## [AI, ready to deploy and be trusted](/services/ai-safety-certification-and-stewardship-services) ![](https://fast.wistia.com/embed/medias/lurdxd2498/swatch) # AI, ready to deploy and be trusted Build that trust long before launch through expert evaluation, transparent governance and independent evidence. [ Contact us ](#form) *play\_arrow* *pause* ## Breadcrumb - [ *keyboard\_arrow\_left* Services ](/services) - [ Home ](/) *pen\_size\_1* - [ Services ](/services) *pen\_size\_1* - AI, Ready To Deploy and Be Trusted Close *cancel* ### Get connected with our team Explore our offerings for AI‑enabled products — and let’s talk about how we can help. \* By ticking this box, I confirm that I have read and understood the [Online Policy](https://www.ul.com/resources/online-policies) and consent to the processing of my personal data as described therein. \* By ticking this box, I consent to the cross-border transfer of my personal data as described in the [Online Policy](https://www.ul.com/resources/online-policies). I agree to receive UL Solutions marketing communications and understand that I can opt out at any time without affecting other services by visiting our [Preference Center](https://www.ul.com/preference-center). ##### Thank you! One of our team members will respond to your request as soon as possible. Close ## Turning AI trust into market traction The market doesn't follow the fastest model. It follows the model it can trust. As you race to develop and deploy increasingly capable AI systems, earning confidence from customers, regulators and stakeholders has become just as important as technical performance. You can build that trust long before launch through expert evaluation, transparent governance and independent evidence. Move fast, arrive trusted. ![Professional surgeons in uniform and VR headset performing operation on patient in modern clinic.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:60daac08-7391-432e-a7e5-12bbce382f56/as/60daac08-7391-432e-a7e5-12bbce382f56.webp?&smartcrop=Portrait&max-quality=90&width=400) ## AI trends, opportunities and risks ![Ai](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/ai.svg)### Artificial intelligence in business: Adoption and real‑world applications Artificial intelligence (AI) is increasingly built into products, software and operations that support decision-making, pattern recognition and automation. Organizations are increasingly exploring how AI-enabled products and systems can help them improve efficiency, reduce manual work and create new customer experiences. At the same time, AI introduces new expectations around trust — such as data privacy, oversight and responsible use — that go beyond what's typically required for traditional software and data projects. ![Filter money](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/filter_money.svg)### Opportunities across industries AI adoption spans a wide range of industries, with applications such as quality control, predictive maintenance, process optimization and user personalization increasingly embedded within existing products and workflows. As use expands, organizations are moving beyond experimentation — focusing on where AI delivers the most value and how it can be deployed with appropriate oversight. This shift is creating a clear opportunity. Organizations that can govern, monitor and scale AI effectively are able to integrate it more deeply across teams and operations, reduce friction and move from pilot projects to consistent execution. ![Shield](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/shield.svg)### Why trust and reliability matter As AI becomes increasingly visible to customers and regulators, trust becomes a practical requirement. Accountability and transparency help organizations reduce compliance risk and set clear expectations for how AI systems perform. At UL Solutions, we support AI safety through training, advisory and independent third-party evaluation. As a global testing, inspection and certification (TIC) organization, we help manufacturers assess AI systems against defined safety expectations—building confidence in your products across markets worldwide. ## The evolving regulatory landscape for AI As AI adoption accelerates and expands across products, services and systems, the regulatory landscape is evolving quickly in response. Rather than a single global rulebook, organizations face a growing set of expectations that shape how AI is designed, governed and evaluated. Understanding this landscape helps teams anticipate risk, align internal practices and avoid surprises as requirements continue to mature. ### EU AI Act *keyboard\_arrow\_down* ### GDPR *keyboard\_arrow\_down* ### NIST AI RMF *keyboard\_arrow\_down* ### International standards *keyboard\_arrow\_down* ![Vacuum cleaning robot in action on wooden floor in modern architecture.