AI Digital Baseload is Reshaping Power Markets and the ETRM Platforms that Serve Them

By Alain Ghanem, client services director of commodities EMEA and trading MEA, and Chantal Ghobril, product marketing manager

At Eworld Energy & Water, one theme dominated our conversations with utilities and transmission system operators (TSOs): AI is reshaping electricity systems. Rapid AI growth is driving a surge in electricity consumption. Existing infrastructure was never designed to absorb it. For power and gas participants, AI driven demand is becoming a structural planning constraint. It increases the need for system flexibility and accelerates reliance on transitional gas capacity alongside renewables. In this context, the ability to deliver more compute or output per gigawatt is becoming a competitive edge. AI-driven digital baseload is becoming a major force. Data center demand is expected to rise from about 55 GW today to 84 GW by 2027. For the first time, digital demand is approaching levels comparable to heavy industry. This will affect grid constraints, infrastructure planning and system costs. By 2030, consumption could more than double to 108 GW, with AI-related demand rising by as much as 50 percent annually. As a result, load curves, planning assumptions and operational decisions are shifting across regions.

Rising digital baseload also reshapes commercial strategies for producers, traders and utilities.

As data centers tighten supply, participants are looking for new ways to monetize volatility and constraints. These include cross-border flows, congestion plays, financial transmission rights (FTRs), spark spread opportunities, and flexible assets such as batteries and peaking power plants.

This pressure is also changing generation and contracting decisions. Grids are delaying the retirement of dispatchable assets as they struggle to meet rising demand. In parallel, AI companies are accelerating long-term power purchase agreements (PPAs) to secure stable, predictable and increasingly low carbon energy supplies. These contracts reduce supply risk for buyers and provide revenue certainty for utilities and suppliers as they expand generation, storage and grid infrastructure. AI-driven digital baseload brings more volatile intraday movements, sharper locational price signals and tighter supply-demand conditions. This increases the volume, speed and complexity of data that trading and risk teams must process. It is important to distinguish two roles of AI here: AI workloads are a new source of electricity demand, while AI tools are increasingly used by market participants to improve forecasting, optimization and risk management.

Energy trading and risk management (ETRM) platforms are becoming more dynamic.

As AI-driven demand increases volatility and data intensity, trading teams are also adopting AI-enabled analytics within their own workflows. To support this shift, platforms need to move away from monolithic designs. They should adopt open, modular architectures that are real-time, interoperable and highly scalable. This approach helps integrate new analytics safely into mission-critical processes without compromising security or performance. It is often enabled through application programming interfaces (APIs) and well-defined services. Trading and asset desks need platforms that can absorb large volumes of forecasting and optimization data, quantify uncertainty, and support increasingly automated decisions across portfolios. Location volatility will be shaped by the interaction between AI workloads and regional power systems. ETRM platforms built on flexible, API-driven architectures are better positioned to handle this complexity and turn it into actionable commercial and operational insights. In practice, this means modernizing ETRM foundations and investing in openness, scalability and integrated analytics. Organizations that act early will be better positioned to navigate the turbulence of digital baseload, unlock new value streams and manage emerging risks in a rapidly evolving power landscape. The message for ETRM leaders is clear: The future of trading, risk and optimization will belong to platforms designed for an energy system where digital demand is growing and reshaping the market itself.