About
AI is everywhere, but it’s making IT estates heavier. As data grows, moving it to the cloud - or between clouds - has become slow, expensive, and risky. This is data gravity: big datasets become too heavy to move. At the same time, cloud costs rise, and sovereignty requirements tighten. CIOs now face the same challenge: How do we modernise for AI without losing control of cost, performance, or compliance?
This roundtable brings CIOs together to share practical strategies for keeping data where it lives and moving only the intelligence - models, metadata, and features - to where it creates value.
Every CIO will recognise the shift. Cloud-first made sense when applications were simple, but today:
- Data volumes exploded, and moving them around is now slow and costly.
- AI needs fast access to local data, not distant copies.
- Cloud bills keep growing, often in unpredictable ways.
- Sovereignty rules tighten, making full centralisation harder.
- Vendors still push for “put everything in our cloud,” while CIOs increasingly want:
“The data stays where it is. Only the intelligence moves.”
This session is a peer-to-peer exchange, a practical discussion about what works, where the real thresholds are, and how to build an AI-ready, cloud-right architecture without adding unnecessary complexity.
Key Discussion topics:
- How to deal with data gravity in an AI-driven world
- When to repatriate, refactor, or keep workloads in place
- Keeping data local while moving metadata, features, and models
- FinOps × MLOps: unit metrics that actually change behaviour
- Guardrails for a manageable, flexible multi-cloud setup
- Balancing cost, sovereignty, and AI performance
Leave with actionable insights you can apply the next day.
