Is being a Controls Engineer
at risk from AI?

Not in the foreseeable future. While AI can accelerate routine programming and documentation, controls engineering is deeply tied to physical systems, safety-critical decision-making, and on-site commissioning. Current AI lacks the embodied presence, regulatory accountability, and real-time troubleshooting ability required for plant floor work. The role will evolve—AI will handle more boilerplate code and simulation—but the human engineer remains essential for integration, validation, and safety sign-off.

Repetitive programming tasks like generating standard ladder logic, creating HMI templates, and drafting P&IDs are increasingly automatable. AI-assisted code generation tools can produce boilerplate PLC code, and documentation tools can auto-update drawings. However, these tasks are typically a fraction of the job. The high-value work—commissioning, safety system design, cross-functional coordination, and troubleshooting complex process interactions—remains firmly in human hands because it requires physical presence, judgment, and accountability.

Junior engineers who spend most of their time on routine programming, screen design, and documentation updates face higher displacement risk, as these tasks are becoming more automatable. Senior engineers who lead system architecture, functional safety reviews, commissioning, and vendor negotiations are much more insulated. The key differentiator is whether you're executing predefined tasks or making judgment calls that carry regulatory and operational consequences. Juniors should accelerate their path to commissioning responsibility and safety certification to build resilience early.

Focus on areas where human judgment and accountability are non-negotiable: functional safety (IEC 61511, SIL certification), cybersecurity for industrial control systems (IEC 62443), and IT/OT convergence. Learn to architect digital twins and use AI-assisted simulation tools as a force multiplier, not a threat. Deepen expertise in a regulated vertical (pharma, energy, chemicals) where validation and compliance create moats. Finally, build cross-functional skills—engineers who can speak to operations, IT, and business stakeholders become orchestrators of complex projects that AI cannot manage end-to-end.

In the near term, no significant downward pressure is expected. Demand for controls engineers remains strong due to industrial automation growth, aging infrastructure upgrades, and the push for smart manufacturing. AI may compress the salary premium for purely execution-focused roles (junior programmers), but engineers with commissioning experience, safety certifications, and system integration skills will see stable or growing compensation. The labor market for experienced controls engineers is tight, and AI is more likely to make individuals more productive than to reduce headcount in the next 5 years.

Yes. Highly regulated industries—pharmaceuticals, nuclear power, oil and gas, aerospace—have stringent validation, safety, and compliance requirements that slow AI adoption and require human sign-off. These sectors also involve high-consequence failures where liability and accountability matter. Conversely, discrete manufacturing and less-regulated facilities may adopt AI-assisted tools faster. If you're concerned about resilience, specializing in a high-consequence vertical with strong regulatory moats is a strategic move.

Incremental change is already underway—AI-assisted code generation, predictive maintenance analytics, and automated documentation tools are entering the market. Over the next 3-5 years, expect these tools to become standard, reducing time spent on routine tasks by 20-30%. However, the core responsibilities—commissioning, safety validation, troubleshooting on the plant floor—will remain largely unchanged because they require physical presence and real-time judgment. The shift will be toward engineers managing more projects with AI augmentation, not wholesale replacement of the role.