Energy companies are being asked to deliver more with roughly the same people. Demand is rising, the grid is being rebuilt, and the skilled field roles that do the work are among the hardest to fill. That combination makes the routine work around the field, the calls, tickets, work orders and reports, a natural place for AI to help.
Demand is rising
In January 2026, the U.S. Energy Information Administration forecast that U.S. electricity use would grow about 1% in 2026 and about 3% in 2027, and named the driver plainly: increasing demand from large computing centers such as data centers.
After years of flat demand, that growth lands on utilities, transmission builders and energy service companies all at once.
The workforce isn't growing as fast
The Department of Energy's latest U.S. Energy and Employment Report found that energy employment fell about 1% in 2025, to roughly 8.4 million jobs. Transmission, distribution and storage was the only major sector to grow, adding about 28,000 workers to reach 1.5 million. Employers reported particular difficulty filling construction, installation, repair and electrically skilled roles, exactly the people who keep projects and the grid moving.
When the people who do the work are scarce, every hour they spend on paperwork, hold queues or hunting for a procedure is an hour taken from the work itself.
Where AI helps today
The best uses are unglamorous and close to operations:
- Customer contact during outages. A voice agent answers the surge of calls during a storm, gives callers the outage status and restoration estimate from your outage system, and routes any safety report, like a downed line, straight to a person.
- Field tickets and work orders. Document processing turns photographed tickets, field notes and permits into structured records, checks them against contracts and flags exceptions before billing.
- Knowledge for newer crews. An internal copilot answers questions from standards, procedures and equipment manuals with a citation to the source page, so experienced staff aren't the only way to find an answer.
- Recurring reports. Automation pulls data from operations systems into the reports that are rebuilt by hand every week or month.
Where it shouldn't decide
Energy work is safety-critical, so the line matters. AI should inform and prepare, while qualified people decide and act on anything involving switching, safety or regulatory sign-off. In practice that means:
- Safety-related calls and reports always escalate to a person immediately.
- Copilot answers cite their source, so crews can check the procedure itself.
- Every automated step is logged and reviewable.
- Systems that touch operational data are deployed within your security boundary, not on a public tool.
Where to start
Pick a workflow that is high-volume, well documented and low-risk to get wrong: outage and billing calls, field ticket processing or a procedures copilot for one team. Measure the baseline, launch with a human review step, and expand only once the numbers hold.
If you operate in oil and gas, power or energy services, we're happy to walk through what this looks like for your crews.
