AI is moving quickly, but many organisations are finding it harder than expected to turn early ideas into something that works day to day.
In most cases, the challenge isn’t the AI itself. It’s the data behind it. If that isn’t in the right place, projects stall and results are inconsistent.
This session focuses on getting your data foundation ready, and what changes when that foundation is in place. The discussion will centre around three key areas:
Getting your data ready for AI
What does “AI-ready” look like in practice? We’ll look at the common issues that hold teams back, from unclear definitions to gaps in quality, and what good looks like when data is reliable, secure and well managed.
Understanding different approaches
We’ll explore the difference between chat-based AI tools and more structured, process-driven approaches, and when each makes sense.
Putting it into practice
We’ll walk through how organisations are using these approaches to improve processes and reduce manual effort, with the right checks in place.
