The Adoption Gap: A 4-Part Special Series — Trailer

Welcome to the Trend Detection podcast, brought to you by Senseye
Predictive Maintenance – which gives you visibility and insights
into all your assets, from single machines to full plants to help
you reduce downtime, increase knowledge sharing and accelerate
digital transformation across your organization.In this special
four-part series, we tackle the uncomfortable truth behind most
predictive maintenance programmes: the technology works, it's the
adoption that doesn't. Across four episodes, we hear from four
experts, each with a different perspective on why industrial AI
projects stall after the pilot, and what the organisations that
succeed actually do differently.What you'll learn in this
series:Why organisational readiness (not algorithm accuracy) is the
real bottleneck for predictive maintenance, and what "being ready"
actually looks like in practiceHow change management should be
designed into a project from day one, not bolted on when adoption
starts to stallThe most common patterns behind failed industrial AI
projects, from pilot traps and misaligned KPIs to trust gaps that
never get closedWhy asset selection and internal champions make or
break the first 90 days after go-live, and what happens when either
one is wrongHow to build momentum from early wins, turning
resistors into advocates and scaling from one line to an entire
plantThe real KPIs that drive renewal and expansion and why
downtime avoided is only part of the pictureYou can find out more
about how Senseye Predictive Maintenance can reduce unplanned
downtime and contribute towards improved sustainability within your
manufacturing plants, by visiting:
www.siemens.com/senseye-predictive-maintenance