According to a new global study by Schneider Electric, the rapid expansion of AI, cloud computing, and data centres is placing unprecedented strain on energy systems, pushing companies in the energy and chemicals sectors to fast-track investment in autonomous operations to enhance efficiency, resilience, and competitiveness.
Autonomy rises to the top priority
The study, based on a survey of 400 senior executives across 12 countries, shows a growing sense of urgency around automation.
Around 31.5 percent of respondents said advancing automated operations is a “critical” priority over the next five years, rising to 44 percent over 10 years. Fewer than five percent viewed it as a low priority.
Executives cited strong commercial pressures driving this shift, warning that delays could lead to higher operating costs (59 percent), worsening talent shortages (52 percent), and declining competitiveness (48 percent).
However, adoption remains uneven due to several challenges, including high upfront investment costs (34 percent), legacy infrastructure (30 percent), organizational resistance (27 percent), cybersecurity concerns (26 percent), and regulatory uncertainty (25 percent).
AI at the core of transformation
The report highlights a broader transformation underway in the sector, as electrification, automation, and digitalisation converge.
Nearly half of executives (49 percent) identified AI as the single most important enabler of autonomous operations, followed by cybersecurity advancements, cloud and edge computing, digital twins, advanced process control, and software-defined automation systems.
“Autonomy is rapidly becoming the new operating model of industry,” said Gwenaelle Avice Huet, executive vice president at Schneider Electric, noting that companies are already operating at around 70 percent autonomy, with expectations to reach 80 percent by 2030.
She added that the shift is not about replacing human workers, but about enhancing productivity, improving safety, and enabling employees to focus on higher-value tasks.
Global race with regional gaps
While momentum is building globally, adoption levels vary significantly by region.
The Gulf Cooperation Council (GCC) countries and Asia are currently leading in both readiness and implementation, supported by strong investments in AI infrastructure and digital transformation.
Countries such as the UAE and Saudi Arabia have emerged as regional leaders, backed by large-scale data centre expansion and government-led AI strategies. A separate study by McKinsey & Company found that 84 percent of GCC organizations have already adopted AI, among the highest rates globally.
Egypt is also positioning itself as a key regional player, with growing interest in AI-driven solutions to boost industrial productivity, modernize infrastructure, and improve energy efficiency, according to the study.
North America is expected to record the fastest growth in adoption over the next five years, driven by its scale in energy production and the rapid expansion of data centres. Europe, meanwhile, is progressing more slowly compared to other regions.
Automated operations reshape industry
Industry analysts say the transition is happening faster than anticipated, with software-defined automation emerging as a central pillar of future energy systems.
Independent energy analyst Gaurav Sharma said autonomous technologies are enabling companies to deliver “more with less” while meeting rising demands for reliability, safety, and carbon reduction.
Real-world deployments are already underway. At Shell’s Scotford refinery in Canada, Schneider Electric is supporting the shift toward flexible, autonomous operations through advanced automation systems.
At European Energy’s Kassø Power-to-X facility, considered the world’s first commercial e-methanol plant, AI-powered systems are being used to optimize clean fuel production and enable remote monitoring.
A turning point for the energy sector
The findings underscore a critical turning point for the global energy industry, as surging electricity demand, driven largely by AI itself, forces companies to adopt smarter, more adaptive operating models.
With power systems under growing strain, autonomous operations are increasingly seen not as a future ambition, but as an immediate necessity to ensure resilience, efficiency, and long-term competitiveness in a rapidly evolving energy landscape.
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