When Intelligence Becomes Abundant, What Becomes Scarce?

Over the weekend, I listened to a fascinating Moonshots conversation hosted by Peter Diamandis on the accelerating pace of artificial intelligence.

The discussion moved rapidly—from AI solving increasingly difficult scientific and mathematical problems, to the value of proprietary data, rapidly falling costs of intelligence, AI alignment, multi-agent systems, and the possibility that organizations will soon have access to levels of cognitive capability that were unimaginable only a few years ago.

One question stayed with me long after the technology discussion ended:

If intelligence becomes increasingly abundant, what becomes scarce?

After more than 15 years working across organizational change, technology transformation, workforce adoption, and most recently AI transformation, I believe the answer may be less about technology than we think.

What becomes scarce is our ability to adapt, align, discern, imagine, and lead.

Intelligence Is Accelerating. Organizations Must Learn to Absorb It.

Most organizations today are still early in their AI journey.

The conversation is often centered around tools:

But they represent only the first wave of AI transformation.

As AI systems become more capable, less expensive, and increasingly agentic, the bigger question becomes:

How should the organization itself change?

Workflows will change.

Roles will change.

Decision rights will change.

Leadership expectations will change.

Learning models will change.

And perhaps most importantly, the relationship between human intelligence and machine intelligence will change.

That means AI transformation cannot remain simply a technology deployment exercise.

It becomes an organizational transformation challenge.

The Next Bottleneck May Be Human Adaptability

One idea from the Moonshots conversation especially resonated with me: rather than continually being surprised that AI capabilities are advancing faster than expected, leaders should begin planning around capability triggers.

For example:

When AI can reliably perform a particular activity, how will we redesign the workflow?

When autonomous agents can coordinate portions of a business process, what decisions should remain human?

When the cost of intelligence drops dramatically, where could we solve problems that were previously economically impossible?

This requires a different style of transformation leadership.

Traditional transformation programs often operate from relatively fixed roadmaps.

AI-era transformation needs to become more adaptive.

Organizations need the ability to sense, learn, experiment, redesign, and scale continuously.

In other words, the future of change management may be less about managing a defined change and increasingly about building the organizational capability to adapt continuously.

AI Alignment Is Also an Organizational Question

Much of the global AI conversation focuses appropriately on technical alignment: how do we ensure increasingly capable AI systems behave in ways consistent with human intent and safety?

But there is another form of alignment enterprises must address.

Organizational alignment.

Are AI investments aligned with business strategy?

Are incentives aligned with desired behaviors?

Are employees aligned around how AI should be used?

Are decision rights clear?

Are governance and innovation moving together?

Are leaders aligned on what AI should augment, automate, or leave distinctly human?

And perhaps most importantly:

Is AI aligned with the purpose of the organization?

Technology can be extraordinarily capable and still produce poor outcomes if the surrounding organization is misaligned.

The future of AI transformation therefore requires both:

Technical alignment + Human and organizational alignment.

Data May Be the Asset. Human Knowledge Is the Hidden Asset.

Another important theme in the Moonshots conversation was the growing strategic importance of proprietary data.

But organizations contain another extraordinary asset that rarely appears on a balance sheet:

Human knowledge.

Years of customer insight.

Frontline experience.

Institutional memory.

Professional judgment.

Lessons learned from successes and failures.

Much of this knowledge still lives inside people rather than systems.

The AI opportunity is not simply to extract that knowledge.

The opportunity is to create better learning loops between people and machines—while preserving context, judgment, agency, and trust.

That may become one of the most important organizational design questions of the next decade:

What should AI know, what should humans continue to own, and how should intelligence flow between them?

From Productivity to Human Flourishing

Perhaps the most important question is not technological at all.

As machines become capable of performing more cognitive work, people will increasingly ask:

What is my contribution?

What should I learn?

Where do I create value?

What remains uniquely human?

Those questions deserve more attention from transformation leaders.

AI should certainly improve productivity.

But productivity cannot be the only measure of successful transformation.

We should also ask:

Did people become more capable?

Did they gain greater agency?

Did the organization learn faster?

Did teams become more creative?

Did employees have more space for judgment, connection, and meaningful work?

Did technology help the organization solve problems that matter?

For me, this is where People, Planet, and Purpose enter the AI transformation conversation.

People: Are we increasing human capability, dignity, learning, and agency?

Planet: Can abundant intelligence help us solve complex challenges in energy, sustainability, healthcare, and resource utilization?

Purpose: Are we directing increasingly powerful technology toward outcomes worth achieving?

Technology gives us extraordinary acceleration.

Purpose determines the direction.

Leadership determines whether we arrive somewhere worth going.

The Leadership Opportunity

I increasingly believe the next wave of AI transformation will move beyond adoption.

It will be about redesigning work, operating models, leadership systems, learning ecosystems, and organizations around human-AI collaboration.

That creates an enormous opportunity for business and transformation leaders.

The organizations that win may not simply be those with access to the smartest AI.

They may be the organizations most capable of continuously aligning people, technology, strategy, and purpose.

Which brings me back to the question I began with:

When intelligence becomes abundant, what becomes scarce?

My answer is increasingly:

Wisdom. Adaptability. Trust. Imagination. Alignment. Purpose.

And perhaps those are exactly the capabilities leaders should be investing in now.

What would you add to the list?