Solar energy generation from a rooftop panel system can be monitored quickly and easily, an example of how artificial intelligence (AI) and digital tools are empowering businesses to optimize energy use and contribute to a decentralized, decarbonized grid.
The energy transition is accelerating. Electrification is surging, renewable power generation is expanding and energy consumption patterns are changing. At the same time, power systems are becoming more decentralized, digital and dynamic. These shifts are creating both complexity and opportunity, and AI is quickly becoming one of the most valuable tools we have to manage this transformation.
COMMENTARY
AI enables us to rethink how we produce, distribute and consume electricity. It allows us to improve efficiency, stability and sustainability across the entire energy value chain. But realizing AI’s full impact depends on how we embed it into infrastructure and business models going forward.
Managing a Decentralized Grid with Intelligence
One of the biggest shifts in the energy landscape is the rise of the prosumer—individuals and businesses that generate their own electricity through solar panels or other distributed energy resources. Many are evolving into localized energy hubs or microgrids, reducing reliance on centralized power but making energy flows more complex and less predictable.
AI is essential for managing this complexity. Advanced algorithms can forecast consumption and generation in real time, guiding when to store, use, or sell energy to support grid reliability and deeper renewable integration.
For businesses electrifying their operations—whether through electric vehicle (EV) fleets, electrified heating and cooling, or on-site storage—AI enables smarter energy decisions. These systems learn usage patterns, respond to dynamic pricing, and adapt to changing grid conditions. AI can shift energy-intensive processes to off-peak hours, optimize EV charging schedules, or draw from batteries when prices spike, reducing costs and alleviating grid stress.
At a broader level, utilities and grid operators can now rely on AI technology to forecast demand, monitor infrastructure, and optimize energy distribution. Together, these capabilities allow commercial and industrial sectors to become active grid participants, transforming energy from a cost center into a strategic asset.
Creating the Conditions for Scalable Impact
AI’s value doesn’t come from technology alone. It comes from how we scale it with the right infrastructure and policy frameworks.
High-speed communication networks are essential to make real-time data processing possible. Equally important are common protocols that ensure devices and systems can speak the same language. Without open standards, AI can’t operate effectively across the increasingly diverse landscape of energy assets.
Regulations must also evolve. Current models often reflect legacy systems built around centralized power and predictable loads. As energy becomes more dynamic, policy must incentivize flexibility, support data sharing and reward services that contribute to grid stability, whether those services come from a utility, a prosumer or an intelligent software platform.
Lastly, we need business models that benefit all participants. Consumers, utilities and technology providers must all see value in investing in AI-enabled systems. This includes financial incentives for demand response, time-of-use pricing and revenue models that reward energy efficiency and resilience.
AI-powered systems can accelerate the energy transition by improving efficiency, resilience, and renewable integration across the grid.
Ensuring Responsible and Trustworthy AI
As AI becomes more embedded in the systems that power our world, its responsible use is critical. That includes ensuring transparency in how decisions are made, designing systems that are explainable and auditable, and maintaining accountability for outcomes. These elements build trust between utilities and consumers as well as across the entire energy ecosystem.
Ethical AI governance should be treated as essential infrastructure. Clear guidelines and frameworks must guide how AI is trained, deployed and monitored, especially when it influences access to energy, data privacy or economic opportunity. Responsible AI is foundational to long-term impact and public trust.
A More Resilient Energy Future
As we face rising energy demands and the urgent need to decarbonize, AI offers a way to make energy management more responsive, efficient and resilient. To succeed, we must act with intention. That means embedding AI into the core of our energy strategy, designing systems that are built to adapt and aligning stakeholders around a shared vision for smarter energy consumption.
The energy transition is a complex challenge, but also a historic opportunity. With AI, we have a powerful means to accelerate progress if we build the right foundations and scale with purpose.
—Peter Weckesser is Chief Digital Officer at Schneider Electric.
