Smart Maintenance: Five Trends Shaping the Future

Artificial intelligence is spreading across the maintenance value chain, wireless condition monitoring is gaining momentum, and software systems are becoming increasingly interconnected. At the same time, the retirement of experienced professionals is creating new pressure to modernise maintenance practices.

Knud Lasse Lueth, CEO, and Zeynep Kaman, Analyst, at IoT Analytics, identify several developments that could reshape industrial maintenance in the coming years.

AI moves across the maintenance value chain. Artificial intelligence is no longer confined to predicting equipment failures. It is increasingly being integrated into diagnostics, maintenance recommendations, software interfaces and work order management.

“There’s a lot of AI in a lot of different parts of the value chain,” Lueth observes.

The next step is greater autonomy. AI systems can already provide predictions, recommend corrective actions and explain the reasoning behind their conclusions. However, allowing AI to independently initiate maintenance activities remains a different matter.

According to Lueth, human approval is still generally required before AI-generated recommendations become actual work orders. Trust, safety and operational responsibility remain important barriers to fully autonomous maintenance.

Wireless sensors gain momentum. One of the fastest-growing segments in smart maintenance is wireless condition monitoring. According to IoT Analytics’ market observations, some wireless sensor providers are reporting annual growth exceeding 100 %.

The appeal is straightforward. Wireless sensors can be mounted on existing equipment without extensive cabling, making condition monitoring easier and often less expensive to deploy.

Kaman points out that technology itself has also matured. Connectivity has improved, and wireless devices can now capture more detailed vibration data, including low- and high-frequency measurements. For maintenance organisations, this creates opportunities to extend condition monitoring to assets that previously lacked continuous monitoring.

Predictive becomes prescriptive. Predictive maintenance answers the question of when equipment might fail. Prescriptive maintenance takes the next step by recommending what should be done about it.

Instead of simply warning that a component may fail within ten days, a prescriptive system can suggest corrective measures and potentially identify the underlying cause. This distinction matters because detecting a problem does not automatically tell a maintenance team how to solve it. Lueth stresses, however, that most industrial maintenance is still preventive or condition based.

Predictive solutions are expanding, while prescriptive maintenance remains at an earlier stage of adoption. The direction is nevertheless clear: from identifying potential failures towards supporting decisions on how to prevent them.

Closing the loop. Another significant development is the convergence of previously separate maintenance systems.

Condition monitoring platforms, asset performance management solutions and computerised maintenance management systems (CMMS) are becoming more closely integrated. The objective is to connect the entire process, from detecting an anomaly and recommending corrective action to creating a work order, completing the repair and recording the outcome.

Kaman emphasises that prescriptive analytics and system integration reinforce each other. Feedback from technicians can improve future alerts and recommendations, creating a continuous learning process.

Rather than operating as isolated tools, these technologies are gradually moving towards a more unified smart maintenance environment.

The skills shortage accelerates digitalisation. Perhaps the most pressing challenge is not technological at all.

Lueth identifies the retirement of experienced maintenance professionals as one of the industry’s biggest challenges. As skilled workers leave, companies risk losing decades of practical knowledge.

Digital technologies offer ways to preserve that expertise. Recording experienced technicians’ work through video, audio and other documentation can create searchable knowledge resources for future employees. Meanwhile, maintenance software is becoming more intuitive and mobile-first. Technicians can access work orders, equipment information and diagnostic data directly through tablets or smartphones.

Kaman highlights the growing importance of simple interfaces and clear instructions that help less experienced employees work effectively.

For maintenance organisations, the message is increasingly urgent: digitalisation is not simply about improving efficiency. It is also about ensuring that critical knowledge and skills remain available when experienced employees retire.

Text: Mia Heiskanen