By Duncan Wood
The U.S. has spent the past decade reshaping global energy markets. It became the world’s largest producer of oil and natural gas. It emerged as a leading LNG exporter. It expanded renewable generation at record pace.
This is what energy dominance looks like in practice: abundant supply, export strength, technological leadership, and resilience across fuels. But sustaining that dominance now depends on something less visible than drilling rigs or export terminals. It depends on permitting speed.
The U.S. does not lack energy resources. It does not lack capital. It does not lack technological innovation. What increasingly constrains deployment across hydrocarbons, electricity, critical minerals and infrastructure is the time it takes to move projects from proposal to approval.
Artificial intelligence offers a way to change that; not by weakening environmental standards, but by modernizing the process used to apply them.
Energy Dominance Requires Infrastructure Dominance
Getting things built is essential to achieving a modern and responsive energy system. Oil and gas production depends on pipelines, gathering systems, and export terminals. LNG exports depend on large-scale federal approvals. Offshore development requires environmental review and leasing coordination. Refining expansions require multi-layered regulatory signoff.
The electricity sector faces similar constraints. Rising power demand from advanced manufacturing, data centers, electrification, and industrial growth requires new generation and expanded transmission capacity. Yet transmission projects can take a decade or more from concept to completion.
Energy dominance is not simply about resource abundance. It is about the ability to build infrastructure at the speed of market demand. When permitting timelines stretch into multi-year review cycles, projects face higher financing costs, regulatory uncertainty, and litigation risk. Even economically viable projects can stall.
This Is Already Part of the Conversation
Federal officials have begun to acknowledge this reality. Secretary of the Interior Doug Burgum has publicly discussed the potential for artificial intelligence to accelerate environmental reviews and improve permitting efficiency. Agencies are increasingly exploring digital modernization tools that can streamline documentation analysis and interagency coordination.
The objective is straightforward: maintain environmental safeguards while reducing procedural delay. That distinction matters. Faster permitting does not mean weaker oversight. It means applying oversight more efficiently. And that means boosting national competitiveness and economic strength.
Where AI Can Make a Real Difference
Permitting processes contain numerous stages that are data-heavy, repetitive, and administrative in nature, precisely where AI systems perform best.
- First, environmental document review. Major infrastructure projects generate thousands of pages of technical studies and cross-referenced analyses. AI tools can quickly identify inconsistencies, verify citations, flag missing mitigation measures, and ensure compliance with statutory requirements. This reduces revision cycles and strengthens the administrative record, lowering litigation vulnerability.
- Second, interagency coordination. Energy projects frequently involve Interior, Energy, EPA, the Army Corps of Engineers, state regulators, and local authorities. AI-enabled tracking systems can monitor deadlines, route technical questions to subject-matter experts, and identify overlapping requirements early in the process. That replaces sequential bottlenecks with parallel visibility.
- Third, public comment processing. Large LNG terminals, pipelines, or generation facilities often receive thousands of public comments. AI can cluster themes, categorize issues, and map concerns directly to sections of environmental reviews within hours rather than months. Agencies can then focus on substantive engagement rather than manual sorting.
- Fourth, spatial and grid modeling. For the electricity sector, AI-driven geospatial tools can rapidly evaluate transmission routes, generation siting options, reliability impacts, and environmental constraints at early stages, reducing costly redesign later.
The Electricity Challenge
Electricity demand in the U.S. is rising again after years of relative stagnation. AI computing facilities, semiconductor manufacturing, advanced industrial processes, and electrification are all increasing load. In fact, most of the focus on the link between AI and energy has focused on that rapidly rising demand curve.
Meeting that demand requires not only generation across natural gas, nuclear, renewables, and emerging technologies, but also expanded transmission capacity. Yet transmission remains one of the slowest-moving parts of the energy system.
If permitting timelines for transmission projects can be shortened, even modestly, the benefits cascade through the system: improved reliability, reduced congestion costs, faster integration of new generation, and stronger economic growth. Energy dominance in the next decade will be measured not only in barrels and cubic feet, but in megawatts delivered and electrons moved efficiently across regions.
A Productivity Reform, Not a Policy Shift
Using AI in permitting should be understood as a productivity and efficiency reform inside government. It is about reducing paperwork redundancy, improving document quality, accelerating coordination, and strengthening transparency: human judgment remains central; environmental protections remain intact; public participation remains essential.
But if the U.S. can responsibly reduce permitting timelines from years to months in key stages it would lower project costs, increase investment predictability, and accelerate infrastructure deployment across the hydrocarbons and electricity sectors alike. That directly supports the goal of sustained energy dominance: abundant production, reliable power supply, export strength, and industrial competitiveness.
The Strategic Opportunity
America currently leads the world in artificial intelligence innovation. Applying that innovation to modernize its own regulatory infrastructure is both logical and overdue. If the U.S. can align its permitting systems with its technological capabilities, it can reinforce its position as the world’s leading energy power, not by cutting corners, but by cutting unnecessary delay.
