Many organisations are rushing to deploy AI into maintenance and asset management while still operating with fragmented data, disconnected systems, inconsistent asset structures, and reactive cultures. The result is often more noise, more dashboards, and greater confusion rather than better decisions.

Yet the barriers to successful AI adoption are not only technical. Trust, organisational culture, decision ownership, workforce anxiety, poor cross-functional alignment, and weak change management capability frequently undermine adoption long before technical limitations appear.

Drawing on practical asset management experience and current research into AI adoption barriers, this session explores how lifecycle thinking, contextualised information, and organisational readiness must be established before AI can deliver sustainable operational value.