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:a22f452d-11ec-44fe-964b-1830cb2f9373/as/a22f452d-11ec-44fe-964b-1830cb2f9373.webp?&max-quality=90&width=400) #### The European Union (EU) AI Act The European Union (EU) AI Act introduces a risk‑based framework that sets out different obligations depending on how and where AI is used. High‑risk AI systems are subject to additional expectations related to risk management, documentation, human oversight and post-deployment monitoring. Even organizations operating outside the EU may be affected if AI‑enabled products or services enter the European market. ![Artificial intelligence AI research of robot and cyborg development for future of people living. Digital data mining and machine learning technology design for computer brain communication.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:cc859a23-824d-4d30-80ca-d785958c13d0/as/cc859a23-824d-4d30-80ca-d785958c13d0.webp?&max-quality=90&width=400) #### General Data Protection Regulation (GDPR) The General Data Protection Regulation (GDPR) continues to influence how organizations collect, use and protect data within AI systems. Requirements related to data protection, transparency and accountability directly apply to and shape AI development and deployment, particularly when systems rely on personal data or automated decision-making. ![Modern white robot arm holding computer processor with copy space.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:391643e2-a231-447d-b630-a8da43481784/as/391643e2-a231-447d-b630-a8da43481784.webp?&max-quality=90&width=400) #### National Institute of Standards and Technology (NIST) AI Risk Management Framework (RMF) In the United States, the National Institute of Standards and Technology (NIST) AI Risk Management Framework (RMF) provides voluntary guidance for identifying, assessing and managing AI‑related risks. The framework emphasizes governance, technical safeguards and ongoing monitoring across the AI life cycle. While not a regulation, it is increasingly referenced as a common baseline for responsible AI practices. ![Engineers, doctors and physical therapists brainstorm ideas to design a robot with arm and hand organs, To be utilized for additional testing on patients.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:ba5b374b-0653-4590-822f-9accd23df3bd/as/ba5b374b-0653-4590-822f-9accd23df3bd.webp?&max-quality=90&width=400) #### Alignment with international standards Alongside regulatory activity, international standards bodies continue to develop guidance on AI safety, governance and reliability. These efforts reflect a shared goal of supporting innovation while reducing the risk of unintended harm. Alignment with relevant regulations, frameworks and standards helps organizations apply consistent approaches to governance, risk and oversight, supporting interoperability, clearer expectations and greater trust as AI systems evolve and scale. ![Vacuum cleaning robot in action on wooden floor in modern architecture.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:a22f452d-11ec-44fe-964b-1830cb2f9373/as/a22f452d-11ec-44fe-964b-1830cb2f9373.webp?&max-quality=90&width=400) #### The European Union (EU) AI Act The European Union (EU) AI Act introduces a risk‑based framework that sets out different obligations depending on how and where AI is used. High‑risk AI systems are subject to additional expectations related to risk management, documentation, human oversight and post-deployment monitoring. Even organizations operating outside the EU may be affected if AI‑enabled products or services enter the European market. ![Artificial intelligence AI research of robot and cyborg development for future of people living. Digital data mining and machine learning technology design for computer brain communication.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:cc859a23-824d-4d30-80ca-d785958c13d0/as/cc859a23-824d-4d30-80ca-d785958c13d0.webp?&max-quality=90&width=400) #### General Data Protection Regulation (GDPR) The General Data Protection Regulation (GDPR) continues to influence how organizations collect, use and protect data within AI systems. Requirements related to data protection, transparency and accountability directly apply to and shape AI development and deployment, particularly when systems rely on personal data or automated decision-making. ![Modern white robot arm holding computer processor with copy space.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:391643e2-a231-447d-b630-a8da43481784/as/391643e2-a231-447d-b630-a8da43481784.webp?