By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel is divided on the impact of AI-driven power demand on natural gas prices by 2028. While some argue it could create a supply deficit and benefit producers, others question the timing, demand growth, and potential for renewable alternatives to reduce gas demand.
Risk: Hyperscalers' direct PPAs for nuclear and renewables could strand gas peaker economics and leave producers with uneconomic volumes.
Opportunity: Accelerated LNG export terminal approvals under 'AI sovereignty' could drain domestic gas supply and spike Henry Hub prices.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
The market has been razor-focused on soaring oil prices this year, and rightfully so. But not paying attention to the broader energy landscape would be a mistake and potentially a missed investment opportunity.
That’s according to Chronometer Partners Chief Investment Officer Matthew Smith, who says there is a huge emerging opportunity in natural gas.
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Smith’s argument is built on the thesis that, as power demand increases due to an oil crunch and the needs of artificial intelligence, natural gas will quickly become the best game in town.
Here are the stocks to buy before that happens.
Image source: Getty Images.
Smith sees natural gas exports in the U.S. ramping from 15 billion cubic feet (Bcf) per day to 35 Bcf by the end of 2030. Smith also expects current excess supply to dwindle and there to eventually be a 5 Bcf deficit of natural gas per day “before the full force of AI demand.”
“Natural gas, which [represents] over 40% of U.S. power generation, is imminently going to become the most important fuel in the country,” Smith said on a recent podcast, according to MarketWatch.
“Gas has lulled everybody to sleep, but what happens is these structural things start to fall into place in 2027-2028, and we start to draw [down] meaningfully in the middle of 2028.”
Interestingly, according to Henry Hub natural gas spot prices provided by the U.S. Energy Information Administration, prices per million British thermal units (BTU) have dropped from $3.62 per million BTU in February to $3.15 in June.
Smith believes that the demand for AI-driven compute, particularly among hyperscalers, could double or triple.
Smith recommends several ways to play this looming natural gas crunch.
U.S. natural gas producers like Expand Energy (NASDAQ:EXE) and Range Resources have quick access to natural gas and can therefore more quickly ramp production, according to Smith.
Smith also thinks other renewable energy sources, such as solar and nuclear, could see increased demand, as they are among the few logical ways to counter higher electricity prices.
“… The only viable solution is to build large-scale nuclear as fast as possible, which would mean it needs to come on in 2033 or 2034,” Smith said.
He thinks a larger nuclear company like Cameco could potentially get up and running in that time frame. Solar stocks Smith likes include XPLR Infrastructure and Clearway Energy.
Ultimately, I agree with Smith’s view that natural gas and other alternative sources of energy could be a good place to park some capital.
What the Iran war has shown many people and investors is that there’s likely to be greater emphasis on domestic energy production and alternative energy, if nothing else, for national security.
Iran’s greatest weapon in this war has been the ability to close the Strait of Hormuz, through which one-fifth of the global oil supply travels daily under normal times.
This has made Americans, who are largely removed from war, feel the pain in their finances.
I also think that regardless of what happens with AI, power demand is likely to move higher because the electric grid has seen very few updates in decades.
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Bram Berkowitz has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Cameco. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Natural-gas tightness from AI is plausible but far from certain given production elasticity, policy risks on LNG, and accelerating non-gas supply options that the article underweights."
The article argues that surging AI-driven power demand will tighten natural gas supply by 2028, lifting prices and benefiting producers like EXE and RRC, plus nuclear (CCJ) and solar (XPLR, CWEN) plays. It cites exports rising from 15 to 35 Bcf/day and a potential 5 Bcf daily deficit. However, it glosses over that US natural-gas production has repeatedly outpaced even aggressive demand forecasts, LNG export capacity additions face regulatory and NIMBY delays, and power-generation mix is shifting faster toward renewables + batteries than the piece admits. Current Henry Hub spot at ~$3.15/MMBtu already reflects ample supply; a structural bull market requires both AI capex and data-center buildout to hit forecasts simultaneously.
The strongest case against is that hyperscaler power demand may be met disproportionately by new renewables, nuclear restarts, and behind-the-meter generation rather than gas-fired peakers; meanwhile, associated gas from Permian oil drilling keeps flooding the market, preventing the forecasted 2028 deficit and leaving producers with stranded volumes at sub-$4 gas.
"The transition to AI-driven compute will force a structural re-rating of natural gas from a volatile commodity to a critical, long-term baseload utility asset."
The thesis that AI compute demand creates a structural floor for natural gas is compelling, but the market is ignoring the regulatory and transmission bottlenecks that prevent supply from meeting demand. While Expand Energy (EXE) and Range Resources (RRC) have the reserves, they face massive capital expenditure hurdles and potential ESG-related financing constraints. Furthermore, the article conflates AI power needs with general grid modernization; the former requires 24/7 baseload power, which solar cannot provide without massive battery storage scaling. I am bullish on the sector but wary of the timeline; 2027-2028 is a long horizon for a market currently obsessed with immediate quarterly earnings beats.