And in today’s energy landscape, speed is strength.
Duncan Wood, PhD North America Fellow, Wilson Center & CEO, Hurst International Consulting.
This article was originally published by RealClearEnergy and made available via RealClearWire.
With a sensible thought through energy policy…
AI Can Help Deliver America’s Next Phase of Energy Dominance
In de-development UK it’s a very different story. In true Luddite fashion AI has become a real bête noire for UK alarmism. They love what it does, one can only conclude that this is another case of if only the server farms were somewhere else. That’s how emissions usually come down.
Datacentre developers are facing pressure to reveal whether their projects will increase the UK’s net greenhouse gas emissions, amid concerns the sites could double national electricity demand.
Developers should demonstrate that their projects will not cause an increase in the UK’s overall CO2 emissions or local water scarcity, as part of a forthcoming national policy statement (NPS) on datacentres
…
Datacentres planned for Elsham in Lincolnshire and Cambois in Northumberland will each have an electricity demand of 1GW, equivalent to the output of a nuclear power station, the letter says, which will need to be matched by new, renewable energy output.
…
“Datacentres will increasingly be powered by renewables and our AI energy council is exploring opportunities to attract investment in new clean power sources for the industry, while the planning system takes water scarcity into account,” the spokesperson said. – The Guardian
Incredibly, official faith remains in intermittent energy sources. With the amount of rain we’ve had over the winter any shortage of water is a failure to build reservoirs to contain it.
Big Tech won’t be relying on unreliables.
4 companies considering using nuclear power for AI processing
Microsoft
Google
Amazon Web Services
Oracle
TechTarget
Why oh why are they not putting their faith and money into renewables?
““Datacentres will increasingly be powered by renewables…..”
I wonder how many square miles of solar panels would be needed for a data center?
First, it would have to be a data center that is only operating from about 10AM to 2PM, less than that in winter…
Overall, a good point is being made here about the review processes that can be accelerated.
BUT it is a mistake, for meeting electricity demand, to sweep “renewables” – i.e., wind + solar + massive battery support for grid supply – into the same category of generation technologies as natural gas and nuclear.
“Meeting that demand requires not only generation across natural gas, nuclear, renewables, and emerging technologies, but also expanded transmission capacity.”
Accelerating unreliable, weather-dependent, material-intensive, and land-hungry options along with reliable sources is a drag on energy dominance.
There. Be careful what you wish for.
That is all for now.
Wait. One more thing. Coal. Don’t count it out.
a drag
That kind of sums up the entire neo-feudalist (globalist) effect on human flourishing.
Yeah, man. The Eco-Nazis are a drag.
SV & WTG have niche applications. So of those connect to the grid.
It is not those technologies in and of themselves that are causing blackouts.
It is the political policies of trying to run the whole shebang with just those.
As a supplement to the grid where the % does not cause instability, once build when, when they are able to supply electricity, it can,, can reduce fuel costs. There possibly, given the right approach, be a benefit.
That aside, the obscene bird choppers and environmentally devastating WV farms and all the wildlife and plant life damage inflicted should be, and possible might be highlighted by AI, given it is allowed to be honest.
Do not get me started on a rant that disparages battery farms. I am too eager.
I’ll file this under “great minds think alike.” 😉
Any process that increases the speed of permitting non-“renewable” energy generation won’t happen. Such things would be tied up in courts for years.
So an AI court system is also needed.
Guilty. (Puts on digital black cap…)
OMG.
I was going to say the same thing but you beat me to it. Gang green will fight sped up permitting systems tooth and nail.
Excellent use of AI. “Permitting processes contain numerous stages that are data-heavy, repetitive, and administrative in nature, precisely where AI systems perform best.” I bet all the choke points have already been pointed out but with all the hype around AI I also bet they’ll pay attention this time around.
“numerous stages that are data-heavy, repetitive, and administrative in nature, precisely where” a person with connections can hide a low-energy relative to complain when their email inbox gets full. Not going away.
Hopefully it can be done in parallel with reform or bypass of the world’s worst educational and health insurance admin.
Story tip – from an unwittingly unreliable ally
Trump Tells Starmer: “Open Up the North Sea Immediately”
…to combat soaring energy prices triggered by the US-led war with Iran. – Daily Sceptic
Keir will check with his muslim sectarian bloc vote and get back to you, Don….
You don’t really need AI, you just need anti-stupidity in governance.
“This is what energy dominance looks like in practice…”
I like the term “energy dominance”. But, I know too many libs here in Wokeachusetts. To them, it sounds mean- you know, like bullies or women beaters. They need to grow up.
“Yet transmission projects can take a decade or more from concept to completion.”
