As artificial intelligence moves from experimentation to deployment, the focus is shifting to where data lives. Microsoft emphasizes an approach that brings AI closer to enterprise data aimed at improving speed, control and real-time decision-making for telecom operators and enterprises.
Microsoft leaders describe data as an emerging economic asset, with organizations seeking to balance innovation with sovereignty and security requirements. The company’s strategy includes a range of deployment models, from public cloud to sovereign environments and localized infrastructure, allowing customers to determine how and where workloads are managed. The approach reflects growing demand for flexibility as regulatory pressures and latency-sensitive use cases increase.
At the same time, the rise of agentic AI is beginning to reshape operations. By combining human oversight with autonomous systems, organizations can respond more quickly while managing costs. With much of enterprise data still unused, bringing AI closer to that data could unlock new efficiencies and operational models across network and enterprise environments.
Anders Wedahl:
We all have different solutions. Everyone has their own thing. They have their own history. And what we are bringing from Microsoft is a 360 view of that data, not just for the network portion of it, but bring it also for the enterprise side of it. To be able to really be agentic and really start thinking of, where do I use humans the best way possible and where can I use the agents in the best way possible? Driving down the cost or reacting much, much quicker.
Meena Gowdar:
Cloud data and AI is now an economic currency for a lot of our customers. They want to be able to protect their data, but still be able to innovate and be part of the global economy. We give those controls for our customers so that they can leverage them, to be able to exercise the level of sovereignty that they need for their workloads.
They can choose to run that in the public cloud, or they can choose to leverage our sovereign private cloud. If this is highly classified, then we give a piece of Azure to be deployed on premises.
Lydia Smyers:
We've worked so, so closely with operators and telcos, to help understand the connection potential and pull it together into a really go to-market asset. And Azure Local is the solution when latency and sovereignty matter most for our customers.
Our foundation for AI development enables a secure environment with this common set of tooling, to create identities for agents in Agent 365. And it provides a real trusted, known environment, for developers and IT professionals across the board.
Marco Rota:
It just gives me access that I need when I need it. By being able to take the goodness of Microsoft security and all of the things that we have baked into Azure, we can now get closer to the enterprise, take advantage of that 90% of enterprise data that's not yet trained. Bring that in with this on ramp, if you will, and also allow for these latency-specific solutions to be queried and worked with efficiently.
Lydia Smyers:
We're talking about providing the local environment for customers and operators, where really sovereignty matters most. And we absolutely think that trust needs to be built in from the start, not bolted on.