The 'natural gas crunch' may be mitigated by rapid advancements in localized modular nuclear reactors (SMRs) or massive efficiency gains in GPU power consumption that render current demand projections obsolete.
"Natural gas prices and forward curves show no evidence of the supply crisis the article predicts, suggesting either the thesis is wrong or the market is massively mispricing a 2027-2028 event—neither is a compelling buy signal today."
The article conflates two separate dynamics—AI power demand and natural gas supply tightness—without proving causation or timing. Smith's 2027-2028 inflection is oddly specific but unsubstantiated. More critically: Henry Hub prices are DOWN 13% since February despite the thesis. If natural gas is truly about to crater in supply, why aren't forward curves pricing in scarcity? The article also ignores that hyperscalers are aggressively building solar + battery + nuclear directly, reducing spot market exposure. Natural gas may benefit from grid baseload needs, but framing it as an AI-driven 'crunch' feels like retrofitting a bullish narrative onto a commodity that's currently in oversupply.
If AI compute demand truly doubles or triples by 2028, and natural gas provides 40% of U.S. power, then even modest demand acceleration could exhaust spare capacity faster than Smith's timeline—and the market would front-run this via futures curves, which today show only modest backwardation.
"AI-driven gas demand alone is unlikely to create a reliable, sustained supply deficit for US natural gas."
The article bets that AI compute will become a multi-year gas demand driver and trigger a US supply deficit by 2028-2030. That thesis rests on several uncertain levers: hyperscaler demand scaling, meaningful LNG export capacity growth, and sustained higher power demand versus efficiency gains. Gas demand could be capped by renewable integration, price signals, and policy shifts; storage/seasonality could smooth any spike. Even if gas outlays rise, the magnitude of a 5 Bcf/d deficit by 2030 implies a massive capex cycle and permitting win that may not occur. The picks (EXE, Range Resources) are commodity cyclicals with high leverage and volatile cash flows, not a guaranteed path to alpha.
Even if the AI compute boom materializes, gas demand may grow only modestly and be swamped by renewables and efficiency; a deficit scenario is unlikely without a prolonged, costly infrastructure push.
"Hyperscaler PPAs for nuclear/SMRs risk economically stranding new gas capacity even if nominal demand grows."
Claude correctly flags that forward curves show only modest backwardation, yet ignores how LNG export delays have repeatedly masked domestic tightness. The real unmentioned risk is that hyperscalers' direct PPAs for nuclear restarts and SMRs could strand gas peaker economics faster than any 2028 deficit emerges, leaving EXE and RRC with contracted but uneconomic volumes.
"The AI power narrative will be weaponized to accelerate LNG export permitting, creating artificial domestic supply tightness."
Claude is right about the forward curve, but both Claude and Grok miss the geopolitical leverage here. The 'AI power' narrative is a convenient cover for the industry to push for faster LNG export terminal approvals. If the DOE accelerates permitting under the guise of 'national security/AI sovereignty,' we could see a massive supply drain regardless of domestic grid efficiency. The risk isn't just demand; it's the policy-driven export of that supply, which will spike domestic prices.
"Policy-driven LNG export upside requires proof in futures curves; the immediate threat to gas producers is hyperscaler PPAs locking in non-gas power, not a 2028 deficit."
Gemini's geopolitical angle is underexplored but cuts both ways. Yes, DOE permitting acceleration under 'AI sovereignty' could drain domestic gas via LNG exports—spiking Henry Hub prices and benefiting producers. But that's a policy bet, not a market bet. The real tell: if this were credible, LNG futures (QBB) would already be pricing in terminal approvals. They're not. Grok's stranded-peaker risk is sharper: direct hyperscaler PPAs for nuclear/SMRs *already* undermine gas baseload economics without waiting for 2028.
"Policy/export bottlenecks can lift domestic gas prices and undercut a long, 2028-focused bull case."
Claude's pricing skepticism is valid, but the real swing factor is policy/export risk. If the DOE accelerates LNG approvals or terminals clear faster than expected, domestic gas is priced to reflect export demand even without a 2028 deficit. Bottlenecks in FERC permitting, ship schedules, and local opposition can still tighten supply intermittently, lifting Henry Hub and pressuring cash flows for E&Ps. This makes the bull case more fragile and episodic than the article implies.
The panel is divided on the impact of AI-driven power demand on natural gas prices by 2028. While some argue it could create a supply deficit and benefit producers, others question the timing, demand growth, and potential for renewable alternatives to reduce gas demand.
Accelerated LNG export terminal approvals under 'AI sovereignty' could drain domestic gas supply and spike Henry Hub prices.
Hyperscalers' direct PPAs for nuclear and renewables could strand gas peaker economics and leave producers with uneconomic volumes.