The Hidden Energy Costs of AI for E&P and Turnaround Planning

AI’s Power Surge: A New Demand on the Grid

Hyperscale data centers (increasingly AI-focused) are expected to consume up to 9% of U.S. electricity by 2030, according to Boston Consulting Group and the International Energy Agency (IEA). That’s more than double today’s levels, and enough to prompt over 80 GW of new U.S. gas generation capacity to enter planning pipelines, as reported by Bloomberg NEF.

Much of this capacity wasn’t even considered on utility roadmaps five years ago and grid congestion in key industrial corridors (Texas, the U.S. Midwest, the Benelux region) is making things worse.

Rising Costs Even If You Aren’t Using More Power

Energy markets are structured to socialize costs. In deregulated markets like ERCOT (Texas), increased grid strain and infrastructure buildout typically show up as:

• Capacity price spikes
• More volatile spot rates
• Higher (power purchase agreement) PPAs for new generation

Meanwhile, in regulated zones, tariffs and connection fees are more likely to rise across the board.

Implications of AI Energy Costs for Turnaround Teams

For energy and process (E&P)  industries, where energy can , these dynamics can no longer be ignored during turnaround planning (U.S Department of Energy).  Key considerations include:

• Electricity will become harder to forecast in multi-year maintenance budgets.
• Digitalization tools (like real-time twins, smart sensors) relying on constant cloud processing may become more expensive to operate.
• Power availability during planned shutdowns may be more constrained.

In short: turnaround timing, peak coordination, and DER strategies may all need a rethink.

CAPEX Isn’t Always A Cost Saver

Ironically, the same AI tools promising smarter, more efficient operations are now indirectly increasing power costs industry-wide. If grid expansions fall behind, the margin impact from rising OPEX could outstrip the productivity gains.

Strategic Takeaways for Turnaround Management

AI is the brain driving digital transformation and electricity is the muscle enabling it. And when that muscle becomes more expensive, it hits the whole value chain. This includes industries that aren’t digitizing fast enough to offset it.

Now is the time to get energy, finance, and operations teams aligned:

• Anticipate electricity cost as a variable input in all turnaround models.
• Prioritize AI implementations that reduce energy load or improve system resilience
• Evaluate on-site generation or long-term contracts to mitigate market exposure

By adjusting planning frameworks today, turnaround teams can remain resilient in an AI-powered future that’s increasingly defined by its energy constraints.

Learn how Cleopatra Enterprise’s Shutdown, Turnaround, and Outage software can help your organization navigate this complexity with data-driven insights and real-time visibility.