How do you trust a system that is still learning?
For Douglas Brooks, that question isn't theoretical, it's the job. As AI works its way into more products, decisions and everyday moments, companies are under real pressure to show how their systems perform outside the laboratory.
As director of incubation and innovation — AI at UL Solutions, Douglas helps organizations answer that question. He works with companies to assess how AI systems behave over time, identify where risks may emerge across the life cycle, and demonstrate how those systems address safety, transparency and compliance expectations.
Turning uncertainty into action
Through his leadership in developing new AI certification services at UL Solutions, Douglas connects technology, assurance and policy. He helps organizations turn broad AI principles into practical steps for evidence, evaluation and governance that can support stakeholder trust.
This includes standing up AI management systems, product-level AI safety services and lifecycle-based risk assessments, along with the methods, competencies and governance models needed to translate emerging requirements into auditable, real-world practices.
The work also requires keeping pace with a fast-moving regulatory landscape. As expectations shift, Douglas helps identify the capabilities, assessment models and governance approaches organizations need to move responsibly and stay ahead of the curve.
"My goal is to balance innovation with scientific rigor so UL Solutions continues to lead as AI becomes increasingly embedded in products and systems," Douglas said.
He carries that same mindset into the industry conversations he helps drive, working alongside regulators, standards bodies, technology partners and customers, including through UL Solutions' invitation-only NEXUS executive forum.
From the laboratory to the real world
Douglas's path to UL Solutions started in the laboratory. He earned a bachelor's degree in electrical engineering from North Carolina State University, then a master's and Ph.D. in electrical and computer engineering from the Georgia Institute of Technology, where his research centered on robotics, perception and intelligent systems. His academic honors include selection as a NASA Harriett G. Jenkins Fellow.
From there, Douglas spent more than a decade at Southwest Research Institute, rising from research engineer to assistant director of the AI R&D department. He led multidisciplinary teams building machine learning, computer vision and robotics solutions for government and commercial clients, negotiating multimillion-dollar contracts along the way.
"From hands-on algorithm development to directing large AI programs and managing complex client engagements, my experience has given me a deep appreciation for how AI systems are designed, how they behave in real-world conditions and how they must be governed, validated and trusted at scale," Douglas said.
He also holds a PMP certification and remains active as an author, speaker and industry contributor.
Innovation with accountability
Moving fast is important. Getting it right is essential. For Douglas, compliance supports a larger goal: helping organizations create AI systems people can rely on.
That is where he sees the real opportunity: turning AI ambition into something organizations can stand behind. By connecting technical expertise with governance and practical evaluation, he helps make responsible AI a discipline companies can build, demonstrate and improve over time.
"AI has the potential to accelerate innovation — but only if it is deployed responsibly. My work helps ensure AI systems are transparent, governed and aligned with human values." — Douglas Brooks
Speaking engagements
- UL Advisory Council of Canada, April 14–15, 2026
- UL Solutions' NEXUS — EMEA Customer Event, May 18–19, 2026
Selected publications
SAE International. (2024). "Artificial Intelligence Data for Ground Vehicle Applications."
Brooks, D., & Howard, A. M. (2012). "Quantifying upper-arm rehabilitation metrics for children through interaction with a humanoid robot." Applied Bionics and Biomechanics, 9(2), 157–172.
Brooks, D., & Howard, A. M. (2010). "A computational method for physical rehabilitation assessment." 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, 442–447.
