Lead­er­ship in the Age of AI: The 3 Phases – Curi­os­ity, Use­ful­ness & Nor­m­al­isa­tion

Once a month, researchers at Copenhagen Business School provide Børsen readers with a current and research-based perspective on the challenges facing leaders.

This time, Professor of Market Strategy and Business Development Thomas Ritter from CBS and Associate Professor Carsten Lund Pedersen from IT University of Copenhagen share their insights on how organisations should navigate through three phases — curiosity, value creation, and normalisation — when something new, such as artificial intelligence, emerges.

At its core, leadership is about enabling a group of people to succeed at a shared task. Good leadership, therefore, must be evaluated by whether goals are achieved to a meaningful degree—and whether people are satisfied with their contributions. This remains true even when the world around us shifts. New technologies, new rules of the game—or even no rules at all—require that leaders continuously revisit and adapt their decisions.

When a new technology like artificial intelligence (AI) emerges, organisations move through three critical phases: curiosity, usefulness, and normalisation. This framework has become evident through our research on the implementation of AI and digital transformation initiatives.

Phase 1: Curiosity

First comes curiosity. What is this technology? What can it do? What are the opportunities—and the risks?

In this initial phase, it is crucial that both leaders and employees remain open-minded and willing to learn, while also unlearning outdated assumptions. Experimentation, exploration, and the willingness to fail fast—and learn quickly—are essential.

Many will recognise this phase from the recent AI boom: it’s characterised by energy, excitement, hype, and often the sense of an impending revolution.

Phase 2: Usefulness

But curiosity alone is not enough. Eventually, the new technology must prove its value. It must improve how the organisation works and generate measurable returns.

This is the second phase: usefulness.
Here, the focus shifts to strategy, value creation, business model transformation, and realignment of ecosystems to support improved outcomes. The central questions become: How does this technology fit into the business? Can it enhance processes, business models, or partnerships?
While change is still necessary in this phase, the leadership task shifts. Now it’s about ensuring that what gets built is solid, sustainable, and makes sense—essentially the opposite of the high-risk experimentation of the curiosity phase.

Many organisations currently find themselves in this stage with AI, asking: can we take this technology out of the lab and into operations?
This is the point at which AI’s strategic value must be proven. Development continues, but leaders must now decide what remains in the sandbox and what should deliver tangible value in day-to-day business.

Phase 3: Normalisation

Eventually, what was once new becomes normal. When a technology delivers value but fades into the background, normalisation has occurred.

Consider autocorrect—most people don’t even think about it as AI anymore. We become annoyed when autofill doesn’t work in an online form or when a passport scanner fails at airport self-service.
For younger generations, using AI tools like ChatGPT isn’t just normal—it’s abnormal not to use them. They have already moved through the curiosity and usefulness stages.

Different phases require different leadership styles

As a leader, you must be able to recognise which phase your organisation is in—and adapt your leadership style accordingly.
Some leaders thrive in the curiosity phase: the tech enthusiasts, trend-watchers, and the anxious—those afraid of being left behind.
During the usefulness phase, the “value hunters” take over: pragmatic leaders focused on finding effective applications and embedding them throughout the organisation.
In the normalisation phase, the ideal leaders are the “natural adopters”—those who seamlessly integrate new tools into business as usual.

But the most effective leaders are those who can shift their style across phases. These “navigators” know when it’s time to explore, when to execute a strategy, and when to simply ensure things run smoothly.

The usefulness phase of AI is underway

Over the past decade, our research into the commercial side of digital transformation—from leveraging big data and customer data to implementing AI—has revealed the recurring pattern of these three phases, along with the challenges of transitioning between them.

That is why we wrote a book on value-enabling Artificial Intelligence (available in Danish). It focuses on how to make AI useful—and how to create real value from it. Because only then will technology investments make sense—not just now, but in the long haul.