Despite major technological advances, predictive maintenance is struggling to become an industry standard.
Its success depends less on algorithms than on organisational consistency and human support.
Hailed for its performance promises, predictive maintenance is still struggling to establish itself as an industry standard. While artificial intelligence (AI) and the IoT open up unprecedented opportunities, their effectiveness remains dependent on a delicate balance between data quality, system consistency and human expertise. For companies, the challenge is no longer to test technological building blocks, but to build a sustainable operational strategy.
Predictive maintenance: industrial promise or technological illusion?
For a decade, predictive maintenance has been presented as the logical outcome of the connected factory. Maintenance 4.0 combined with Factory 4.0… However, in 2025, predictive maintenance is still far from being widespread. Admittedly, the technologies are there (smart sensors, embedded AI, etc.), but their implementation remains complex.
La confusion commence souvent par le mot lui-même. « Prédictif » recouvre des réalités très différentes, du simple seuil d’alerte à l’analyse croisée de données complexes. Dans certains secteurs très industrialisés, comme l’aéronautique ou la défense, les cas d’usage se multiplient. Toutefois dans la majorité des entreprises, les projets restent limités à quelques périmètres pilotes, faute de données exploitables, d’intégration fluide ou de retour sur investissement mesurable.
The confusion often starts with the word itself. ‘Predictive’ covers a wide range of realities, from simple alert thresholds to complex cross-analysis of data. In certain highly industrialised sectors, such as aeronautics and defence, use cases are multiplying. However, in most companies, projects remain limited to a few pilot areas due to a lack of usable data, seamless integration or measurable return on investment.
Conditions for success that go beyond technology alone
If predictive maintenance is struggling to gain acceptance, it is not for lack of technology. Sensors, artificial intelligence, analysis tools: everything is already in place. But these building blocks still need to work together. Isolated, poorly positioned or contextualised data is of little value. It is the overall consistency that makes the difference.
Integration plays a central role here. When CMMS, IoT, BI, and BIM are considered as a whole, the company gains clarity. It can finally move from simply monitoring activity to a proactive approach.
However, none of this works without teams. They are the ones who validate, interpret and arbitrate. In this sense, technology cannot replace field experience, because to take full advantage of the tools, it is also necessary to support their use, provide training and develop practices in line with the pace of the business.
More than just a technical project, an industrial strategy
When properly planned, predictive maintenance optimises interventions, reduces unexpected downtime and helps to better allocate resources. Provided it is part of a genuine business strategy. For a project to be useful, it must target the right equipment, the right sensors and the right thresholds. The aim is not to anticipate all breakdowns, but to intervene where the impact is real.
Added to this are two key dimensions: data confidentiality and cybersecurity. In a system open to connected objects, each sensor becomes a potential attack surface. However, data from industrial equipment is often sensitive, even critical. It must therefore remain on site to be better protected. This requires architectural choices, strictly controlled access and AI capable of operating locally. Because effective but poorly secured artificial intelligence remains a vulnerability. And in such an environment, security cannot be an option.
Ultimately, predictive maintenance reveals more than just a new relationship with machines. It is a different way of thinking about industrial performance. More agile and more targeted. And perhaps the real turning point will not come from the technology itself, but from the ability to bring together data, tools and human expertise. This is where the industry of tomorrow will be played out.
By Carlo Fichera, Chief Executive Officer and Founder of Siveco Group.
