The grid was not designed for the pace of hyperscale data center deployment, workloads that can double a facility's power draw with a software update, or demand growth that moves on a timeline measured in months while the infrastructure required to serve it is measured in years.
What's less often said—but what the data and the regulatory record make clear—is that the grid's limitations today are as much regulatory as they are physical. The wires and transformers are part of the constraint. So are the rules, timelines, and coordination mechanisms that govern how new load gets connected, approved, and served.
At HData's Let's Go! 2025 conference, Peter Shaw (Director of Energy, Sustainability and Infrastructure at Guidehouse) sat down with Justin Felt (Director of Policy Analysis and Development) and Lila Jaber (former Chairmain and Commissioner at Florida Public Service Commission) to discuss future-proofing the grid for AI and data center growth. While the infrastructure problem presents challenges, the regulatory problem is equally as challenging and, in some ways, harder to solve.
Speed Is the New Constraint
Data centers can come online in one to two years. Generation and transmission assets can take five to seven years or more to permit, site, and build. Although the mismatch isn’t novel, but AI-driven demand growth has made it acute in ways the energy system has not previously had to manage.
Utilities are being asked to deliver power faster than traditional planning cycles allow. Regulators are trying to balance speed with cost allocation, reliability, and ratepayer protection. Developers are facing interconnection timelines and approval processes that were designed for a different demand environment.
The issue is alignment, or the absence of it. When the parties responsible for building, approving, and connecting new load infrastructure are operating on timelines that diverge by several years, projects stall even when the underlying resources exist to support them.
Why Regulation Becomes the Limiting Factor
Grid regulation was designed to optimize for stability. That is a legitimate and important goal. But demand growth driven by AI infrastructure is forcing regulatory systems to operate under conditions they were not built for, and the gaps are showing up in predictable places.
Interconnection queues are backlogged across most major regional transmission organizations. Supply chain constraints are delaying critical equipment, compressing timelines further. And regulatory frameworks that assume relatively static demand profiles are struggling to accommodate load growth that is neither static nor predictable.
The result is a category of project failure that is easy to misread. A well-capitalized data center development with a committed offtake agreement and a willing utility can still stall, not because the grid lacks capacity in any physical sense, but because the regulatory pathway to accessing that capacity does not move at the speed the project requires.
What happens is a coordination failure. And coordination failures are regulatory problems, not infrastructure ones.
The Misalignment Across Timelines
A recurring theme in the Let's Go! 2025 session was that grid stress is not caused by any single failure point. It is the result of misalignment across parties who are each doing their jobs but on timelines that don't fit together.
Data center developers move quickly, because their competitive environment demands it. Utilities plan deliberately, because their capital commitments are long-lived and their obligations to ratepayers are binding. Regulators move cautiously, because the consequences of regulatory error in a monopoly-service environment are borne by parties who had no role in the decision.
Each of those postures is rational. The problem is structural: when the timelines those postures produce diverge too far, the regulatory system becomes a bottleneck rather than a coordination mechanism. Interconnection rules that lag behind new load types, approval processes that assume stable demand curves, and planning frameworks that cannot accommodate interim or hybrid solutions all contribute to that bottleneck, both independently and in combination.
Regulatory innovation in this context means developing mechanisms that allow coordination across parties moving at different speeds, without sacrificing the stability and accountability that make regulatory systems worth having.
Flexibility as a Governing Principle
Across the session's discussion, one concept surfaced consistently: flexibility, or specifically the capacity of regulatory systems to accommodate uncertainty and adapt to conditions that weren't anticipated when the rules were written.
That includes flexible regulatory frameworks that allow interim solutions when permanent infrastructure isn't yet available. It includes flexible resource use that maximizes existing interconnections rather than defaulting to new construction. And it includes flexible planning assumptions that acknowledge, rather than paper over, the uncertainty in long-term demand forecasts driven by AI adoption curves that no one can predict with confidence.
What Forward-Looking Teams Are Doing Now
AI-driven load growth is not a short-term anomaly to be managed through temporary accommodations. It is a structural shift that will reshape demand profiles across the grid for the foreseeable future. The organizations that recognize that early and build their regulatory intelligence and engagement strategies accordingly will be better positioned than those waiting for the regulatory environment to stabilize before acting.
Investment in better load forecasting transparency is crucial, so planning assumptions can be tested against realistic demand scenarios. It means engaging regulators earlier in the development process, before interconnection applications are submitted and before positions have hardened. And it means building the capability to monitor regulatory proceedings—interconnection dockets, IRP filings, transmission planning processes, and rulemaking activity—at the scale and speed that the current environment demands.
As grid challenges become more regulatory in nature, visibility into policy movement becomes the input that separates teams with strategic options from those managing surprises.
The presentation videos at LET'S GO! 2025 are available for download. For more on AI built specifically for the regulatory work of utilities, regulators, advocates, and other energy professionals, visit hdata.com.
About HData
As the AI-native operating system for energy regulation, HData serves the largest customer ecosystem in regulated energy, helping utilities, regulators, advocates, advisory firms, corporates, and energy technology companies navigate regulatory complexity. Through centralized data, domain AI, and purpose-built applications, HData accelerates the research, analysis, and workflows critical to how the future of energy is decided.
