AWS launched Agentic Grid Planning on AWS on September 17, 2026, a program that gives utilities access to specialized AI agents to speed up interconnection studies. For operations, real estate, and construction teams, the bottleneck in connecting new energy resources directly affects project timelines, site viability, and load growth planning. Duke Energy, the first collaborating utility, has already cut data preparation tasks from two weeks of manual work to a matter of hours.
The program addresses a growing gap. According to Lawrence Berkeley National Laboratory, more than 2,000 GW of generation and storage were waiting for U.S. transmission interconnection at the end of 2025. Those projects that did reach operation spent a median of more than five years in the queue. In ERCOT alone, requests to connect large loads hit roughly 410 GW in March 2026. Meanwhile, the number of qualified engineers available to perform these studies is not keeping pace with the volume.
How the AI agents work inside existing workflows
The AI agents do not replace existing simulation software or engineering judgment. Utilities continue using the physics-based simulation tools, grid models, scripts, and engineering standards they already trust. The agents run and coordinate study workflows across those tools, handling data preparation, analysis execution, and task sequencing. Engineers direct the study, review the versioned audit trail, and make all final engineering decisions.
Duke Energy engineers provided transmission planning expertise and ongoing feedback during development. Their teams now use the agents to automate key parts of the interconnection study process. The utility aims to increase planner capacity and lay groundwork for expanding these capabilities into large load planning workflows.
"Duke Energy maintains one of the largest utility grids in the United States, and our engineers must complete a higher volume of increasingly complex studies as demand for generation and load grows," said John Pressley, Managing Director of Digital Strategy and Engineering at Duke Energy. "Our engineers lead the work and make all final engineering decisions, while AI agents provide them with more time for engineering judgment and review."
Regulatory pressure is tightening study timelines
FERC Order No. 2023 now requires transmission providers to use first-ready, first-served cluster studies and meet firm study deadlines for generator interconnection. Grid operators including ERCOT, NYISO, and SPP are also developing new interconnection processes for large loads. Agentic Grid Planning on AWS is designed to help utilities meet these requirements by accelerating study throughput without sacrificing the deterministic modeling that regulators expect.
"Thousands of gigawatts of generation and storage projects are waiting to connect to the grid, while electricity demand continues to grow," said Joseph Santamaria, general manager, Energy and Utilities at AWS. "By working with the applications that planners already trust and keeping engineers in control at every step, we are helping utilities move studies forward and connect the energy infrastructure that communities and businesses need, faster than ever before."
Why this matters for operations, real estate, and construction
Interconnection delays are a hard constraint on project schedules. When a new data center, manufacturing facility, or commercial development cannot get a clear timeline for grid connection, site selection, permitting, and financing all stall. A program that compresses study preparation from weeks to hours changes the risk calculus for large-load projects. For teams managing portfolios of sites, faster interconnection studies mean fewer carrying costs and more predictable delivery dates. This intersects directly with AI for Operations workflows, where automating repetitive coordination tasks frees engineers to focus on the decisions that move capital projects forward. For firms evaluating greenfield sites or retrofitting existing properties, the ability to get interconnection answers faster can determine whether a deal moves ahead or dies in the queue.
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