The most underrated technology news story of 2025 is that AI has turned electricity into a competitive advantage.
An investment industry report published in December described AI as a central driver for demand in power, land, and grid interconnection, noting projections that global data-center electricity consumption could more than double by 2030. The exact numbers vary by forecast, but the direction is clear: compute growth is colliding with permitting delays, transformer shortages, and the reality that grids don’t scale on software timelines.
And then came the headline that made the strategy explicit: Alphabet’s reported acquisition of Intersect Power for about $4.75 billion, described as a move tied to data centers and energy infrastructure framed as part of a push to secure reliable power supply for AI growth.
Whether you view it as vertical integration or defensive logistics, the message is the same: the bottleneck for AI isn’t only model quality. It’s power availability.
This is a fundamental shift from the previous cloud era. The 2010s cloud race was about who could build data centers and lease server capacity. The 2025 AI race is about who can build data centers and guarantee multi-gigawatt power delivery and secure grid interconnections quickly enough to monetize demand.
That changes behavior across the whole stack:
- Tech companies pursue long-term power purchase agreements.
- Data center developers become quasi-utilities.
- Regions with cheap and abundant electricity become strategic assets.
- Governments start treating data centers like national infrastructure.
In practice, you can see this in how data center discussion has matured. One industry trends piece described the sector as being “forced into adulthood,” arguing data centers can no longer behave like passive grid customers. The emphasis is on power independence and policy alignment.
The economic consequences are enormous. If AI demand grows faster than power delivery, you get a “compute premium”: the organizations that secure early power and interconnection win disproportionate market share, while latecomers pay more for capacity or wait longer to deploy.
This also changes where AI gets built. It’s not just “where are the engineers?” It’s “where is the power?” That can shift investment toward regions that offer fast permitting and grid upgrades. The geopolitical undertone is obvious: if power scarcity determines AI leadership, then energy policy becomes technology policy.
The irony is that AI itself is often marketed as a tool to optimize energy systems—smart grids, better forecasting, reduced waste. Yet in the short run, the industry’s growth makes the grid constraint worse. That’s why corporate strategy is moving toward controlling more of the energy pipeline, not just optimizing consumption.
Alphabet’s Intersect move (as reported) is a perfect example because it’s not “buy more GPUs.” It’s “buy the ability to power the GPUs.”
This power story also connects to regulation and public sentiment. Data centers are not universally loved. Communities worry about water use, land use, and “who gets the electricity” when households face high bills. If AI firms are perceived as soaking up grid capacity while ordinary consumers pay more, political backlash becomes likely. That’s one reason companies increasingly say they want to build power without shifting costs onto other grid customers.
So what does this mean for “technology news” in 2026?
- Expect more energy deals disguised as tech deals.
Acquisitions, joint ventures, and long-term contracts with power developers will become routine. - Expect AI cluster announcements to include megawatts.
It won’t be impressive to say “we have X GPUs” without saying “we have Y MW secured.” - Expect regulation to follow.
Governments may create special permitting lanes, energy requirements, or grid cost-sharing rules for large data centers. - Expect the AI race to reward boring excellence.
Not the flashiest demo rather the company that can deliver stable, low-cost inference at scale without being throttled by power scarcity.
In a sense, the AI revolution is dragging technology back into the physical world. Software can scale instantly; electricity cannot. The companies that win will be the ones that treat electrons like a strategic input not an afterthought.