&max-quality=90&width=400) #### National Institute of Standards and Technology (NIST) AI Risk Management Framework (RMF) In the United States, the National Institute of Standards and Technology (NIST) AI Risk Management Framework (RMF) provides voluntary guidance for identifying, assessing and managing AI‑related risks. The framework emphasizes governance, technical safeguards and ongoing monitoring across the AI life cycle. While not a regulation, it is increasingly referenced as a common baseline for responsible AI practices. ![Engineers, doctors and physical therapists brainstorm ideas to design a robot with arm and hand organs, To be utilized for additional testing on patients.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:ba5b374b-0653-4590-822f-9accd23df3bd/as/ba5b374b-0653-4590-822f-9accd23df3bd.webp?&max-quality=90&width=400) #### Alignment with international standards Alongside regulatory activity, international standards bodies continue to develop guidance on AI safety, governance and reliability. These efforts reflect a shared goal of supporting innovation while reducing the risk of unintended harm. Alignment with relevant regulations, frameworks and standards helps organizations apply consistent approaches to governance, risk and oversight, supporting interoperability, clearer expectations and greater trust as AI systems evolve and scale. ## Common challenges we help customers navigate As organizations continue to explore and deploy AI, recurring patterns are emerging across industries. AI adoption moves quickly, while expectations around safety, compliance and trust evolve more slowly. Many teams need help translating high‑level principles and regulatory guidance into practical day-to-day decisions that support innovation while managing risk. ![Shelter in place](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/shelter_in_place.svg)### Limited in‑house AI safety expertise AI introduces technical, ethical and governance considerations that many organizations are still building experience around. Teams may have strong data science or engineering capabilities but limited familiarity with AI safety standards, evaluation approaches or life cycle governance. This knowledge gap may slow progress, create uncertainty and make it harder to assess whether AI systems are operating as intended. ![Hand holding globe](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/hand_holding_globe.svg)### Navigating compliance and market access As AI regulations and standards emerge, organizations must interpret how new requirements apply to their products and markets. Questions around AI compliance, documentation and testing requirements can affect speed to market and confidence in deployment decisions. Without clear alignment with evolving requirements, teams risk rework, delays or inconsistent approaches across regions. ![Heart handshake](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/heart_handshake.svg)### Building brand differentiation and user confidence Customers, partners and regulators increasingly expect transparency into how AI systems behave and how AI-related marketing claims are substantiated. This expectation often includes statements about data use, model transparency, system performance and human oversight. Demonstrating responsible AI practices — supported by clear communication and third-party assessment — helps organizations differentiate their brands and strengthen user confidence. Alignment with recognized AI safety principles further reinforces trust over time. ![Business people using tablet computer in server room](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:065fa4ad-f38d-48bd-8c54-fdafe050f322/as/065fa4ad-f38d-48bd-8c54-fdafe050f322.webp?&smartcrop=Portrait&max-quality=90&width=400) ## Highlighted AI services ![Circuit chip 2](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/circuit_chip_2.svg) ### UL 3115 AI Safety Certification Services for AI-Enabled Products UL Solutions offers third-party evaluation of AI-based products to support safer deployment, public trust and market confidence. [ Learn more *arrow\_forward* ](/services/ul-3115-ai-safety-certification-services-ai-enabled-products) ![Teacher teaching](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/teacher_teaching.svg) ### UL Training and Personnel Certification for Artificial Intelligence Foundations Navigate the AI landscape and obtain a personnel certification in artificial intelligence and machine learning. [ Learn more *arrow\_forward* ](/services/ul-training-and-personnel-certification-artificial-intelligence-foundations) ![Robotic arm](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/robotic_arm.svg) ### Artificial Intelligence (AI) and Autonomous Safety Services AI and autonomy compliance services can help