By 2027, 40% of control rooms in the power and utilities sector will be operated by AI-driven systems, predicts new research from Gartner. This development is expected to reduce human error and increase operational efficiency while introducing new challenges in cybersecurity.
A key driver behind this shift is the sector’s commitment to AI investment. Gartner’s 2025 CIO and Technology Executive Survey revealed that 94% of chief information officers (CIOs) in the industry plan to boost AI-related spending in 2025. The average planned budget increase across these organisations is 38.3%, reflecting a strategic focus on leveraging technology to modernise operations.
“AI technology is poised to transform the power and utilities sector,” said Gartner senior director analyst Jo-Ann Clynch. “Human decision-making is critical, but it is also a significant factor in industrial accidents. AI-driven operations offer a compelling solution, performing tasks with repeatability, precision, and without bias when effectively governed.”
The transition to AI aligns with broader changes in the energy sector, where decentralised systems are reshaping traditional utility models. Distributed energy resources, including solar panels and energy storage solutions, are playing a pivotal role. These systems enable customer-owned intelligent assets to optimise costs, manage production, and address energy needs dynamically. AI technologies are critical in this ecosystem, supporting real-time data analysis, predictive maintenance, and automated anomaly detection to enhance efficiency.
Despite the benefits, the integration of AI introduces security vulnerabilities in cyber-physical systems. These interconnected environments, combining digital and physical processes, are increasingly at risk of cyberattacks. Gartner has highlighted the need for significant investments in security measures and compliance frameworks to safeguard critical infrastructure.
To help organisations navigate this transformation, Gartner recommends three key strategies. First, companies should develop a comprehensive AI integration plan, focusing on areas where AI can minimise human error while establishing governance systems to monitor and mitigate risks.
Second, robust cybersecurity measures are essential. Gartner advises investing in advanced protections, including quantum-enhanced security technologies, and conducting regular vulnerability assessments. Ensuring that incident response systems are prepared for evolving threats is critical to maintaining system integrity.
Finally, effective collaboration between humans and AI is necessary for a smooth transition. Gartner suggests training programmes to help control room staff work alongside AI systems, interpret outputs accurately, and maintain oversight in decision-making processes.
The integration of AI-driven systems into power and utility operations marks a significant evolution for the sector. While the benefits in efficiency and decentralisation are substantial, addressing security risks and ensuring human-AI collaboration will be vital to achieving sustainable progress.
Practical examples of AI integration in power and utility control rooms
The integration of AI into power and utility control rooms is no longer a distant concept, with several initiatives already demonstrating how these technologies can reshape the sector.
One prominent example is the US National Renewable Energy Laboratory’s (NREL) development of “eGridGPT,” a generative AI model designed to assist power grid control room operators. This model supports decision-making processes by interpreting data and operational models, enabling operators to act with greater precision. The AI tool focuses on enhancing grid reliability and efficiency by providing proactive decision support and predictive online control, a capability that aligns with the evolving needs of modern energy systems.
Another initiative comes from Camus Energy, a US-based grid orchestration platform, which is leveraging AI as an intelligent copilot for utility operators and planners. Rather than replacing existing systems, Camus Energy’s approach is to augment them, improving operational efficiency and delivering optimised solutions. By offering actionable insights, the AI enables operators to retain ultimate decision-making authority while relying on enhanced data processing and analysis to support their tasks.
The US Department of Energy (DOE) is also advancing the use of AI in the energy sector through its Artificial Intelligence for Interconnection (AI4IX) programme. This $30m funding initiative is designed to accelerate the integration of new solar and wind energy projects into the power grid. By using AI to streamline the interconnection application process, the programme aims to address delays and promote the adoption of renewable energy sources more effectively.
Further, the Biden administration has taken steps to formalise AI’s role in critical infrastructure, including the power grid, by releasing a set of guidelines. Developed by the Department of Homeland Security, these guidelines urge AI developers to evaluate risks, align AI applications with human-centric values, and ensure the protection of user privacy. The framework also highlights the importance of robust cybersecurity measures to mitigate the potential risks associated with integrating AI into critical infrastructure.
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