According to the KPMG report “Intelligent Energy. A Blueprint for Creating Value through AI-Driven Transformation,” more than 44% of companies in the energy sector treat artificial intelligence (AI) as a core element of their business, and as many as 60% declare a return on investment (ROI) in AI exceeding 10%. While an increasing number of organizations implement AI solutions in critical operational processes, broader adoption is still hindered by data quality issues, skills shortages, and regulatory complexity.
The study shows that 92% of energy industry leaders consider AI deployment a key source of competitive advantage. Companies view AI not only as a technical tool but primarily as the foundation for transformation—used to automate processes, improve decision quality, manage risk, and achieve ESG goals. The most common AI applications include network operation optimization, infrastructure maintenance automation, real-time data analytics, and predictive management of costs and emissions.
Currently, 56% of organizations are running AI pilot projects, yet only 13% have internal competency centers enabling solution scaling. Nevertheless, 79% of respondents reported improved operational efficiency, and 65% identified increased efficiency as the primary benefit of AI implementations. Additionally, 74% note a positive impact of AI on revenue growth, while 60% report ROI exceeding 10%.
Awareness of AI’s potential is growing, but many firms still lack structures to fully exploit it. Major barriers include poor data quality (cited by 58%), regulatory complexity (38%), and budget constraints (37%).
AI delivers the greatest benefits where high-quality data is available. The technology increasingly leads business process automation. Energy companies investing in AI for predictive infrastructure maintenance, power balancing optimization, and dynamic demand forecasting already see tangible gains in operational efficiency and loss reduction. Polish energy firms are more open to pilot projects, but full technology scaling remains limited by insufficient data quality and shortages in analytical skills. Priorities in coming years should include developing data infrastructure and building teams that combine technological expertise with sector knowledge. “AI won’t replace experience but can significantly enhance it where speed and accuracy of decisions matter,” comments Andrzej Gałkowski, Partner and Head of AI at KPMG Poland and Central and Eastern Europe.
Regarding the energy transition, companies increasingly face challenges balancing AI adoption with sustainability goals—63% find this difficult, and 71% view sustainability as a strategic priority, even above technology deployment. Yet organizations continue investing: 96% allocate funds for development projects without expecting immediate returns.
Structural barriers remain significant for AI deployment in energy. Legally, the lack of precise regulations on AI applications in critical infrastructure creates uncertainty for investors and operators. Still, the direction looks promising: both the EU AI Act and Poland’s forthcoming Digitalization Strategy through 2035 promise facilitation in standardization, interoperability, and secure AI adoption.
As digital transformation progresses, a systemic approach to integrating AI into operations is key—starting with process automation, through modern data infrastructure development, to leveraging AI to support climate goals and enhance system resilience. Coordinated technological, organizational, and regulatory efforts will determine whether AI delivers real, lasting value to the energy sector, emphasizes Anna Szczodra, Co-Managing Partner at KPMG Law and Head of Energy Advisory in Poland and EMA.
KPMG’s report finds energy firms focus on building flexible cloud-based infrastructure—64% operate using corporate cloud or hybrid-cloud models. Concurrently, data organization needs increase, with inconsistent formats and lack of quality standards cited as major challenges by 58%.
About the Report:
The “Intelligent Industries” series is based on KPMG International research combining quantitative and qualitative methods. It includes in-depth interviews with technology, regulatory, and business experts, plus KPMG sector advisors. The study surveyed 1,390 decision-makers from key markets (Australia, China, Germany, UK, Canada, France, Japan, and the US), including 163 from the energy sector. An 18-month generative AI business value analysis project complemented the research. The results form a practical guide for organizations aiming to harness AI’s potential effectively.
