The energy sector is transforming. Driven by the need for decarbonization and improved efficiency, companies are turning to artificial intelligence to make operations more intelligent and adaptive. But unlocking this potential depends on how well AI is integrated into software that serves real business needs. Unatec can help bridge the gap between cutting-edge technology and practical implementation, ensuring AI delivers real value in complex energy environments.
“AI is definitely not a magic bullet which can be used everywhere, but we already see a lot of use cases in the energy sector,” says Raúl Gil García, CEO of Unatec. “The real value comes when intelligent systems are embedded in practical, reliable software that people trust and use.”
Predictive Maintenance: From Downtime to Uptime
One of the most promising applications of AI in the energy sector is predictive maintenance. By analyzing data from sensors, equipment logs, and historical performance, AI can detect patterns that indicate early signs of failure, allowing operators to intervene before breakdowns happen.
This can significantly reduce unplanned downtime, extend asset lifespans, and optimize maintenance schedules, especially in large-scale infrastructures like power plants, refineries, or renewable energy parks.
“AI makes it possible to go from reactive to proactive,” says Gil Garcia. “But it only works if the models are supported by good software and clear interfaces that maintenance teams can actually use.”
Optimizing Complex Energy Assets
Energy companies manage vast, interconnected systems, from gas networks and storage terminals to hybrid power plants and distribution grids. AI can help operators make better real-time decisions by analyzing dozens of variables simultaneously: demand forecasts, equipment status, weather data, and more.
When supported by intuitive software, AI can assist in optimizing energy flows, improving dispatch efficiency, and lowering operational costs, all while staying within regulatory and safety boundaries.
AI at the Edge: Enabling Decentralized Intelligence
With the growth of distributed energy resources – EV chargers, rooftop solar, home batteries – the grid is becoming more dynamic and decentralized. AI can help manage this complexity by enabling localized decision-making at the edge of the network.
Instead of relying solely on centralized control rooms, companies can deploy lightweight AI models on field devices or edge gateways, enabling faster responses and greater resilience.
“In energy, timing is everything,” Gil García notes. “AI at the edge can enable systems to react autonomously, even in milliseconds, but only if the software is efficient and secure.”
From Algorithms to Action
Having a high-performing AI model is only part of the equation. It also needs to be embedded in a platform that delivers actionable insights in a clear, explainable, and user-friendly way. This is particularly important in critical sectors like energy, where human operators still play a central role.
“Our role as a software partner is to bridge the gap between what AI can do and what energy professionals actually need,” says Gil García. “AI has immense potential to help energy companies become more efficient, sustainable, and competitive. But to move from ideas to impact, it must be embedded in well-crafted software.”
At Unatec, we believe in building smart systems that work in the real world, combining AI capabilities with software designed for people, performance, and the future of energy.