Skills Shift: Maintenance Engineers in the Age of Data and AI

For today’s maintenance engineers, success depends not only on technical expertise but on the ability to interpret, anticipate, and optimise. Expectations are expanding. Communication, collaboration, and alignment of technical decisions with operational and business priorities are now essential in multidisciplinary environments.

“The demand for skilled trades is evolving into highly specialised, digital-first work,” says Sander van ‘t Noordende, CEO of Randstad, one of the world’s leading HR and recruitment companies that also publishes regular research on labour market trends, skills, and the future of work.

He explains that as these roles now require continuous learning, similar to knowledge work, skilled trades should be viewed as a top-tier career path.

From fixing to predicting: Engineers are no longer valued only for their ability to repair equipment, but for their capacity to prevent failures. This shift is driven by the availability of real-time data.

Predictive maintenance and IoT-based analysis are now central to the role. Engineers interpret data streams—such as vibration, temperature, and pressure—to identify early signs of failure and intervene before disruptions occur. In many cases, failures signal that systems were not properly monitored in advance.

Alongside this, programmable logic controller (PLC) diagnostics have become a core skill sought after by many companies. Troubleshooting increasingly means interpreting digital fault codes and understanding control logic rather than relying solely on physical inspection.

According to industry experts, data analysis has become as fundamental as traditional tools; engineers who do not read and utilise data cannot improve performance.

This data-driven mindset extends across modern operations. Engineers maintain robotic systems, monitor automated production environments, and use digital metrology tools, such as coordinate measuring machines and laser scanners, to ensure precision and quality.

The Rise of the Industrial Mechatronics Specialist: Driving Continuous Improvement in daily operations. Using methodologies such as Lean and Six Sigma, engineers analyse performance data, identify inefficiencies, and continuously refine processes.

At the same time, increased connectivity brings new responsibilities. Maintenance professionals must understand the basics of cybersecurity to protect operational technology, from access control systems to smart infrastructure.

These changes reflect a broader shift driven by Industry 4.0. Maintenance roles have evolved from reactive and preventive models toward predictive and prescriptive approaches.

The traditional technician is becoming an “industrial mechatronics specialist,” combining mechanical expertise with digital and analytical capabilities.

As the Ranstad CEO describes, maintenance work has moved much closer to knowledge work. As a maintenance engineer, you are expected to manage systems, interpret data, and make decisions that impact the entire operation.

With this shift has come a change in how skills are prioritised. Engineers looking to advance their careers should focus first on developing data fluency and an understanding of digital integration.

From there, building expertise in quality management and continuous improvement processes can significantly enhance career prospects.

AI raises the bar—does not replace it: As digitalisation accelerates, artificial intelligence is becoming integral to everyday maintenance work. This development often raises concerns about job displacement, but available evidence suggests that, rather than replacing jobs, AI is shifting the nature of maintenance work and creating new expectations for engineers.

Kevin Ruttens, Senior Business Manager, Engineering at Randstad, notes that AI is not replacing junior engineers but elevating the expectations for entry-level positions.

This shift requires engineers to show judgment and analytical abilities beyond routine activities. Increasingly, they must interpret complex AI outputs, manage automated systems, and make decisions based on digital information. Therefore, training should emphasise digital fluency, ethical oversight, and systems thinking to keep pace with AI-driven changes.

The human factor still matters: Despite rising technical demands, soft skills are becoming more—not less—important. Attributes such as communication, teamwork, and attention to detail are critical in collaborative and highly regulated environments.

Data from Randstad shows that care is among the most frequently mentioned qualities in job postings, reflecting the importance of safety, compliance, and quality. Clear communication, meanwhile, ensures coordination across teams and the smooth operation of complex systems.

Automating stepping stones is risky. Even as the role of an industrial maintenance professional evolves, the industry faces a widening skills gap. Many early-career engineers enter the workforce with strong mechanical foundations but lack experience in data analysis, digital diagnostics, and system-level thinking.

This challenge is compounded by pressure on the talent pipeline.

Replacing junior engineers with technology is not an answer. Junior roles are not just about execution; they are critical for knowledge transfer.

Much of engineering expertise is acquired informally: by observing experienced colleagues, understanding why legacy systems were designed the way they are, and absorbing unwritten practices around risk and safety.

If these roles disappear, this transfer is disrupted, Ruttens explains. Over time, organisations risk creating a “broken succession pipeline,” with fewer candidates developing into senior positions.

Tacit knowledge may also be lost when experienced engineers retire, with no next generation prepared to inherit it.

He also notes that, over the next five to ten years, organisations relying too heavily on automation risk developing a leadership gap. What may appear to be a tactical cost-saving measure today could create significant challenges for operational continuity in the future.

What comes next? Looking ahead, demands on maintenance engineers will continue to rise. Artificial intelligence is expanding rapidly, with skills such as AI orchestration and prompt engineering becoming increasingly relevant. Engineers are already using AI to support diagnostics and optimise workflows.

At the same time, sustainability is reshaping the field. As industries adopt renewable energy systems, maintenance teams will need to manage smart grids, energy storage systems, and new infrastructure.

Automation will handle routine monitoring, but human expertise will remain essential in complex, unpredictable situations.

From support function to strategic role: Maintenance is no longer a purely technical support function. It is becoming central to operational performance. This development will continue.

To succeed, engineers must continuously develop their skills, combining technical expertise with data fluency and a proactive mindset. The goal is no longer just to maintain equipment, but to optimise systems and improve outcomes.

For those who adapt, this shift offers significant opportunities. Maintenance engineers are no longer just keeping operations running; they are helping define how they evolve.

Key Skills Shaping Maintenance Work Over the Next Decade

AI orchestration and prompt engineering

As AI adoption accelerates, maintenance engineers will increasingly work with autonomous systems and large language models to support diagnostics and optimise workflows.

Renewable energy and green tech integration

Integrating smart grids, energy storage, and sustainable technologies into existing infrastructure will become a core capability.

Advanced human-in-the-loop problem solving

As automation handles routine tasks, engineers will be valued for their ability to solve complex, real-world problems and make decisions in dynamic environments.

Fewer Entry-Level Roles, Higher Expectations

Entry-level engineering jobs are declining, reflecting a broader shift in how work and skills are changing. Engineering is one of the first fields where this is clearly visible, but similar trends are emerging across the broader job market.

Research supports this. A 2025 Stanford study found that employment among engineers aged 22–25 has fallen by 16%, a trend directly linked to AI. At the same time, entry-level hiring has dropped sharply—down 72% in European tech and 34% in the U.S. compared to pre-pandemic levels.

This comes at a time when more skills are needed, not fewer. The World Economic Forum estimates that 60% of workers will need retraining by 2027, yet only about half have access to it.

At the same time, expectations are rising. According to the Randstad Workmonitor 2026 report, 41% of workers would leave a job without learning opportunities, and 44% would not take a role that doesn’t offer future-proof skills.

The message is clear: if companies can’t show how employees will grow alongside AI, they risk losing the talent they need.

Source: Workmonitor 2026

ABOUT: Sander van ‘t Noordende

Sander van’t Noordende is Chief Executive Officer and Chair of the Executive Board at Randstad. He started his role in March 2022 and had previously served as a member of the Supervisory Board since March 2021. Sander spent the majority of his career at Accenture, where he held a number of executive roles. He holds a degree in Industrial Engineering, specialising in Finance and Marketing, from the Eindhoven University of Technology.

Text: Nina Garlo-Melkas Photo: Randstad