AES's Maximo robots installed 180,000 solar panels, now treating construction automation as proven tool

AES, a global energy company, developed Maximo through AES Next, its innovation and business-building platform. The system is an AI-powered robotic apparatus designed to automate one of the most physically demanding stages of solar construction: lifting and installing photovoltaic modules on utility-scale solar sites. Unlike factory robotics, Maximo operates on active construction sites where terrain, weather, equipment, and working conditions change constantly. Each solar module can weigh up to 75 pounds, and construction crews must lift them hundreds of times per day.

According to Nick Hegeman, Maximo's chief commercial officer, the primary technical challenge was building a system reliable enough to handle this workload at consistent pace without asking engineering, procurement, and construction (EPC) firms to change their existing processes. Maximo had to work with different terrain, weather conditions, module models, and wattages across sites without being reprogrammed for each location. The system needed to assess depth, tilt, and module placement independently and integrate into existing construction workflows and supply chains rather than force customers to reinvent their processes.

The system has now installed more than 180,000 solar modules representing more than 100 MW of generating capacity. Robots using Maximo have exceeded 500 installations per day, and crews using the technology install up to 24 modules per person per shift hour. The turning point came when Maximo moved from pilot deployments to utility-scale projects. In December 2025 and January 2026, the system reached an installation pace of 20 MW a month. Two of the five largest EPCs in the country visited a site to witness Maximo operating at this pace and, in both cases, immediately fast-tracked their technology evaluation process. At that scale and reliability, customers stopped viewing the robot as an experiment and began counting on it to meet contractual deadlines.

Hegeман explained that safety begins before robots are switched on, with crews undergoing training and site-specific safety checks the same way any new heavy equipment would be introduced to a job site. Once operating, Maximo uses real-time perception to continuously identify tracker structure, modules, and nearby obstacles, self-correcting the moment conditions change—such as when a person enters the work area or an unexpected obstruction appears.

Customer adoption, Hegeman said, accelerated because of the system's ease of integration and reliable performance. While labor shortages, heavy modules, and timeline pressure all drove interest in robotics, the decisive factor was trust earned through testing and proven track record. Maximo addresses multiple pressures at once: it delivers installation rates more than double the industry average, reduces crew size needed for heavy modules, and can shave up to two months off utility-scale timelines. Being incubated inside AES gave Maximo an unusual advantage: immediate access to AES's own solar construction pipeline, allowing the technology to be field-proven on live sites from the start rather than tested in controlled environments and later seeking pilot deployments.

Looking ahead, AES sees further opportunities in automation on the digital side of projects, giving EPCs real-time visibility into installation progress and crew performance. Material handling and site logistics—the movement of modules, pylons, and components across active construction sites—stand out as the next major automation opportunity. AES is also monitoring how panel manufacturers are adjusting their designs with automated installation in mind, a sign that robotics is beginning to influence hardware development upstream in the renewable energy sector.