On June 18, 2026, the Federal Energy Regulatory Commission (FERC) issued a directive requiring US grid operators to set aside a fast lane for interconnection requests from data centers dedicated to artificial intelligence. In essence, new AI facilities get priority access to the power grid over traditional infrastructure.
However, the measure has a clear limit: it doesn't address the structural shortage of energy supply. Speeding up connection times doesn't solve the problem of how much electricity is actually available. As a result, data center operators and their customers will still have to deal with supply constraints in the medium term. In particular, tech SMEs that rely on cloud infrastructure or AI-as-a-service offerings could see indirect effects on costs and service availability.
At SHM Studio, we keep a close eye on these regulatory developments because they directly affect the digital value chain of Italian companies. Understanding global infrastructure trends also helps SMEs plan smarter technology investments. In short, the FERC directive is an important signal: AI is now treated as critical infrastructure, with all that implies for political and market priorities.
The FERC directive: a fast lane for AI
On June 18, 2026, the Federal Energy Regulatory Commission (FERC) published a directive that redraws the priorities for accessing the power grid in the United States. Specifically, grid operators must now reserve an accelerated path for interconnection requests from data centers dedicated to artificial intelligence. It's a significant regulatory shift, one that formally recognizes AI as critical national infrastructure.
Until now, grid connection requests sat in queues that often lasted for years. According to US energy industry data, the average wait for a commercial interconnection exceeded three years. The FERC measure aims to clear a bottleneck that has been slowing the growth of AI computing capacity in the country.
The original source, TechCrunch, points out a critical issue, though: the directive doesn't address the structural shortage of energy supply. A fast lane, then, doesn't guarantee that electricity will actually be available.
The unresolved issue: energy supply doesn't grow by decree
The FERC decision speeds up the paperwork, but it doesn't create new power generation capacity. Meanwhile, energy demand from AI data centers keeps growing at a steady pace. According to estimates from the IEA (International Energy Agency), data centers could consume more than double today's energy by 2028.
This imbalance between supply and demand puts pressure on energy prices and could destabilize supply. In addition, regional US utilities have to handle demand peaks their infrastructure was never designed to support. As a result, even with the fast lane, many data center projects could face delays tied to the physical capacity of the grid.
Even so, the political signal is clear: the US administration sees AI competitiveness as a strategic priority. For this reason, the FERC directive is expected to be only the first step in a broader regulatory package.
Immediate impact on the global tech supply chain
US regulatory decisions on energy and infrastructure have a ripple effect across the entire global tech ecosystem. So even Italian SMEs that use cloud services, AI-as-a-service platforms or SaaS infrastructure need to pay attention to these developments.
First, the major hyperscalers, such as Microsoft Azure, Google Cloud and Amazon AWS, have data centers concentrated in specific areas of the US. If these facilities get priority access to the grid, their ability to expand AI services grows. Likewise, European providers that depend on American technology will benefit indirectly from this increased computing availability.
However, there's also a less optimistic scenario. If the energy shortage persists, data center operating costs will rise. As a result, cloud and AI service prices could face upward pressure in the medium term. Italian tech SMEs should factor this into their technology budget planning for 2027-2028.
For example, companies that are considering adopting AI solutions for
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