There is no shortage of opinions about artificial intelligence (AI). Depending on who you talk to, it is either the biggest strategic opportunity ever or an overhyped technology that will disappoint once the excitement fades. As through my work, I am lucky enough to have regular contact with different executive boards and management teams, I am fully convinced the truth lies somewhere in between. In other words: leadership behavior, not technology, ultimately determines which side an organization ends up on.

A conversation that stayed with me

Not long ago, I spoke with a C‑level executive from one of our clients - someone who has seen multiple technology waves come and go. What struck me was not his extraordinary excitement about AI, but the calm seriousness with which he described their approach. Their board, he explained, had made a clear decision: AI literacy was no longer optional. For all.

Every board member now has very concrete expectations written directly into their KPIs. Not abstract ambitions, but practical responsibilities - understanding how AI agents can support the areas they oversee, identifying processes that can be optimized, and regularly challenging their teams on where AI could realistically improve outcomes. In short, the board itself is expected to practice what it governs.

His reasoning was simple and, frankly, refreshing: “We cannot expect the organization to develop real AI capability if the leadership treats it as someone else’s topic.”

That conversation stayed with me because it captured something many companies are still missing. Competitive advantage in the coming years will not come from having access to AI - it will come from knowing how to use it well, responsibly and pragmatically.

From fascination to usefulness

One of the biggest shifts executives need to make is moving from fascination to usefulness. Early AI discussions are often dominated by what is possible. More mature conversations focus on what is helpful.

In practice, the initiatives that generate trust and momentum tend to be surprisingly down‑to‑earth. AI that helps people prepare better, respond faster, understand context or reduce repetitive effort often delivers more measurable value than ambitious end‑to‑end automation promises.

I have seen organizations achieve real gains simply by using AI to summarize complex information flows or assist employees in navigating internal knowledge. These are not initiatives that usually make headlines—but they make work noticeably easier, and that matters.

On the other hand, I have also seen bold AI projects stall because they were detached from operational reality. Poor data foundations, unclear ownership or underestimated regulatory complexity quickly erode confidence. The lesson is not to avoid ambition, but to earn it gradually.

Adoption is the real battleground

One uncomfortable truth about AI is that value only appears when people actually use it. If AI sits in a separate tool, outside daily workflows, adoption declines fast. The most effective use cases are those that disappear into the background and simply make existing processes smoother.

This is where leadership judgment becomes critical. Choosing where to embed AI, how much autonomy to grant it, and how to define human accountability are management decisions, not technical ones. Organizations that address these questions early tend to scale their initiatives with far less friction.

Good governance plays a quiet but decisive role here. Clear boundaries around acceptable use, data sensitivity and decision authority do not slow teams down. On the contrary, they create confidence—confidence to experiment, to deploy and to improve.

A modern Darwinian reality

There is a phrase I hear more and more often from executives, sometimes half‑jokingly: those who learn to work with AI will survive; those who don’t will struggle. It does sound like a modern, corporate version of Darwin—but there is a real insight behind it.

This is not about replacing people with machines. It is about amplifying human capability. Leaders who understand how AI can support judgment, not replace it, will make better decisions faster. Teams that learn how to delegate routine cognitive work to AI will have more space for creativity and critical thinking.

And, perhaps most importantly, organizations whose leadership genuinely understands these dynamics will be better positioned to differentiate themselves—not just on efficiency, but on adaptability.

Experience over theory

Working within a global IT services and advisory environment has reinforced this view for me. The organizations that succeed with AI are rarely those with the most sophisticated models. They are the ones that treat AI as a long‑term capability, built step by step, grounded in business reality and supported by leadership example.

They start small, observe carefully, adjust often and scale deliberately. They remain curious, but disciplined. And they regularly ask themselves a simple question: Is this making our people better at what they do?

Reflection for leaders

If there is one takeaway I would offer to fellow executives, it is this: AI strategy starts with leadership behaviour. Tools matter, data matters, governance matters—but mindset matters most.

AI will not automatically deliver value. People will. And those who invest in their own practical understanding of AI—at board level as well as across management—will be far better equipped to turn opportunity into lasting advantage.

Instead of a disclaimer: I used AI tools as a practical aid while shaping this article, but the reflections above are my own—grounded in personal experience working with executive teams across industries. The tone, conclusions and examples are intentionally personal, because this is how I, a bit old-fashioned as I am, believe AI should be used: not as a replacement, but as meaningful support for leaders. And personal note is essential flavour in business, not only in this article.

Author bio

Matej Kurent is Managing Director of SoftwareOne in Slovenia, working closely with executives on cloud transformation, governance and the practical adoption of AI. He focuses on bridging strategy and execution, helping organizations translate technology potential into real business outcomes. As part of a global organization, he brings international experience with a strong local, hands‑on perspective. He is also an LJUBLJANA MBA alumni (3rd generation), he continues to give back as part of the LJUBLJANA MBA Alumni Board, supporting a strong, future-focused alumni network.