An Exclusive Interview with Ula Nairne, Global Vice President of Media & Entertainment at Stelia

Artificial intelligence may be transforming businesses, but Ula Nairne believes the organisations that thrive won’t simply be the ones with the smartest technology; they’ll be the ones with the smartest leadership.

As Global Vice President of Media & Entertainment at Stelia, Nairne sits at the intersection of artificial intelligence, commercial strategy and global innovation, advising enterprises on how to turn emerging technologies into meaningful business transformation. Having worked with some of the world’s most influential brands, including Samsung, LEGO, L’Oréal, Sony Pictures and The Wall Street Journal, she has spent her career helping leaders navigate complexity, embrace innovation and build for what’s next.

In this exclusive conversation with Glazia, she shares why AI is redefining leadership, why trust and judgment will become even more valuable in an automated world, and how organisations can move beyond adopting technology to building intelligence that lasts.

Glazia: You’ve noted that many leaders use AI simply to speed up existing tasks rather than rethink their entire business. What major opportunities are executives missing when they treat AI as a productivity booster instead of a true game-changer? 

Ula Nairne: They’re missing the opportunity to reinvent what their business actually is.

Look, productivity gains are real and necessary. Everyone is under pressure; budgets, boards, and teams are all pushing for better tools. So, starting with faster workflows and reducing manual work makes sense. It’s the obvious first step. But it isn’t transformation.

The real question is this: if intelligence can now flow through an entire organisation, how should the business operate differently?

There’s a strange paradox with AI. It’s overhyped in the short term and underestimated over the long term. Some companies expect magic tomorrow, while others still don’t recognise how profoundly it could reshape everything over the next decade.

That’s where leadership becomes critical. You can’t simply layer AI on top of outdated structures and expect a new organisation to emerge. You have to rethink the foundations: data, governance, workflows, risk, infrastructure, brand, customer experience, and decision-making.

The danger is that many companies are building what I call an AI “Frankenstack”: a collection of disconnected tools, impressive pilots, and clever demonstrations stitched together without a solid foundation. There’s no governance, no cost control, and no clear data strategy.

Speed matters, but speed without a foundation is fragile. I often compare it to The Three Little Pigs. If you build your AI house out of straw because you’re obsessed with speed, it may look impressive during a pilot. But when the big bad wolf of scale, regulation, cost, and risk arrives, it won’t stand.

In my work with global enterprises, this is the shift I help companies make: moving from AI experimentation and basic optimisation to intelligent AI infrastructure. The goal isn’t to test another shiny tool. It’s to build the foundations that allow intelligence to operate safely across the business, supported by the right governance, data strategy, security, IP protection, cost control, and scalability.

In media, entertainment, and consumer brands, it’s no longer just about producing more content at a lower cost. It’s about transforming audience behaviour; what people watch, trust, share, and buy into meaningful intelligence. We’re moving from simply producing content to creating experiences that respond to people in real time.

AI gives us speed and scale. Culture, taste, and judgment give it meaning. Otherwise, we’re simply creating more noise, faster.

For me, AI doesn’t just improve productivity. It changes power: who understands customers better, who acts on data faster, who distributes ideas more intelligently, and who transforms attention into value.

That’s the real game-changer. AI moves companies from being process-led to intelligence-led. Once intelligence operates across the business, leadership has to move beyond adopting tools and start defining how humans and AI work together.

G: As companies transition from simple digital tools to fully autonomous AI systems, how do you see the day-to-day role of business leaders changing to manage this new “non-human” workforce?

Ula Nairne: Leadership is becoming less about having all the answers and more about knowing where human judgment still matters most.

AI can analyse, recommend, and even act at incredible speed. But it doesn’t understand the consequences the way we do. It doesn’t understand reputation, emotion, loyalty, or trust. That’s still our territory.

The strongest leaders I’ve seen develop a calmer, sharper kind of confidence. They ask the right questions: What data is driving this? What happens if it goes wrong? Are we actually becoming smarter, or just faster?

It’s about ambition with restraint. Move quickly, but don’t hand over responsibility.

For me, that’s the new leadership muscle.

And that becomes even more important as intelligence moves beyond software into physical environments, where humans, robots, and autonomous systems must work side by side.

G: With the future of work blending physical and digital human-robot collaboration, how can leaders balance the push for ultimate efficiency with the need to keep their human teams feeling safe, motivated, and valued?

UN: Leaders need to be honest: AI and robotics transformation isn’t just a technology shift. It’s a human shift.

I learned that early through robotics. I worked with U.S. robotics companies, orchestrating fleets of robots from different manufacturers and systems, which was revolutionary at the time. I also worked with organisations training robots and robotic dogs in digital twin environments before deploying them in the real world.

It sounds like science fiction: robotic dogs, virtual worlds, and fleets of autonomous machines, but the biggest lesson I learned was deeply human.

When we designed environments where robots, software, and people worked together, the machines weren’t always the hardest part. If the system is designed well, robots are remarkably predictable.

Humans are the wild card, in the best possible way. We improvise, create, feel, get tired, and bring both chaos and brilliance. People need to be designed into these systems from the beginning, not added at the end.

Physical safety matters, of course, but so does making people feel respected and valued.

If you only talk about efficiency, people hear, “We’re replacing you.” If you talk about removing repetitive work so humans can focus on what we do best judgment, creativity, relationships, and taste the entire conversation changes.

That word, taste, matters.

In a world where AI can make everything faster, cheaper, and more polished, the things that become truly valuable are the ones that remain deeply human.

Creativity isn’t just production. It’s timing. It’s judgment. It’s understanding what will make people feel something. Machines can support that. They cannot replace it.

Efficiency creates scale. Trust creates adoption. Great leaders need both.

But trust also depends on ownership of the data, context, and intelligence these systems are built upon.

G: You recently shared that owning your own data is far more important than how sophisticated an AI model is. How should modern leaders shift their strategies so they’re building something they actually own rather than simply renting intelligence from technology giants? 

UN: The model isn’t the moat. The moat is what your organisation knows that no one else does: your customer relationships, your context, and your brand intelligence.

Most companies will have access to the same foundation models. The competitive edge comes from proprietary data and how effectively you activate it.

For media enterprises, sports organisations and consumer brands, the most valuable intelligence often sits within the relationship they have with their audience: what people watch, love, skip, share and buy. What makes them trust a brand? That information becomes incredibly valuable when it’s organised, protected, and activated properly.

The question every board should be asking is:

“What intelligence do we own, and how do we make it usable in a secure, governed, and scalable way?”

Especially in media and consumer businesses, a deep understanding of local culture, behaviour and trust is incredibly powerful.

Trust is going to become everything.

When anything can be generated or faked with ease, people need to know what’s real and who stands behind it. For brands, media organisations and public institutions, that’s not a minor detail. It goes directly to reputation, credibility, and public trust.

Because ultimately, if you don’t own the data, the context, or the customer relationship, you’re not really building intelligence.

You’re renting it.

It’s also why I care deeply about digital sovereignty and strategic technology partnerships, particularly in emerging markets. It’s one of the key themes I’ll be speaking about at the African Ambassadors’ Economic Forum in Washington, D.C.

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