The Boston Consulting Group (BCG) published a study concluding that artificial intelligence can increase worker productivity in the renewable energy sector by between 15% and 25%, as well as improve energy yield by one to three percentage points. The report, titled "A Real-World Game Plan for AI in Renewable Energy," warns that, although the expected gains result from greater asset availability and more effective operational execution, value capture "remains limited" in many organizations.
The study comes at a time of accelerating investment, with energy and utilities companies planning to triple their investment in AI in 2026 compared to 2025 — the largest increase among all sectors analyzed, with the exception of insurers. BCG emphasizes that the problem is rarely the lack of use cases, but rather the difficulty in scaling initiatives beyond the pilot phase and linking them to well-defined business metrics.
One of the most relevant findings of the study is that 10 to 15 well-selected use cases can capture between 60% and 70% of the total value potential, provided they are chosen for their operational and financial impact. Among the main application areas are real-time operational monitoring, asset performance forecasting, maintenance, and field operations management. In one case analyzed, a European utility applied AI to field work order planning, reducing unproductive time by one to two and a half hours per technician per day, resulting in operational cost savings of several million euros.
In the Portuguese context, the agenda gains momentum as the country strengthens its energy transition and modernizes infrastructure. BCG recommends a hub-and-spoke model — a central structure that defines standards and manages governance, combined with decentralized business units — and warns that companies cannot import the "move fast and break things" motto from the technology industry, given the critical nature of energy infrastructure.
