Artificial intelligence is showing up in more places every year, from chatbots to infrastructure software that helps run buildings and data centers. That growing presence raises an obvious question. If AI is making decisions that affect energy systems, cooling equipment, or other operational technology, how do we know it is safe and reliable? UL Solutions now says it has a way to answer that.
The company announced the first certifications issued under its AI safety testing service, and two products have already passed the evaluation process. According to UL Solutions, the certifications were awarded to the Qcells Energy Management System and the Omniconn Platform 4.0 smart building platform. Both systems were reviewed under UL 3115, which the company describes as its framework for evaluating the safety of AI based products.
UL Solutions says these are the first certifications anywhere issued under UL 3115. The evaluations looked at factors such as reliability, transparency, accountability, and operational safeguards. The company also verified that both systems include controls that keep humans involved in oversight even as automation increases.
“As AI begins to operate in real-world systems, independent safety certification is essential to public trust,” said Jennifer Scanlon, president and CEO of UL Solutions. “These certifications establish a new benchmark for trustworthy, responsibly managed AI in critical infrastructure.”
The Qcells certification focuses on an AI driven optimization agent built into the company’s Energy Management System for data centers. The software analyzes conditions such as energy generation, grid status, and demand, then coordinates available resources while providing insights for operators. The goal is to help facilities balance power use more efficiently without giving up human control over the system.
“This certification shows that human and agent energy optimization collaboration can be safe and is ready for data center operations,” said Dr. Youngchoon Park, president of the Grid and Energy Services Business at Qcells. “It offers a credible path to scale while demonstrating our commitment to creating resilient, reliable, AI-enabled platforms.”
Omniconn’s certification applies to its Platform 4.0 software, which connects building automation tools, IoT sensors, and operational systems into a single management environment. The platform provides monitoring, predictive analytics, and automated controls intended to improve energy efficiency, cooling performance, and overall building operations.
“At Omniconn, our focus has always been on helping customers run smarter, more efficient buildings without losing visibility or control,” said Ibrahim Lari, chairman of Omniconn. “This certification from UL Solutions reinforces that our platform is built with the right safeguards in place and gives customers greater confidence as they adopt AI-driven building operations.”
The certification process evaluates not only technical performance but also governance and oversight practices around the AI systems themselves. In other words, it is not just about whether the software works. It also examines whether the organizations behind these platforms are maintaining safeguards and accountability as automation increases.
That matters because AI is quickly moving beyond novelty applications. Data centers, energy systems, and building infrastructure are increasingly managed by software that analyzes large volumes of operational data and makes automated adjustments. When those systems fail, the consequences can affect uptime, efficiency, and sometimes safety.
UL Solutions appears to be positioning UL 3115 as a framework for addressing those concerns. Rather than relying entirely on vendor claims, the certification offers a structured evaluation that organizations can use to demonstrate responsible AI deployment.
Whether UL 3115 becomes a widely recognized benchmark remains to be seen. But the first certifications for Qcells and Omniconn suggest that the industry is beginning to take independent AI validation more seriously. If AI is going to manage power systems, cooling infrastructure, and other operational technology, outside verification will likely become increasingly important.
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