Videos
Burnt Oak Partners on Pragmatic AI, Sovereignty, and the Future Telecom Ecosystem
Insights
- AI adoption is shifting from experimentation to practical, scalable implementations focused on delivering measurable business value.
- Digital sovereignty and resilience are becoming strategic priorities as organizations evaluate long-term AI and cloud dependencies.
- Future success will depend on flexible architectures and strong ecosystems that allow organizations to adapt as AI technologies evolve.
At MWC 2026, Mats Hultin of Burnt Oak Partners discusses how the industry's AI conversation is maturing from broad enthusiasm to a focus on real-world business outcomes. He explains that organizations are increasingly looking for scalable AI solutions that can deliver measurable value while addressing growing concerns around sovereignty, resilience, and long-term technology dependence. The conversation explores the challenges of building the infrastructure and business models required to support AI at scale, as well as the importance of collaboration across telcos, cloud providers, system integrators, and AI vendors. Hultin also argues that because AI technologies evolve so rapidly, organizations should focus less on individual applications and more on building flexible, modular architectures that can adapt over time. Looking ahead, he believes AI will become a pervasive capability embedded across every aspect of the business, much like IT is today.
Mats Hultin:
The big themes this year, AI, of course, it's everywhere in all different shapes. So what I like about that is that the discussion is getting more from general AI to much, much more pragmatic, scalable AI that really delivers value.
Another big theme that comes into AI and a lot of other cloud is also sovereignty. How dependent are we? Do we have a resilient set up in our different solutions? And then of course, it's about continue to scale the digitalization with AI. A lot of agentic AI and how to really drive that into your business.
I think there are strategic, tactical operational realities and you need to embrace all of them. I think personally that a couple of years from now AI, it will be everywhere. So you will talk about AI like we talk about IT today. It's embedded everywhere.
There's a lot of challenges in the infrastructure layer. First of all, no one really wants to pay for it. So the business model, how should the business model look like? To make AI really deliver value, business value, you need to really figure out how it can help you in your business model strategically.
I think system integrators, cloud providers, AI providers and telcos need to find their ecosystems of how to transform both the enterprise business and everything around it.
Investing in AI today is something we all need to do, but it is complex. Things become legacy very quickly. Don't focus on the applications, focus on the content. We will need to have an architecture that enables that change and that plugability of components. And it's absolutely true for AI as well. And the plugability of that architecture, I think will be very important.
