Everyone is talking about AI agents, but most organisations are still working out how to create real business value from them and, more importantly, how to operate them safely and reliably at scale. Over the past 18 months, I've worked with some of Microsoft's largest enterprise customers across engineering, construction, energy and professional services as they move from AI experimentation into production. The conversations are no longer about chatbots and copilots—they're increasingly about autonomous workflows, governed AI agents, and systems that interact with critical business processes. In this session, I'll share what customers are actually building today, where they're seeing value, and the operational challenges they're encountering along the way. We'll explore why reliability, observability, governance and operational readiness are becoming as important as the AI models themselves. Topics covered include: The shift from copilots to agentic AI Real customer use cases and lessons learned Common governance and operational challenges What SRE and platform teams need to prepare for How organisations can scale AI safely without introducing new operational risk This isn't a session about AI hype—it's a practical look at what is happening on the ground today and what it means for the next generation of enterprise workloads.
Seema Sharma is a Senior Specialist at Microsoft focused on Azure, Data and AI transformation across Microsoft's largest enterprise customers in the UK. She works with organisations to modernise data platforms, adopt Microsoft Fabric, implement AI solutions, and establish the governance and operating models required to run these technologies at scale. Her recent work has centred on helping enterprises move from AI pilots to production-ready agentic AI solutions that deliver measurable business outcomes.
