy.

Having an AI strategy is not a substitute for having strategy.

The second, and deeper, question is what is happening to their core business strategy in this context. For decades, strategy was constrained by the availability of information. Leaders spent months gathering market intelligence, analysing competitors and understanding customers before deciding where to invest.

AI has changed that equation. Information is abundant. Scenarios that once took weeks to develop can now be generated in minutes. Yet this abundance can create an illusion of analysis rather than make strategic choices easier—as we argued in the first essay in this series.

And the reason is quite simple: if technology repeatedly creates narratives that feel permanent, the role of leadership is to distinguish between what deserves a response and what deserves a commitment.

The role of leadership is to distinguish between what deserves a response and what deserves a commitment.

One way to do that today is to separate strategy into two distinct conversations.

The first is about change. Every leadership team needs to understand how technology is reshaping its industry, how customer expectations are evolving, where new competitors are emerging and which capabilities the organisation must build. And indeed many organisations review strategy by asking what has changed since the last planning cycle. New technologies, market shifts and competitive moves dominate the discussion. Those questions remain essential, but they are only half the conversation.

The second is about continuity. It asks a different set of questions. Leaders should spend equal time reviewing what has not changed.

What do we believe will still be true ten years from now?

Which customer needs are fundamental rather than fashionable?

What aspects of our business create value regardless of the technology through which that value is delivered?

Too often, the second part gets missed, leading to hype-driven answers that are no substitute for original and more enduring strategic choices.

An education company may invest heavily in AI tutors, adaptive learning and personalised content while remaining anchored in the belief that parents still value institutions that help children develop confidence, relationships and character. A bank may automate almost every customer interaction while continuing to organise itself around trust. A retailer may embrace every new digital capability without losing sight of convenience, affordability and reliability as the reasons customers return.

Those enduring assumptions become the baseline against which meaningful change can be assessed. Without a baseline, every new technology appears to demand a new strategy.

And therein lies the real strategic challenge of the AI era: to build strategies that are both adaptable and enduring.

In the next essay in this series, we turn to that baseline: what should leaders hold constant when almost everything around them appears to be changing?