We often believe that incumbents fail because they’re too slow.

It’s a convenient explanation.

It guarantees consensus theater.

Yet, it doesn’t quite explain why fast-moving incumbents fail.

The ones who do everything right by the textbook - the ones that both explore and exploit - the ones you talk about in HBS case studies.

Adobe checks all those boxes - one of the rare incumbents that made the leap to the cloud without imploding. In the early 2010s, it pulled off a full business model reboot, turning its one-time software licenses into recurring subscriptions. It rebuilt its products for continuous delivery and taught a generation of analysts to worship ARR (annual recurring revenue). By the mid-2010s, Adobe was thriving. The Creative Cloud became a case study in bold reinvention - the story of a company that understood the difference between digitizing its products and digitizing its economics.

The incumbent wasn’t slow.

If anything, the incumbent had moved fast and gotten it right.

And yet, as I write in Figma - the untold story, Adobe failed to counter Figma’s growing dominance.

Why exactly do the fast incumbents fail?

Below, I unpack 15 counterintuitive lessons on this topic, based on a podcast discussion I had with Aidan McCullen on The Innovation Show.

The ideas I cover apply every bit as well to the dilemmas that firms face today with AI adoption and covers:

Why productivity isn’t the real prize

Why expertise can become a liability

Why ‘learning AI’, while important, is not at all sufficient.

How power shifts not just between companies but inside careers, as algorithms strip away agency from some roles while new value accrues to others.

Read this as both a map of corporate disruption and a set of ideas to challenge how you think about disrupting your own career path.

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The slow incumbent fallacy is the belief that incumbents fail because they move too slowly.

Well, here’s the thing:

Incumbents often don’t fail because they move too slowly.

They fail because they move fast in the wrong direction.

The myth of slowness is comforting because it preserves the illusion of control.

It lets everyone nod along in boardrooms and MBA classrooms: just be faster, more agile, more experimental. It helps you sell Lean Startup and Agile bootcamps into organizations as some form of silver bullet.

But speed within the old frame is still the old frame.

The fallacy persists because it panders to existing hierarchies and treats failure as a matter of efficiency rather than imagination.

But architectural revolutions, like the cloud, platforms, and now AI, are not efficiency games. They are system redesign games.

There are three broad reasons incumbents love the slow incumbent fallacy, particularly when it’s sold to them in the form of workshops with a lot of post-its stuck to ‘innovation room’ walls.

Architectural change is harder to perceive than operational change

Operational change shows up on dashboards and KPIs. Architectural change is not quite as visible because it makes older metrics completely irrelevant.

Managers can see faster workflows, but not the invisible shift in the system’s underlying logic.

That invisibility makes architecture both the slowest-moving variable and the most dangerous to ignore.

More on this topic:

Execution bias amplifies path depandance

Speed is good if you’re headed in the right direction.

But if your expertise, incentives, and infrastructure are all tuned to preserve yesterday’s logic, every process, skill, and metric reinforces the old logic and makes you progressively blinder to the new one.

Movement is misunderstood as progress

Motion is visible, quantifiable, and consensus-friendly.

It produces the illusion of progress without confronting the existential dread of redesign.

Architecture, by contrast, requires leaders to admit they don’t fully understand the game board.

Measuring motion soothes anxiety; re-architecting threatens identity.

That’s why organizations fetishize execution while avoiding the deeper work of redefining which execution matters.

Let’s unpack this further using the Adobe vs Figma case.

For starters, here’s the video with Aidan exploring the case:

Now digging into the ideas in here:

How architectural shifts determine incumbent fortunes

How value migration determines incumbent fortunes

The shift from execution to governance

How moving fast in the wrong is worse than not moving at all

How to reimagine your career to avoid the incumbent trap

And finally, a. diagnostic to apply this to your business or your career.

Read more