Energy AI Hits 70% Autonomy in Schneider Electric Survey

Schneider Electric's global survey of energy executives finds the sector operating at 70% autonomy, with plans to reach 80% by 2030.

Energy AI Hits 70% Autonomy in Schneider Electric Survey

A global survey of energy and chemicals executives across 12 countries, commissioned by Schneider Electric, finds the sector already operates at roughly 70% autonomy. Routine tasks — monitoring equipment health, adjusting power flows, optimizing maintenance schedules — run with minimal human intervention. The executives surveyed plan to push overall autonomy to 80% by 2030, with a significant portion of operations expected to reach full automation on the same timeline.

Nearly half of respondents identified energy AI as the single biggest enabler of that acceleration. Real-world deployments support the confidence. Shell's Scotford Refinery in Canada uses AI-driven process controls that have compressed decision cycles from hours to minutes. European Energy's Kassø Power-to-X facility runs automated forecasting models that adjust operations without waiting for a human operator. These deployments show what high autonomy looks like in practice: systems that handle standard conditions independently while escalating genuine anomalies to human teams.

The barriers between current levels and the 2030 targets remain concrete. Executives pointed most often to high implementation costs, followed by legacy systems that resist integration with modern AI grid management platforms and organizational resistance from teams reluctant to cede control to automated workflows. Each reinforces the others: legacy equipment demands expensive custom integration, and that cost gives skeptics reasons to slow adoption.

Gwenaelle Avice Huet, Schneider Electric's Executive Vice President for Energy Management, put it directly: "Autonomy is rapidly becoming the new operating model of industry." Energy forecasting AI and autonomous control systems are moving from pilot programs to production environments faster than most operators expected even two years ago. Companies treating utility automation targets as aspirational rather than operational risk falling behind those already scaling.