AI Is Accelerating Activity. Is It Improving Thinking?

Artificial intelligence is creating more analysis, more dashboards and more activity than ever before in manufacturing.

What it is not automatically creating is better thinking.

In many organizations, leaders are busier, better-informed and more digitally equipped than at any point in their careers, yet decision quality is not improving at the same rate.

That disconnect is not a technology problem, but rather an intentionality problem.

We Know How to Be Disciplined

Manufacturing leaders understand discipline. We define processes. We establish standards. We measure outcomes. We expect alignment between what we say, what we do and what we can prove.

At the enterprise level, rigor is familiar.

But one layer down, at the level of mid-level leadership development, that same discipline is not always applied with equal clarity.

Consider something simple: a trade show.

Travel is approved. Time away from operations is invested. Meetings are scheduled. Panels are attended.

But before arriving, how often are these questions made explicit?

• What capability gap are we trying to close?
• What assumption are we testing?
• What decision should this inform?
• What would success look like when we return?

Without declared intent, the event becomes merely motion: action without accomplishment. With intent, it becomes structured learning. The same is true for how leaders grow.

Engagement Is Sustained by Growth

In earlier discussions about AI transformation, we emphasized trust, transparency and psychological safety in the workplace. Those remain essential.  However, leaders’ engagement also depends on growth.

In my work with organizations, and now in the classroom, I see a consistent pattern. High performers rarely disengage because they lack work. They disengage when their thinking stops expanding.

AI intensifies that pressure. Data becomes probabilistic, and recommendations become model-driven. In reality, decisions require broader interpretation of the data and stronger judgment.

If leaders are not intentionally expanding their perspective with ongoing learning and by seeking out new ideas and concepts to challenge their thinking, they default to familiar mental models. Teams sense it, debate quietly softens and overall initiative-taking slows.

There is a familiar executive concern: “What if we invest in leadership development and people leave?”

The better question, building off the sentiments of Peter Drucker, is: “What if we don’t invest, and they stay?”

In an AI-enabled environment, underdeveloped leadership is not neutral. It shapes how technology is interpreted, how risk is assessed and how opportunity is pursued.

Capability is not a perk. It is a performance safeguard.

AI and the Illusion of Progress

AI gives us unprecedented access to information, but it does not automatically deepen judgment.

Dashboards surface trends, and algorithms personalize content. Generative tools draft plausible conclusions. Today, leaders can move faster, but not necessarily think deeper.

Without deliberate exposure to disconfirming perspectives, confirmation bias strengthens quietly. Confidence rises, but accuracy does not always follow.

The result can look like progress through more analysis, more output, more activity—without a corresponding improvement in decision quality.

Intentional learning is the counterweight, but it needs to be intentional and cannot remain informal.

Put Intentional Growth Inside Leader Standard Work

Operational excellence depends on leader standard work, the few critical actions leaders commit to doing consistently, so that continuous improvement becomes routine rather than episodic. Daily management routines, review cadences and structured accountability prevent drift.

If decision quality increasingly depends on how leaders interpret AI-assisted inputs, then cognitive growth deserves similar structure.

Intentional learning should not be left to spare time or personal preference. Rather, it should be embedded in how leaders operate.

Practically, that means:

• Identifying, each quarter, a capability gap aligned to business priorities.
• Selecting inputs deliberately—whether through reading, benchmarking, structured dialogue or targeted training.
• Creating space to reflect and translate insight into operational implications.
• Asking explicitly: What decision or practice changed because of this learning?

Most performance reviews evaluate results and observable behaviors. Few ask how a leader’s thinking has evolved.

In stable environments, experience compounds naturally. In AI-enabled environments, experience can calcify just as easily as it compounds.

Making learning visible shifts it from optional to expected.

A Simple Illustration

At an individual level, the discipline can be straightforward.

Instead of asking, “What should I read next?” a leader asks, “What dimension of my thinking is underdeveloped?”

Instead of consuming broadly, they select material aligned to that gap. They capture reflections. They revisit themes. They ask how their decisions shift as a result.

The reading itself is not the objective. The alignment between intent and outcome is.

The same logic applies to conferences, certifications and AI tools. Every investment of time and attention should have a declared purpose and a visible impact.

Activity is easy to measure. Capability and results are not, unless we design for them.

From Motion to Measurable Growth

In manufacturing, we would never invest in automation without defining expected performance improvement. Leadership development deserves the same clarity.

AI will continue to accelerate activity across our organizations. The competitive advantage will not belong to those who simply adopt new tools. Instead, it will belong to those who deliberately strengthen how their leaders think.

Organizations that treat learning as incidental will see widening variability in decision quality and engagement. Those that embed intentional growth into leader standard work will compound insight the way they compound capital.

• Engagement is sustained by growth.
• Growth is sustained by intentionality.
• Intentionality must be designed, not assumed.

In the AI era, that is not an abstract idea. It is disciplined leadership.