Microsoft: Can Generative AI Speed up Energy Permitting?

The process of getting a permit for the construction of a renewable energy project can be long, difficult and expensive.

As renewable energy gains momentum, companies face prolonged, costly and complicated processes that act as barriers to prompt deployment.

Microsoft has been exploring ways in which technology can help to streamline this process and get more clean energy installations off the ground.

The concept originated during a hackathon event hosted by Microsoft, where developers and innovative thinkers brainstormed software improvements.

Since then, the tech giant has begun investing time and resources into revolutionising permitting using Gen AI.

For this project, Microsoft's team has put a special focus on nuclear power where planning and permitting can take more than a decade and cost millions of dollars.

"Permitting is the single biggest bottleneck to deploying clean energy fast enough to avoid runaway climate change," Microsoft says of the issue.

"That's not just inefficient – it's existential."

Collaboration and innovation

The project's origins trace back to a 2022 gathering of the Repowering Coal Consortium at Microsoft's Dublin offices.

Fifty industry representatives from across the advanced nuclear sector identified permitting as a critical obstacle to scaling nuclear deployment from one reactor per decade in the Western world to the 2,500 needed globally to replace coal power.

Mark Tipping, Global Offshore Power to X Director at Lloyd's Register, believes this initiative will be hugely impactful. 

"Together, we're tackling one of the biggest challenges in deploying nuclear technology, which is navigating complex, slow and costly licensing processes," he says.

The technical breakthrough

The team initially attempted to solve permitting challenges using traditional software approaches but found the problem intractable.

Conor Kelly, a key team member, explains: "We first started trying without Gen AI... just normal software programming. It was an intractable problem."

The breakthrough came with the realisation that generative AI could interact with vast datasets and format content as needed by varied licensing documents.

The combination of Azure OpenAI and Kernel Memory now allows for the rapid creation of draft permitting documents, reducing a process that once took extensive time down to mere minutes.

Microsoft's structured approach

The solution addresses three core challenges in the permitting process.

Automated document creation uses Gen AI to draft permitting documents from historical and project-specific data.

A Copilot system provides permitting engineers with access to entire regulatory datasets through ad-hoc queries, running entirely on companies' own Azure tenants to prevent data leakage.

Pre-submission review capabilities flag missing information before formal submission, reducing costly delays with regulators.

Delivering a measurable impact

The introduction of AI-driven permitting has resulted in productivity gains of 25-75% in energy project workflows.

Ed Essey, Senior Director of Business Value at Microsoft, believes this project speaks to the importance of pursuing ideas with curiosity and an open mind.

"It's incredible to see that what began as a side project got Microsoft into nuclear," he says.

The initiative has catalysed a cross-Microsoft task force on AI for permitting, with support from senior executives including Chief Sustainability Officer Melanie Nakagawa and President Brad Smith.

While initially focused on nuclear permitting, the project has expanded to cover renewables, mining and other clean energy sectors.

The team is now working under Microsoft's MCAPS Energy & Resources division, developing new applications for mining and offshore wind projects.

"This project was about realising much wider applicability – not just this specific nuclear permitting document, but right across the nuclear permitting field and into wind and other renewable energy permitting," Connor says.