What AI Hasn’t Changed About Transformation—And Why That Matters More Than Ever

Over the past year, I’ve had at least as many conversations about AI than I’ve had about strategy, operations, and culture combined. It’s the topic on every agenda, and with good reason. The pace is staggering and the potential very real.

And yet, something feels off.

In many organizations, AI is treated as a standalone tool, a technical upgrade, or even worse, a productivity hack. It’s added to the existing organization like a new layer of software, neatly boxed into innovation sprints, pilot projects, or IT-led initiatives.

What’s often missing is something more fundamental: the realization that AI doesn’t eliminate the need for strategy. It makes the need for real strategy even greater.

AI is not a shortcut around transformation. It’s an accelerant of everything that makes transformation hard and necessary.

With Industry-Wide AI Adoption, there is a Real Risk of Doing Nothing. But Equally of Doing Too Much of the Wrong Thing.

Frequently the AI journey follows a familiar course: curiosity, experimentation, disillusionment. Organizations move fast with granting LLM access, co-pilots, and selective agents, and still end up stuck after a while.

Why?

Because the hard part of AI isn’t technical. It’s strategic. And cultural.

What AI really exposes is the lack of alignment, coherence, and courage at the heart of too many transformation efforts. The temptation is to move quickly. But in doing so, many skip the work that actually matters.

I’ve seen teams with dozens of use cases and no unifying direction. I’ve seen executive committees excited by demos but uncertain about trade-offs. I’ve seen transformation programs grind to a halt—not because of bad tech, but because the people weren’t brought along.

AI doesn’t remove the need for strategy. It multiplies it.

What (Still) Matters Most

Here’s the paradox: Some of the most powerful principles of strategic transformation, principles that have been around for years, are now more important than ever.

They’re not new. But they’ve never been more relevant.

In my personal experience, these four stand out:

• Think from the future back

• Act in two horizons: perform and transform

• Put culture at the heart of strategy

• Work with the organization—not on it

Let’s unpack them.

1. Think from the Future Back

Many leadership teams begin their AI strategy process by mapping out every department’s current pain points or improvement potentials. The result? A long list of incremental fixes and automation ideas - but no vision.

So let's flip that script: What would winning look like in your industry once it’s reshaped by AI? That question reframes the conversation from problem-solving to ambition-setting. It opens up space to think about new customer experiences, reimagined value creation, and entirely different business models.

Future-back thinking is not about predicting the future. It’s about starting from a bold ambition and building a bridge to it—step by step.

2. Act in Two Horizons

AI forces leaders to live in two realities. In one, you’re trying to make the current business more resilient—streamlining operations, improving margin, upgrading decision-making. In the other, you’re building something new—offering different services, entering new ecosystems, inventing the next version of your business.

There is true cost to ignoring either horizon. Over-focusing on performance can lead to missed opportunities. Over-prioritizing reinvention can destabilize the core.

The companies that get it right run both tracks at once—with different metrics, mindsets, and teams. AI isn’t either/or. It’s both/and. But it only works when each horizon has clarity and accountability.

3. Put Culture at the Heart

Here’s a hard truth: You can’t implement AI in a culture of fear. And yet many organizations try.

They roll out AI tools without addressing what people are really worried about—being replaced, being left behind, being exposed. The result is resistance, skepticism, and shallow adoption.

What becomes clear is that AI strategy must start with emotional reality. Do your teams feel safe to experiment? Do your leaders know how to talk about change—not just push it?

One client began by surveying their teams not on readiness, but on belief: Do you believe we can change? That surfaced more insight than any diagnostic. And it gave the leadership team a starting point for real engagement.

Culture is not a soft topic. It’s the system architecture of transformation.

4. Work With the Organization—Not On It

Transformation doesn’t happen because a slide says it should. It happens because people choose to make it real.

That choice only happens when teams are involved in the process—not just as recipients, but as co-creators. Especially with AI, where the learning curve is steep and the implications are personal, transformation needs to be something the organization builds together.

I’ve seen it firsthand: cross-functional teams running through "divergent thinking" processes, brining in new ideas from inside and outside the organization, prototyping use cases, and getting leadership to wrestle with new governance models. These moments don’t just create better solutions—they build belief.

You can’t delegate ownership. You have to invite it.

So What’s Actually Changed?

If these principles aren’t new, what’s different?

Three things: speed, saturation, and stakes.

• Speed: AI is moving faster than any prior wave of innovation. Strategy cycles can’t take 12 months anymore.

• Saturation: It’s not just a tech topic. AI touches every function, every role, every customer interaction.

• Stakes: The gap between companies that move with clarity—and those that scramble—is growing wider by the month.

In this new environment, transformation isn’t just about direction. It’s about momentum.

Which is why we need to bring back the fundamentals—with more discipline, more urgency, and more humanity.

The Work Ahead

If you’re leading through this shift, ask yourself:

• Do we have a shared ambition for what winning looks like in an AI-enabled world?

• Are we running both performance and transformation with intention?

• Are we surfacing the real cultural barriers—or just managing resistance?

• Are we co-creating strategy with the organization—or imposing it from above?

If not, you may be implementing AI - but you’re not yet transforming with it.

Let’s change that. And let’s do it together.

I’d love to hear how others are navigating these questions. What’s working in your context? What’s getting in the way? Feel free to share your reflections.