For many people in maintenance, AI agents sounds impossible — something that will never work in practice. And to be fair, if you expect AI to fully automate your plant and replace people, then no, that will likely not happen. And more importantly: we don’t think anyone should want that.
Where AI can make a huge difference is in cutting out the wasted time that technical professionals deal with every day. Searching for documents, digging for information, chasing details that were forgotten, fixing miscommunications, or redoing steps because a process wasn’t followed — all that time loss is exactly where AI can support.
Today: How we already use AI agents for maintenance
In our maintenance clarity programs we already work with AI Agents. What used to be handled with logic and experience, AI now helps scale up. For example, in backlog cleanup we used to handle 30–40% of the noise with smart data logic. Today, even with backlogs of 7,000 work orders, our AI Agents can fully classify and define them.
Tomorrow: How we will use AI agents for maintenance
We’re training AI Agents to support planners, schedulers, engineers, and preparers in daily work. That means helping a scheduler use resources more effectively, reminding an engineer when a PM interval needs to be revised, or nudging a work preparer about missing drawings or suppliers. Even small reminders like “you forgot this step” already prevent major issues.
In the long run, we see AI Agents becoming as standard as a basic training for a work preparer: a strong foundation that can be adapted to any site.
How it fits into our programs
Every program we run — from backlog cleanup to scheduling clarity — is built with AI Agents in mind. The data is cleaned, the context is added, and the process is structured in a way that the agents can learn from. Step by step, the foundation gets stronger, and the AI Agents become more capable of supporting your team.