Are Ai-powered Robots The Future Of Solar Construction?

As the renewables industry grapples with a labor shortage, AI-powered construction robots are picking up some of the slack.

Global engineering, construction, and procurement (EPC) contractor Burns & McDonnell is among the latest to deploy smart machines to help build utility-scale solar projects. Via a partnership with AI and robotics company Gritt, Burns & McDonnell has spent the past year evaluating AI-powered robotics and testing their effectiveness in real-world construction environments, including at multiple utility-scale solar sites.

This summer, the EPC took the training wheels off.

Burns & McDonnell deployed AI software and robotics from Gritt to install a portion of the solar modules on-site at the 346 megawatt (MW) Gibson City Solar Project in McLean County, Illinois, developed by Earthrise Energy. At Gibson City, the Gritt machines lifted and placed solar modules, reducing the need for repetitive heavy lifting.

“Solar construction is very repetitive work, lifting 80-pound modules day after day,” noted Adam Bernardi, renewables business line director at Burns & McDonnell. “As solar installations continue to grow in scale, we have an opportunity to leverage technology in ways that help our teams work safer, faster, and smarter. By helping crews handle some of the most repetitive and physically demanding tasks, Gritt offers a solution that can improve safety while helping us deliver projects more predictably.”

The Gibson City project, which utilizes NextPower terrain-ing trackers, a Shoals above-ground collection system, and SMA inverters, reached commercial operations earlier this month.

The Gibson City Solar Project, developed by Earthrise Energy, was a proving ground for EPC Burns & McDonnell’s AI robotics partnership with Gritt. Courtesy: Burns & McDonnell

Gritt combines AI and robotics to automate labor-intensive work on construction sites, building systems that attach to standard equipment and can then autonomously handle tasks placing and assembling solar arrays, pouring concrete, and laying rebar. Gritt’s technology is specifically tailored for outdoor construction sites, where terrain, weather, and conditions can vary significantly. The company’s AI-powered systems are designed to assist crews while continuously learning from field operations. That makes each site a “classroom” for the AI, and every deployment provides opportunities to better understand changing weather conditions, site logistics, terrain challenges, and construction workflows.

In general, next-generation construction automation is intended to help improve safety, enhance project predictability, and support construction teams rather than replace them. Both Burns & McDonnell and Gritt stressed that the robots are not intended to eliminate the jobs of human solar construction workers, but rather work alongside them to speed up processes or to complete repetitive, labor-intensive tasks. Utility-scale solar panels often weigh 60 pounds or more, and installers have to bend and lift large loads hundreds of times over the course of a single job.

“Construction has always been powered by skilled craft, and that isn’t changing,” said Jami Stone, a construction project manager at Burns & McDonnell. “There will always be a human element to robotics. Learning how to operate, manage and work alongside these technologies helps expand construction professionals’ toolkit.”

Don’t forget Maximo

In 2024, global power company AES Corporation unveiled a first-of-its-kind AI-powered solar installation robot, Maximo, which works alongside human teams to accelerate project construction by placing and attaching modules. Maximo uses AES’s proprietary data to adapt to real-world site conditions and can support multiple tracker and module manufacturers. Burns & McDonnell and Gritt’s technology, Maximo also learns on the job.

“Maximo is equipment,” explained Deise Yumi Asami, head of renewable technology and innovation at AES. “A tool for our construction workforce that helps them be more productive and to keep systems going the entire time we’re on site.”

Invented and owned by AES, Maximo was programmed using a wide range of Amazon Web Services (AWS) tools, including AWS RoboMaker, a cloud-based simulation service that enables robotics developers to run, scale, and automate simulation. Maximo can perform in a broad range of climates and lighting conditions and has been validated in the field across a variety of U.S. project sites, including its first utility-scale deployment at the Oak Ridge Solar project in Louisiana, where it helped power Amazon operations. It also lent a helping hand (or robotic arm) at Cavalier Solar in Virginia.

AES later deployed Maximo to its massive two-phase Bellefield solar and storage project in Kern County, California. This spring, Maximo eclipsed a major milestone, installing more than 100 MW of utility-scale solar capacity at Bellefield. The 1,000 MW first phase of the project was completed last year, and phase two is expected to be wrapped up later in 2026. Once completed, the 2,000 MW Bellefield site will be one of the largest solar-plus-storage facilities in the United States.

AES believes its solar installation solution will help close the gap between the need for faster time-to-power and construction capacity, and says the 100 MW achievement marks the transition of robotic module installation from early deployment validation to sustained commercial production.

“Reaching 100 MW at a single site is an important milestone for Maximo and for the role robotics can play in solar construction,” observed Chris Shelton, president of Maximo. “It demonstrates that intelligent field robotics can deliver consistent results at utility scale. As solar deployment continues to accelerate globally, technologies that improve installation speed, quality, and reliability will become increasingly important.”

The Bellefield project scaled from using a single robot to a coordinated fleet of four Maximo units operating in parallel. By tightly integrating robotic placement into standard construction workflows alongside skilled union technicians, AES reports the fleet delivered “a step‑change in productivity while maintaining high safety and quality standards.” Maximo’s version 3.0 units’ technical performance rate consistently exceeded installing one module per minute, with crews finishing as many as 24 modules per shift hour per person, nearly double the output of traditional installation methods, according to AES.