Industrial AI is emerging as a key technology for energy and utilities organisations as they seek to improve grid resilience, manage aging infrastructure and respond to rising electricity demand, according to new research commissioned by IFS.
The global study, conducted by Censuswide among 850 C-level and senior utility executives, found that utilities are balancing sustainability objectives with growing operational pressures, including extreme weather, infrastructure challenges, affordability concerns and increased demand from electrification and data centres.
IFS said these pressures are prompting utilities to reassess how technology can support asset performance, operational efficiency and grid reliability.
“The pendulum in the energy sector has swung fast. Sustainability continues to be a critical objective for utilities, but evolving operational and geopolitical realities are driving a more balanced investment agenda,” said Carol Johnston, VP of Energy & Utilities at IFS.
The research found that 57% of utility leaders consider AI critical for reducing operational costs, while 47% said it is critical for optimising asset performance and managing electrification-driven demand growth.
According to IFS, Industrial AI can help connect fragmented systems, predict equipment failures and automate complex operational workflows. The research also points to challenges around the underlying data needed to support these capabilities.
Nearly half of respondents, or 49%, said operational data silos are hindering real-time decision-making. Only 33% described their asset lifecycle management capabilities as advanced, while 51% said their asset management systems are in place but operate in silos with limited predictive capabilities.
IFS said these findings highlight the role of modernised asset management in supporting technology-enabled approaches to resilience, reliability and investment planning.
“Utilities cannot invest their way out of today’s challenges through new infrastructure alone,” Johnston said. “Addressing growing demand and affordability pressures requires a balanced strategy that gets more from existing assets while making smart investments in new capacity, grid modernization, and resiliency.”
The research also identified growing interest in technologies designed to provide greater flexibility across the electricity grid. Battery Energy Storage Systems (BESS) and Distributed Energy Resource Management Systems (DERMS) are being considered as utilities look to manage demand volatility and protect against prolonged outages.
AI is also expected to play a role in integrating new energy technologies, with 46% of respondents saying it is critical for accelerating the integration of renewable and distributed energy resources.
Looking further ahead, 22% of utility leaders identified advanced geothermal as having the greatest potential long-term impact on securing continuous clean baseload power, while 18% selected small modular reactors.
IFS said the findings indicate that digital transformation in the utilities sector is increasingly being assessed through operational outcomes, including grid uptime, customer experience and regulatory compliance.
The research suggests that combining asset lifecycle management with Industrial AI could give utilities greater visibility into existing infrastructure while supporting decisions around new capacity, grid modernisation and emerging energy technologies.
