79% energy firms report AI-led efficiency gains; 60% record ROI above 10%: Report
New Delhi: About 79 per cent of energy companies surveyed globally reported measurable efficiency improvements from the adoption of artificial intelligence, with 60 per cent of them achieving returns on investment above 10 per cent, according to a new report by KPMG International.
The findings were published in the report titled "Intelligent Energy: A Blueprint for Creating Value Through AI-Driven Transformation," based on a global survey of 163 senior executives from eight countries.
According to the report, 56 per cent of the surveyed energy companies have moved beyond pilot projects to scaled AI implementations, while 44 per cent have embedded AI capabilities across multiple business functions.
KPMG noted that 76 per cent of energy firms intend to increase their investments in AI over the next 12 months, with 63 per cent of them planning to raise spending by more than 10 per cent.
Anish De, Global Head of Energy at KPMG International, said in the report, 'For AI to truly scale and deliver value, energy companies must rethink not just their technology, but their entire operating model.'
The report highlights the emergence of agentic AI, which allows systems to autonomously manage workflows. In one case study cited in the report, a 21-day process was reduced to 18 minutes using AI agents.
However, several challenges to AI adoption remain. Around 58 per cent of companies reported data quality issues due to inconsistent formats and legacy systems. Regulatory complexity was cited by 38 per cent of respondents, while 37 per cent pointed to budget constraints as a key hurdle.
Only 13 per cent of the companies surveyed said they have an AI Centre of Excellence in place.
Despite the challenges, 92 per cent of organizations indicated that they are investing in future-focused AI projects even without immediate return on investment expectations. These include applications in predictive maintenance, carbon emissions tracking, safety automation, and customer service.
The report identifies use cases for AI in managing smart grids, autonomous energy trading, and optimising distributed renewable energy assets. It also notes the increasing adoption of AI in customer-facing areas, including demand forecasting and real-time service analytics.
The report concludes that scaling AI across value streams and embedding it in real-time decision-making across generation, transmission, trading, and customer engagement will be critical for energy sector transformation.
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