With all the $$$ being spent on AI, time to buy better politicians! It would only cost nickles and dimes compared to the money spend on data centers and AI. 🙂
“America currently leads the world in artificial intelligence innovation. Applying that innovation to modernize its own regulatory infrastructure is both logical and overdue.”
Government will be the last segment of our civilization to use AI. At least that’s my opinion watching the state of Wokeachusetts and its excessive bureaucracy- which has no motivation to be more productive. They become less so every year. Unless we can get better politicians. Not sure if Trump is moving this along in the federal bureaucracy- I hope he is. But some states just keep getting worse. I’ve talked to some people in my state’s agencies and they barely know AI exists. To master AI you have to work hard at it to determine how it can be one of your best tools in your tool box. Too much work for the agency people I know.
Okay, I’m going to go out on what I think is a very short branch and say – “AI is going to under perform.”
Maybe, possibly, with AI used to increase efficiency of paperwork, a lot of the government bloat can be trimmed.
Parkinson’s laws will continue to apply regardless of AI
A. Work expands to fill the time allotted.
B. Expenditures rise to meet income.
C. Staff in any administrative department increases at a rate unrelated the state of whatever, if anything, is being administered.
Knowing government, they’ll just generate the bloat faster.
I like the idea of using AI to streamline the process. But AI requires human supervision. AI has to be built by humans, trained by humans and monitored by humans. Hallucinations are an on-going issue. AI is just as limited by GIGO as any other computer program.
AI can handle many of the routine tasks. Repetitive, rule-based processes are where AI automation flourishes. We must avoid the temptation to turn over approvals and denials to AI. Humans must remain in charge.
“Using AI in permitting should be understood as a productivity and efficiency reform inside government. It is about reducing paperwork redundancy, improving document quality, accelerating coordination, and strengthening transparency: human judgment remains central; environmental protections remain intact; public participation remains essential.”
While this is true, it occurred with the use of a computer system that allowed the availability of more rapid and thorough information. It needs to be more clearly shown how this could be an improvement and not worse. Potential problems require a lot more than recognition. We already saw that in many scientific papers before AI.
Permitting is not the critical path. Hardware delivery is. Large gas turbines are sold out for several years in advance. Buying one today puts you on a multi-year wait list (as much as 5 years). Steam turbines much the same. Large power transformers were 60+ weeks delivery even in the best of times. I am sure that that supply chain is impacted also. If the power plant requires a new gas lateral or railroad connection (coal), that can be a multi-year schedule for right-of-way acquisition and pipeline build-out, especially if new compression is required and especially if that compression is gas turbine driven. Even meter station hardware in typically more than a year’s lead time.
AI isn’t going to help with any of that.
Story Tip.. Farmers left with the clean-up bill.
‘Farmers to pay’ | Premier Chris Minns’ confession on abandoned renewables projects
I don’t mean to be a wet blanket, but there are things AI just can’t do.
First, the electric grid has two main components, transmission and distribution. Transmission is from the power plant to an interconnection point on the distribution network. You can’t just plop an AI center down wily nilly in the distribution network and expect the distribution network to have the capacity to serve it. Thats why many are looking at their own dedicated power plants that are colocated.
Second, large transmission lines are a nightmare to plan. Property rights must be addressed. This involves land owners, politicians, courts. AI has a long way to go to be able to find negotiated settlements agreeable to all.
Lastly, AI cannot speed manufacturer of wire, steel, transformers, switches, insulators and all the infrastructure needed to add transmission and distribution hardware needed to supply the AI itself. Much of this already have lead times in years. This doesn’t begin to address the issue of trained experts needed to properly build all of this.
I would like to add that I watched blades and other turbine structures being offloaded at Harbor Island, the closest to the Gulf possible of the Corpus Christi Texas area. Currently they are exporting from more inland harbor lots of gas, not the liquid. Also transport of blades seemed a joke requiring escorts, going through small towns, including the first, Aransas Pass, and one got hit by a train in Luling. How will AI speed up ship deliveries? With lots of experience on smaller vessels I wouldn’t want to be on these huge ships in high seas any faster, bad enough as it is now. Not all but careless computer promoters promised less paperwork but I am sure we got more, has anybody studied it?
A joke some 60 years old. At that time, the word was “computer”, not “AI”. The computer was tasked to design a ship to transport cargo between the U.S. and Europe, with a minimum fuel consumption. The computer designed a ship with zero fuel consumption, and three thousand miles long.
Uh, NO.
There is no “need” for “renewables,” they are nothing but a parasite on the system. Ditto for any “emerging technology” that has “reducing (meaningless) CO2 emissions” as one of its “goals,” since that will be another parasite.
And COAL should be in the mix as well. There is nothing wrong with using coal given modern pollution control equipment, the US has plenty of it, and it’s a great companion to gas. Better for baseload than gas, since it can be stockpiled unlike gas.