Is being a Control Systems Engineer
at risk from AI?

Not in the foreseeable future. While AI can assist with simulation, code generation, and tuning, the core responsibilities—commissioning physical systems, validating safety-critical designs, navigating regulatory frameworks, and troubleshooting in industrial environments—require human judgment, accountability, and physical presence. Current AI lacks the sensory feedback, contextual understanding, and liability framework to operate independently in these domains. The role will evolve toward higher-level integration and oversight, but demand for skilled engineers remains strong.

Routine tasks like PID tuning, boilerplate PLC coding, and documentation drafting are already seeing AI assistance and will continue to accelerate over the next 2-3 years. However, the complex, safety-critical, and physically integrated aspects of the role—commissioning, regulatory compliance, cross-disciplinary coordination—are unlikely to be automated within the next 5-7 years. The bigger shift is that engineers who don't adopt AI tools for productivity will fall behind peers who do. Focus on building skills that complement AI rather than compete with it.

Prioritize three areas: (1) Deepen expertise in safety instrumented systems and functional safety standards (IEC 61508/61511), which require human certification and accountability. (2) Develop fluency in IT/OT convergence, including industrial cybersecurity and cloud-connected SCADA systems, as this is a growing complexity layer AI cannot yet navigate independently. (3) Strengthen project leadership and client-facing skills—the ability to translate technical constraints into business outcomes and coordinate multidisciplinary teams is a durable human advantage. Also, learn to use AI tools (simulation assistants, code generators) to amplify your productivity rather than resist them.

In the near term, salaries are likely to remain stable or grow modestly due to continued demand for infrastructure modernization, industrial automation, and energy transition projects. Engineers who adopt AI tools to increase throughput may see productivity bonuses or faster career progression. However, there may be downward pressure on entry-level roles as AI handles more routine tasks, making it harder for juniors to gain experience. Senior engineers with commissioning expertise, safety certification, and project leadership skills will command premium compensation, as these capabilities are difficult to automate and in short supply.

Senior engineers have significantly more resilience. They bring deep domain knowledge, regulatory expertise, client relationships, and the ability to lead complex commissioning projects—all areas where AI has minimal capability today. Junior engineers face a tougher landscape: AI tools are automating the routine tasks (simple PLC coding, standard loop tuning) that traditionally served as training ground. New entrants will need to accelerate their path to hands-on commissioning experience and safety-critical work to differentiate themselves. Mentorship and early exposure to physical systems are critical for juniors to build defensible skills.

Yes, but less than in purely digital roles. Control systems engineers working in regions with heavy industrial activity (manufacturing hubs, oil and gas, utilities, mining) have stronger demand and more resilience because physical presence is required. Engineers in regions with aging infrastructure or aggressive automation adoption (e.g., parts of Asia, North America) may see faster AI tool deployment but also sustained demand for skilled integrators. Remote work is limited in this field due to commissioning requirements, which insulates the role from global labor arbitrage but also ties career prospects to regional industrial health.

Industries with high safety criticality, regulatory oversight, and physical complexity offer the most resilience: oil and gas (especially upstream and refining), pharmaceuticals and biotech (cleanroom automation, batch control), utilities (power generation, water treatment), and food and beverage (hygiene standards, traceability). These sectors require extensive validation, human accountability, and domain-specific expertise that AI cannot replicate. Conversely, roles in simpler discrete manufacturing or purely software-based control may see faster automation. Specializing in a safety-critical vertical significantly boosts long-term resilience.