A decade ago, a Deloitte brochure declared, _“Every company is an energy company, and if it’s not now, it will be soon.”_ That statement is proving truer than ever. AI is rapidly transforming industries, but its insatiable hunger for power has exposed a growing disconnect between the cost of a watt and the value of the bits produced by those watts. I call this the **Watt-Bit Spread**, and it’s wider than ever. The AI revolution isn’t just about smarter algorithms; it’s about energy economics, power markets, and a mismatch between supply and demand that threatens to slow innovation. ### 1. AI’s Insatiable Energy Demand 💡 The AI boom is fueled by an economic imperative: **maximize throughput**. Companies are racing to train ever-larger models, with power-hungry GPUs operating at unprecedented scales. This creates an urgent need for power **now**, not years down the road. Power delivered in 2027 is worth exponentially more to AI firms than power in 2030, making access to energy a key competitive advantage—just as cloud infrastructure was in the last tech wave. [[Needs of Hyperscaler Offtakers - Maximizing Compute Capacity at Scale and Speed]] ### 2. Utilities Are Stuck in a Different Timeframe ⏳ Unlike AI companies, utilities operate under a **minimize overhead** model. Their goal isn’t to chase rapid growth but to provide stable, cost-efficient electricity under strict regulatory frameworks. In their world, an electron delivered in 2027 is worth the same as one in 2030. This fundamental mismatch between **AI’s time-sensitive energy demand** and **the utility sector’s slow-moving investment cycles** creates a market inefficiency where the true value of power is not reflected in pricing. ### 3. The Market Response: Bypass the Grid ⚡ To sidestep this issue, many data center operators are seeking to generate their own power, cutting utilities out of the equation. But this isn’t a real solution—gas and other energy providers are **also** bound by the same regulatory and economic constraints. The result? A patchwork of short-term fixes rather than a grid-scale strategy to meet AI’s demands sustainably. ### So What? The Grid Must Evolve 🔄 The AI energy challenge is not just a corporate problem—it’s a **grid-scale problem** that demands grid-scale solutions. The technology exists to help—**grid-enhancing technologies, long-duration storage, superconductors**—but the regulatory and economic models must catch up. If utilities can capture some of the premium AI companies are willing to pay for power, they can accelerate investments and **modernize the grid for all users**. The AI revolution isn’t just reshaping computing—it’s forcing us to rethink how we value and distribute electricity. If we get it right, we could be on the cusp of the most significant energy transformation in a century. 🚀 --- [[Future of Energy Storage]] | [[Data Centre Energy Demand]] | [[How AI Will Impact Energy Demand]]