An artificial intelligence keynote designed for energy, water and network operators. Romain Rissoan shows how AI optimises production, balances grids, anticipates maintenance needs and supports the energy transition.
Intermittent renewable energy, real-time grid balancing, the imperative of energy efficiency and the maintenance of critical infrastructure: the energy and utilities sector faces growing complexity. The energy transition is, at its core, a data transition — and artificial intelligence is the tool that makes it possible to manage that complexity, to anticipate rather than react, and to optimise at a scale and speed no human team could achieve alone.
This AI keynote for the energy sector illustrates practical applications with real-world examples: production and consumption forecasting, smart grids, predictive maintenance of infrastructure, and energy efficiency. Romain Rissoan also highlights the pivotal role of AI in supporting sobriety and the transition to cleaner energy, while addressing the essential questions of reliability and cybersecurity that apply to critical systems.
The talk is tailored for technical, operations and innovation leadership teams, as well as front-line engineers and field teams. The aim is to offer a grounded and responsible perspective: showing where AI creates genuine value for energy, water and network operators, how it works alongside human oversight on sensitive infrastructure, and how it serves both performance targets and environmental objectives.
Applications spanning production, networks and customer relations.
AI anticipates renewable energy output — often intermittent — and demand, by integrating weather data, historical records and usage patterns. This precise forecasting enables operators to balance supply and demand, reduce reliance on costly or carbon-intensive generation assets, and stabilise an energy system that is becoming increasingly complex and decentralised. The result is a more resilient grid and fewer costly emergency interventions.
By monitoring and optimising networks in real time, AI improves both the reliability of distribution and overall energy efficiency. It supports the integration of renewables, manages peak demand, directs flows and responds rapidly to incidents — transforming historically passive infrastructure into intelligent, adaptive networks capable of handling the demands of a decarbonised energy landscape.
On critical infrastructure — power stations, networks, pipelines — AI anticipates failures by analysing sensor data and historical records. Outages and incidents decrease, interventions are scheduled at the optimal moment, and the availability of assets on which public energy or water continuity depends is significantly strengthened. Unplanned downtime gives way to proactive, intelligently timed maintenance.
AI identifies waste and anomalies, and optimises energy consumption across buildings, industrial sites and equipment. It pinpoints savings levers, continuously adjusts settings and makes a tangible contribution to efficiency and emissions-reduction targets — with a return on investment that is often rapid and measurable. Every percentage point saved translates directly into reduced costs and lower carbon output.
AI tools power subscriber relations and customer support: answering billing, connection and consumption queries, and providing personalised energy-saving advice. Customers receive prompt responses around the clock, contact centre pressure eases, and advisers focus on complex situations requiring human expertise and judgement — improving both satisfaction and operational efficiency.
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