Despite years of investment, most organisations remain stuck in an endless cycle of AI pilots that never deliver operational value. The numbers are sobering: 76% of AI initiatives fail to achieve expected returns, manufacturing failure rates sit at 76.4%, and only around 11% of organisations have genuinely scaled AI into production. Leadership ambition continues to outpace workforce readiness, with AI skills scoring the lowest of any readiness dimension at 2.69 out of 5.

This workshop is for maintenance and reliability managers tired of proofs of concept that work in isolation but evaporate the moment they meet real operational systems and messy data. We'll examine why pilots fail at scale, what high-performing organisations do differently, and how to build the foundational capabilities - clean data, system integration, workforce literacy, and governance - that determine whether AI delivers value or becomes another sunk cost. We'll also tackle the more provocative opportunity: rather than using AI to optimise existing processes for marginal 10% gains, how do you reinvent maintenance entirely to be dynamic, responsive, and tied to actual operating conditions?

• A diagnostic framework for assessing whether your organisation is genuinely AI-ready or simply AI-curious
• Strategies for closing the gap between leadership ambition and workforce capability
• A governance approach addressing transparency, accountability, and the boundaries between AI recommendations and human judgement in safety-critical environments
• A reinvention-first methodology: what would maintenance look like with unlimited resources and perfect information, and where can AI realistically bridge that gap?

Bring your current AI initiatives, your scepticism, and your hardest integration problems - we'll work through them together.