AI is not a goal, but an accelerator of better maintenance
The maintenance sector is in the midst of a major digital transformation. In a conversation with NVDO Chairman Ronald Wever, it becomes clear that artificial intelligence is no longer a vision of the future, but a development that is already making a difference today.
"What we see,” he explains, "is that AI helps us finally make the shift from reactive to predictive maintenance. That may well be the biggest breakthrough.”
Where maintenance traditionally relied on inspections and fixed intervals, AI now makes it possible to determine exactly when intervention is needed based on data.
"We can detect failures earlier, reduce downtime, and extend the lifespan of assets. That not only improves efficiency, but also safety and sustainability.”
From data to value
According to Wever, the real power of AI does not lie in the technology itself, but in how organizations use it.
"AI can analyze vast amounts of data and recognize patterns that are simply invisible to humans. But value only emerges when you translate those insights into better decisions.”
He adds that he hopes to see exactly this in practice during Maintenance NEXT in April 2027.
Applications are already widespread, from predictive maintenance and visual inspections using image recognition to optimizing energy consumption and even supporting procurement processes. Still, he warns against an overly instrumental approach.
"We need to move away from the idea that AI is a goal in itself. It is a means to make processes smarter and more effective.”
Not a replacement, but an enhancement of craftsmanship
A common concern is that AI might replace traditional craftsmanship. Wever is clear on this, partly based on findings from the NVDO Maintenance Compass:
"AI is not a replacement for technicians or maintenance professionals. It is an addition.”
He emphasizes that human expertise remains essential.
"AI can predict and analyze, but it cannot tighten a bolt or repair an installation. True craftsmanship remains physical and context-driven.”
What does change is the role of professionals.
"They have better information at their disposal and can therefore work smarter. That ultimately makes the profession more interesting and more valuable.”
Challenges and conditions
According to Wever, implementing AI is not a guaranteed success. Data quality, integration into existing systems, and new regulations are key points of attention.
"Without good data, there is no good AI. And organizations must be willing to invest in knowledge, infrastructure, and new ways of working.”
The labor market also plays a role.
"AI will not solve staff shortages, but it can increase the impact of existing teams. Think of support in training and knowledge transfer, exactly where NVDO excels.”
Step by step forward
The most important lesson from the Maintenance Compass, according to Wever, is that organizations should start small.
"Start with concrete problems and use the data you already have. Build from there.”
He concludes:
"Everyone will start working with AI. The difference will not be whether you do it, but how you do it.”