About

You can have the best dashboards in the world and still get no change in behaviour. That is not a tooling problem. It is an adoption problem. In this session, I’ll share a practical way to think about the adoption gap, the space between access and action. We’ll unpack three common blockers: split ownership between builders and users, familiar habits that override data, and a confidence gap that stops people trusting what they see.

This is for data leaders, BI teams, product owners, and anyone trying to shift data from reporting to real decisions.

Using real examples from enterprise enablement, we’ll look at what works when you connect people properly, build culture through small routines, and design technology that supports curiosity rather than caution. We’ll also cover where AI can reduce friction, and what needs to be true first for AI to strengthen adoption rather than add noise.

Takeaways

• A simple adoption gap model you can reuse, plus the three blockers to look for
• Examples of practical connection mechanisms that support adoption
• Three repeatable culture routines to reinforce adoption
• A grounded view of how AI can support adoption