Today’s utility infrastructure is facing mounting challenges driven by the growth of new data centers, construction and sustainability initiatives. According to the International Energy Agency, global electricity demand is expected to rise by at least 4% per year through 2027.
In addition to electrification and growing energy consumption, utilities must modernize aging infrastructure, integrate distributed energy resources (DERs) and enhance grid resiliency in response to climate challenges. At the same time, they are under pressure to maintain and upgrade critical infrastructure while keeping pace with rapid technological advancements.
Advanced technologies and solutions, including artificial intelligence (AI) and machine learning (ML), are emerging as key enablers in addressing these challenges. However, barriers exist that are making widespread adoption of AI and ML more difficult.
In a recent survey of 600 utilities, four barriers to the adoption of AI and ML were identified:
- Hypercautious Adoption: 39% of utilities cited rigorous regulations and a safety-first mindset as factors slowing the pace of technology adoption. Utilities must balance the need for innovation with regulatory frameworks designed to ensure safety and reliability.
- Standardized Data: Legacy systems and inconsistent data formats often delay the adoption of AI and ML. 40% of utilities highlighted this issue, as they face the challenge of modernizing infrastructure while ensuring compatibility with new technologies.
- Sticker Shock: Financial barriers, including the cost of implementation and ongoing maintenance, were cited by 41% of utilities. The initial investment in AI and ML technologies, along with ongoing maintenance costs, presents a significant hurdle.
- Technical Tribulations: The most significant challenge, as noted by 43% of utilities, is the shortage of workers skilled in both traditional and advanced utility operations. Many workers are experienced with legacy systems, but there is a lack of expertise in the latest technologies.
Pivoting from traditional to advanced
When asked what would be most helpful to drive their AI/ML integration, utility executives said:
- Proven Technology: The desire for proven solutions is near universal and was cited by 62% of survey participants. Of the six countries we surveyed, proven technology tops the list across all except France, where it ranks second.
- Technology and Consulting Support: 53% said advanced technology and expert consulting support are needed to navigate complexities, optimize operations and drive meaningful outcomes using AI.
- Regulatory Support: 49% expressed the need for regulatory guidance to manage compliance, adapt to policy changes and ensure responsible deployment.
- Employee Education: 48% indicated that continued education is critical to equipping their workforce with the skills and knowledge needed to implement and manage AI solutions.
The barriers to AI and ML adoption have helped utility executives come up with a clear wish list: They need proven tools, help from experts, support from governments and programs to educate employees. Addressing these areas will not only facilitate AI adoption but also help bridge the growing skills gap by ensuring utilities are equipped to meet evolving demands. To achieve this, utilities should focus on three key strategies:
- Establish Strategic Partnerships: Forming partnerships with verified technology partners can accelerate the successful implementation of advanced technologies such as AI and ML.
- Upskill the Workforce: Utilities should provide ongoing training and learning opportunities for their workforce to ensure up-to-date knowledge and expertise.
- Localize Solutions: While there is always a bigger picture, utilities should focus on regional challenges and tailor solutions to fit their infrastructure and workforce needs.
Weighing the benefits of AI and ML adoption
Digital transformation is not an overnight process, but with a thoughtful and strategic approach, the benefits of AI and ML adoption are substantial. These technologies enable streamlined operations, real-time decision-making and predictive maintenance, helping utilities prevent prolonged service outages and improve overall efficiency. By embracing AI and ML, utilities can better manage growing energy demands while overcoming today’s workforce and infrastructure challenges, ultimately building a more resilient and future-ready grid.
Marina Donovan is Vice President for Global Marketing and Public Affairs at Itron.