Data Centre Demand is Growing Like Never Before and Suppliers Must Adapt

Behind every AI breakthrough and cloud-based service is one critical infrastructure: the data centre. For energy suppliers, these facilities are fast becoming the biggest driver of electricity demand. However, unlike traditional commercial customers, data centres come with a new set of challenges. From unpredictable ramp-up schedules to limited demand flexibility, their rise is forcing suppliers to rethink how they forecast, price, and manage energy contracts.

With AI-driven innovation accelerating, energy demand from data centres is surging. According to Goldman Sachs, global power demand from these facilities could increase by 165% by 2030. In the U.S. alone, data centre electricity use could make up 8% of total national consumption. This level of growth is reshaping the energy landscape and putting added pressure on margins, forecasting models, and regulatory compliance.

So, what should energy suppliers do to adapt?

Why Data Centres Are a Different Kind of Customer

Data centres don’t behave like other large commercial loads. Most facilities are designed with long-term expansion in mind, which means their initial energy consumption can significantly underestimate future demand. For suppliers, this presents a major forecasting challenge: contracts priced on early usage data may quickly become unprofitable once the facility ramps up.

Adding to the complexity, data centres have relatively stable base loads, often operating 24/7 without major fluctuations due to weather. While that might seem like a win from a scheduling standpoint, it limits the opportunity to shift demand to off-peak hours. Many data centres also can’t participate meaningfully in demand response programs due to their always-on requirements.

The result? A customer that seems predictable on the surface but can introduce significant risk if growth and usage trends aren't actively monitored and forecasted with precision.

Another layer of complexity comes from the diversity of workloads. Some data centres may experience rapid growth due to new contracts with cloud service providers, AI companies, or government entities, all of which bring different usage patterns and expectations for reliability and power availability. Suppliers that lack visibility into these operational variables risk underestimating both near- and long-term demand.

Traditional Forecasting Models Fall Short

Traditional load forecasting methods rely heavily on historical data. But in the case of a new or scaling data centre, that historical data either doesn’t exist or is misleading. Suppliers must evolve their models to incorporate:

• Interval Data (IDR): Real-time usage data helps track and predict subtle shifts in consumption.
• Advanced Metering Systems (AMS): Enhanced visibility into customer behavior and ramp-up trends.
• Collaborative Planning: Engaging directly with data centre operators to understand build-out timelines and growth plans.

These tools and partnerships help suppliers move from reactive to proactive forecasting, enabling smarter, more profitable decisions.

Additionally, resources like the International Energy Agency's reports on data centre efficiency and the U.S. Department of Energy's data centre energy use assessments offer valuable context and benchmarking to guide more precise planning.

As part of proactive planning, suppliers should also develop scenario-based forecasting techniques that explore multiple demand pathways, factoring in variables like policy shifts, hardware upgrades, and regional growth strategies. This approach can help mitigate the uncertainty that comes with AI-related expansions and variable deployment timelines.

Hedging and Risk Management in the Age of AI Demand

The volatile nature of data centre growth demands a rethinking of risk strategies. Block hedging is one effective way to minimize exposure to unexpected demand spikes. It allows suppliers to lock in prices for specific volumes over time, providing some stability even when usage fluctuates.

However, the key is in the contract design. Energy contracts must be priced and structured to accommodate growth periods and the unpredictability of new facilities. That means:

• Including flexible pricing mechanisms for usage above baseline projections.
• Allowing for periodic contract reviews or reforecasts.
• Clearly defining risk-sharing terms in cases of dramatic load changes.

Data centres that can participate in demand response programs offer another potential lever. But due to their need for continuous uptime, this isn’t always realistic. Suppliers must assess each facility’s operational model to determine whether DR programs can truly be part of the strategy.

Another avenue for risk mitigation is leveraging AI-based analytics platforms that help suppliers track real-time performance metrics and predict future consumption based on correlated variables like regional AI adoption, new construction permits, or even labor market trends in tech-heavy areas. This level of granular insight can give suppliers a significant competitive edge.

Suppliers Must Work Closely with Data Centre Operators

No forecasting model can replace real-time insight from the customer. Energy suppliers that foster strong communication with data centre operators gain a critical edge. Discussions about…

• Expected usage patterns,
• Planned expansions,
• And backup generation capacity

…can inform contract terms and load planning in meaningful ways.

These partnerships also help identify red flags early, like major construction delays or sudden changes in demand strategy, which can dramatically affect load forecasts and profitability.

Suppliers should consider establishing quarterly or biannual review meetings with data centre partners to align on upcoming changes and share forecasting assumptions. Formalizing this communication loop strengthens trust and improves visibility for both parties.

Regulatory Pressures and the Need for Agility

As energy demand from AI and digital infrastructure grows, so too does the regulatory scrutiny. Governments and utility commissions are adjusting policies to accommodate the environmental and grid implications of data centre expansion.

For suppliers, that means staying ahead of new compliance requirements is essential. Penalties, pricing disadvantages, or missed incentive opportunities can cut into margins quickly. Agility here is a competitive advantage: the faster a supplier can adapt to new policies, the more resilient their business becomes.

Useful resources include the EPA ENERGY STAR program for data centres and regional guidance like the California Public Utilities Commission's page on data centres and electrification.

Suppliers should also keep a close eye on evolving emissions regulations, especially in jurisdictions prioritizing net-zero commitments. Understanding how incentives, penalties, and reporting requirements are structured can help energy companies stay compliant while maximizing ROI on sustainable energy contracts.

Preparing for a Future That’s AI Driven and Fuled by Data Centres

The rise of data centres represents both a challenge and an opportunity for energy suppliers. Those who cling to outdated forecasting methods and rigid pricing models will struggle to keep up. But suppliers who embrace advanced metering, invest in customer partnerships, and rethink their risk management strategies will be well-positioned to thrive.

As AI continues to push demand upward, energy suppliers must become just as innovative as the technologies they power. The data centre surge is here to stay—and for those ready to adapt, it could become one of the most significant growth drivers of the decade.

Long term, success will hinge on marrying real-time data insights with agile pricing and regulatory awareness, creating a flexible strategy that evolves in lockstep with one of the most transformative technological shifts of our time.

If you’re ready to adapt your forecasting capabilities and create more agility in your energy supply business, we’d love to show you what Risk360 can do.