The U.S. Department of Energy’s current AI-and-grid agenda describes a buildout that is larger, faster, and more interdependent than a conventional capital program. DOE is aiming to apply AI across planning, interconnection, operations, and security, while a July 2026 partnership pairs an anticipated 1.8-gigawatt AI and high-performance-computing campus with new generation, transmission, and up to 2.6 gigawatts of battery storage. Storage, supply chains, permitting, cybersecurity, rate design, and community legitimacy all become part of the same delivery problem.
That is why the energy transition is not only a technology or investment thesis. It is an operating model challenge: can the organization make decisions across assets, markets, regulators, communities, suppliers, and data without losing the thread of reliability?
The 2035 target changes the shape of leadership
An organization can manage a solar project, a transmission program, or a storage portfolio as a series of individual initiatives. It cannot manage the transition that way. The value of each project depends on the network around it: interconnection queues, transmission availability, flexible demand, market rules, workforce capacity, and the ability to operate through volatility.
The leadership question moves from “Which asset should we build?” to “What decision system lets us keep the portfolio coherent as assumptions change?” That system needs a shared view of dependencies, a clear escalation path, and measures that balance cost, reliability, speed, resilience, and public value.
The hidden work is coordination
The most expensive delays are often not caused by a missing technology. They arise when functions optimize locally: engineering advances a design while permitting is unresolved; procurement commits to a supplier without a resilience scenario; finance measures project return without valuing optionality; operations inherits a system no one has rehearsed under stress.
We recommend a transition control surface with four connected views:
- Portfolio: which investments advance the strategic pathway and which dependencies could stop them?
- System: how do generation, transmission, storage, demand, and digital control interact?
- Stakeholders: what evidence do regulators, communities, customers, and partners need to support the next decision?
- Readiness: can the people and processes operate the capability safely on day one?
A more useful definition of resilience
Resilience is not simply the ability to recover after an outage. It is the capacity to preserve critical service while the system is changing. That means designing for degraded modes, clear authority, observable dependencies, and an operating rhythm that learns from near misses before they become public failures.
The same logic applies to data. A grid modernization program needs trusted asset data, interoperable interfaces, and decision-quality telemetry—not another dashboard that cannot be connected to an action. Inference from DOE’s planning horizon: digital governance and change management should be funded as core infrastructure, because they determine whether physical infrastructure can be coordinated at the required pace.
What leaders can do now
Start with the decisions that will become irreversible in the next 12–24 months. Map the dependencies, evidence, owners, and failure modes around each one. Then run a small cross-functional release that proves the organization can move from scenario to decision to operational learning.
Global Enterprise helps infrastructure leaders connect strategy, operating model, data foundations, and change architecture. The goal is not to produce a more elegant transition plan. It is to build the management system that can carry the plan through uncertainty.