AI: How Companies in the Energy Sector Are Increasing Their Profits

A recent analysis shows that the energy industry is now using artificial intelligence (AI) extensively. Examples from six areas demonstrate how productivity and profit margins can grow.

Düsseldorf. They save money, working hours, and operate more efficiently: energy companies are already benefiting significantly from the use of artificial intelligence (AI). This is the result of a study by PwC subsidiary Strategy&, which was made available exclusively to Handelsblatt.

According to the study, AI has already led to cost savings of over 60%, productivity increases of more than 50%, and margin improvements of 10 to 20% in specific use cases.

1. Intelligent Energy Supply and CO₂ Reduction

Many energy-consuming companies could significantly reduce their energy costs-if they better understood their consumption. AI makes this possible. For example, the startup Ecoplanet offers a solution that monitors the electricity consumption of running machines.

Founder Henry Keppler reports on a customer with 250 locations in Germany who used Ecoplanet's AI to identify sites with particularly high energy consumption. "Our AI identified a faulty industrial kitchen. The electric stovetops were overheating," Keppler says. This issue caused €30,000 in additional costs-until the AI detected it.

A key point: companies don't just pay for the amount of electricity they use, but also for the maximum power demand-the peak time when they draw the most electricity and strain the grid. For example, a faulty kitchen can cause a temporary spike in consumption, increasing the overall electricity contract cost.

AI can more easily identify the source of such peaks. One industrial customer had a spike caused by a cooling unit during a particularly hot day. The AI correctly suspected the cooling unit, and the customer saved €80,000 by reacting accordingly.

AI also helps energy providers find customers. According to the study, AI has improved customer acquisition success rates by up to 30% by identifying those actively seeking such solutions.

2. Smarter Energy Trading

Strategy& observed major benefits from AI in energy trading (electricity and gas). AI optimizes trading algorithms, identifies opportunities, incorporates historical data and forecasts, and operates with far greater capacity than human traders. This enables faster trading and returns that are 5-10% higher.

Ecoplanet also offers AI solutions to improve energy trading timing. Keppler explains: "It's no longer just about using less energy, but about using it at the right time." For instance, renewable energy is often abundant and cheap at certain times, while coal power is expensive at others.

AI helps companies avoid overbuying energy, which would force them to sell excess at a loss. Ecoplanet developed a machine learning algorithm to mitigate this risk. A large language model (LLM) assists customers in interacting with the system-for example, by stating they expect to use 10% less energy next year and prefer certain sources. The AI translates this into an optimal purchasing strategy.

3. Higher Profits for Energy Providers

According to the study, power plant operators can increase their commercial operating time and revenue by 5-10% using AI-and boost profits by 2-3% through smarter deployment planning.

These intelligent solutions have been in use for some time. Frédéric Godemel, Executive VP for Energy Management at Schneider Electric, points to a system that uses machine learning to forecast loads and generation: "Energy providers can operate more reliable, cost-effective, and sustainable grids."

Better forecasts allow providers to plan how much electricity is needed and when, reducing reliance on fossil backup plants and increasing the use of renewables.

4. Predictive Grid Monitoring

AI is particularly useful for monitoring power grids. According to Strategy&, known use cases have already saved 50,000 work hours and 10,000 helicopter flight hours annually-over €20 million.

The concept: AI uses satellite and drone imagery, weather data, and pattern recognition to detect infrastructure issues early. Godemel says: "We use AI for storm forecasting-it predicts weather damage and helps utilities deploy teams early and efficiently."

AI can also inform technicians in advance about which part is broken. Niemeier explains: "Currently, technicians often visit a site two or three times-first to assess the issue, then to return with the right parts." Augmented reality (AR) could help here by overlaying real-time data through smart glasses, allowing remote simulations and training.

5. Reducing Energy Use in Data Centers

Schneider Electric also uses AI in partnership with chipmaker Nvidia. Godemel says: "In data centers-for example, with Nvidia-we've reduced cooling energy consumption by up to 20%."

They achieved this through virtual modeling and testing, which also shortened the construction

6. Automated Customer Service

Strategy& sees the greatest savings potential in customer service. Well-trained AI chatbots can resolve 80-90% of customer inquiries, according to Niemeier.

This is especially helpful given the skilled labor shortage. Support costs could be reduced by 60%. While not energy-specific, Niemeier notes: "Customer service is a major issue in the energy sector-and thus a major cost-saving opportunity."

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Tags: AI, digital grid