IN Brief:
- Schneider Electric’s latest study of 400 senior energy and chemicals executives across 12 countries points to higher autonomy targets through 2030.
- Respondents identified AI, digital twins, cloud-edge computing, and software-defined automation as leading enablers, while cost, legacy systems, and cybersecurity remain major barriers.
- Rising data-centre electricity demand and workforce pressure are pushing autonomous operations from selective deployment towards plant-wide strategy.
Schneider Electric says energy and chemicals operators are accelerating investment in autonomous operations, with a new global survey pointing to a sector that is moving beyond isolated automation projects and towards broader plant-level autonomy. The company’s latest Global Autonomous Maturity Report is based on responses from 400 senior executives in 12 countries and frames autonomy as an increasingly central operating model decision across heavy industry.
The survey suggests the shift is already under way. Respondents reported current operations running at an average of 70% autonomy, with plans to reach 80% by 2030. Around 31.5% said advancing autonomy is a critical priority over the next five years, rising to 44% over a ten-year horizon, while fewer than 5% placed it in the low-priority category. That points to a market that is no longer treating autonomy as a distant technical ambition.
Commercial pressure is the main driver. Schneider said 59% of executives believe delaying adoption will increase operating costs, 52% expect workforce constraints to worsen, and 48% see slower adoption as a competitiveness risk. The barriers are substantial but familiar: high upfront cost was cited by 34% of respondents, legacy systems by 30%, organisational resistance by 27%, cybersecurity concerns by 26%, and regulatory uncertainty by 25%.
Artificial intelligence sits at the centre of the investment case. Schneider said 49% of respondents identified AI as the single biggest enabler of faster autonomous adoption, ahead of cybersecurity advances, cloud and edge computing, digital twins, advanced process control, and open, software-defined automation. The pressure behind that investment is coming not only from inside the plant, but also from the power system around it. The International Energy Agency projects data-centre electricity consumption will more than double to around 945 TWh by 2030, while electricity generation required to supply data centres rises to more than 1,000 TWh, underlining the wider energy system strain associated with AI growth.
The regional pattern is uneven. Schneider’s data places GCC countries and Asia ahead on current maturity, while North America is expected to accelerate fastest over the next five years as data-centre expansion and energy demand growth intensify. Europe is still advancing, but on a steadier trajectory. That slower pace does not remove the pressure on operators; it mainly means the route to autonomy is likely to be shaped more by retrofit decisions, software integration, and existing asset constraints than by greenfield build-out alone.
Schneider linked the survey findings to live deployments at Shell’s Scotford Refinery in Canada and European Energy’s Kassø Power-to-X facility in Denmark, where software-defined automation, remote monitoring, and AI-supported digital models are being used to improve operational responsiveness. The underlying argument is that autonomous operations are becoming less about a single control technology and more about the integration of power management, process control, software, and industrial data into one operational layer.
That leaves autonomy looking increasingly like a systems question rather than an automation add-on. For operators facing higher energy intensity, tighter labour availability, and more volatile operating conditions, the direction of travel is towards facilities that can sense, predict, adapt, and recover with less manual intervention across the whole site.
