Artificial intelligence is advancing faster than most organizations. Companies are buying new tools, while processes often remain unchanged. Daniel Fazlić, moderator of the NT Business track Frontier Company: From AI Experiments to Competitive Advantage, argues that the biggest challenge is not technology itself, but the willingness of organizations to rethink how they work, make decisions and create value.

Daniel Fazlić is a consultant in digital transformation, digital product development and AI adoption. Previously, he served as Director of Digital Development at Bloomberg Adria, where he worked at the intersection of editorial teams, technology, data and product development across multiple markets. His work focuses on measurable business outcomes and the practical application of technology. He is also a pilot, which has given him a unique perspective on technology, complex systems and decision-making under uncertainty.

What do you see as the biggest challenge behind the slow adoption of AI and the transformation towards future-ready organizations?

Technology is often the easiest part of the transformation. Buying a new tool is usually only a few clicks away. AI models improve every month, while organizations change their processes, responsibilities and decision-making structures much more slowly. That gap is expensive. Many projects end up frozen or perceived as “useless.”

I often compare it to a device you bought because you were convinced it would change your life, only to find it sitting unused in a drawer.

What mistakes are companies making?

Many organizations simply add new tools to existing processes because they are attracted by the latest shiny thing. If you take a poor or outdated process and add AI, you mostly end up with a faster poor process.

Real transformation starts when organizations ask why they do things the way they do, which steps can be removed, which can be automated, and where people create the greatest value. And believe me, people will remain essential to that process.

What is the biggest risk?

The biggest risk is waiting.

A company can continue using old ways of working for quite some time before realizing that the gap between itself and the best performers has become too large.

As I often say: if you wait too long, the runway becomes too short and the landing becomes very hard.

AI gives us an opportunity to eliminate repetitive, low-value work and allow people to focus more on analysis, creativity, relationships and decision-making.

How do the most successful organizations approach this transformation?

They start with something concrete.

They select a business problem or process, look at the data, assign ownership and define success metrics in advance.

When we were implementing an automated and personalized homepage at Delo, we measured click-through rates, time spent on page and editorial workload reduction. Technology was only a means to achieve those outcomes.

The same applies to marketing, sales, analytics and customer support.

You often emphasize the importance of the MVP approach. Why?

Organizations should not wait for a perfect final product.

They should test an MVP, a minimum viable product, improve it continuously and learn from it. That means accepting mistakes and understanding why things did not work.

Those lessons are incredibly valuable.

It is also important to understand that AI is much bigger than ChatGPT. The greatest value will emerge when data, automation, business rules and generative AI become part of a single integrated process.

How will this affect jobs?

Today’s static job descriptions will gradually disappear.

People will increasingly become analysts, strategists, creators and technology users at the same time. Organizations that help employees develop these capabilities will gain a significant advantage.

Personally, I often learn things that I never expected I would need. AI helps me do that in a way that matches my learning style, my pace and my schedule.

What would you ask Andreas Ekström?

His concept of “organic intelligence” fascinates me.

I would ask him:

If the best AI tools become available to almost every company, which uniquely human capability will become the rarest and therefore the most valuable competitive advantage?

His observation that organizations may eventually wake up and realize they no longer understand the world around them also resonates strongly with me.

We have already seen this happen in media and many other industries. Companies noticed each individual technological shift, yet still failed to adapt as a whole.

AI is accelerating that cycle dramatically.

The real problem begins when we try to interpret new technologies through the logic of an old business model.