confirm that products incorporating AI are built with safety and security in mind. [ Learn more *arrow\_forward* ](/services/artificial-intelligence-ai-and-autonomous-safety-services) ![Ai](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/ai.svg) ### AI Stewardship Our third-party verification around AI performance can help reassure users that this functionality supports reliable and ethical operation without causing unintended harm to individuals or society. [ Learn more *arrow\_forward* ](/services/ai-stewardship) ![Secure cloud](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/secure_cloud.svg) ### Artificial Intelligence/Machine Learning in Safety-Critical Systems Integrate Artificial Intelligence/Machine Learning (AI/ML) into your automotive and medical device safety-critical systems with the support of UL Solutions Software Intensive Systems experts. [ Learn more *arrow\_forward* ](/sis/services/aiml-safety-critical-systems) ![Virtual engagement](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/virtual_engagement.svg) ### Digital Services and Artificial Intelligence Training Courses Learn how you can confidently develop both data-driven digital services and software with artificial intelligence (AI) or machine learning (ML). [ Learn more *arrow\_forward* ](/sis/training/digital-services-and-artificial-intelligence-training-overview) ## UL 3115 UL 3115 is the Outline of Investigation (OOI) for Safety of AI‑Based Products. It provides a structured way to evaluate AI safety across a wide range of products and systems that include AI‑based capabilities. Rather than focusing on a single technology or use case, UL 3115 applies a horizontal approach that can be used alongside existing product safety standards. ### What UL 3115 covers *keyboard\_arrow\_down* UL 3115 addresses AI safety through technical, ethical and governance considerations. It looks at how AI systems are designed, developed and deployed, with attention to how they behave in real‑world conditions. This includes factors such as robustness, risk management, transparency, data handling and oversight across the AI life cycle. [ Learn more ](/services/ul-3115-ai-safety-certification-services-ai-enabled-products) ### How our AI safety certification works *keyboard\_arrow\_down* We conduct independent, third-party assessments aligned with UL 3115 to evaluate whether an AI-enabled product or system has implemented appropriate safety measures for its intended use and risk profile. The evaluation considers how safety is addressed in design, governance and ongoing oversight, as well as how the system behaves in real-world operation, examining outcomes alongside underlying algorithms and architecture. This approach provides objective insight into system reliability, predictability and resilience, helping organizations demonstrate that AI safety considerations are integrated throughout the product life cycle as systems evolve and scale. ### Governance, documentation and life cycle *keyboard\_arrow\_down* AI systems evolve over time, which makes governance and documentation critical. UL 3115 considers how organizations manage change, maintain records and monitor performance throughout the AI life cycle. This includes anticipating future states, tracking risks and supporting accountability. ![UL AI Mark](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:fee72df4-4276-4122-9b3e-f5de2c6a342a/as/fee72df4-4276-4122-9b3e-f5de2c6a342a.webp?&max-quality=90&width=400) ![Northbrook Labs Robotic Arm Testing 25](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:4d73ed28-9092-48b1-9a18-5ca3df64255e/as/4d73ed28-9092-48b1-9a18-5ca3df64255e.webp?&max-quality=90&width=400) ![A humanoid robot is ironing clothes in a modern, stylish home, holding a jacket on a hanger while pressing a shirt on an ironing board. The futuristic AI assistant demonstrates smart home automation, showcasing advanced robotics in daily household chores. The bright, contemporary interior emphasizes a seamless blend of technology and everyday life.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:d898f15c-836b-4f3a-b673-4e8237f5fb13/as/d898f15c-836b-4f3a-b673-4e8237f5fb13.webp?&max-quality=90&width=400) ![UL AI Mark](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:fee72df4-4276-4122-9b3e-f5de2c6a342a/as/fee72df4-4276-4122-9b3e-f5de2c6a342a.webp?&max-quality=90&width=400) #### What UL 3115 covers UL 3115 addresses AI safety through technical, ethical and governance considerations. It looks at how AI systems are designed, developed and deployed, with attention to how they behave in real‑world conditions. This includes factors such as robustness, risk management, transparency, data handling and oversight across the AI life cycle. [ Learn more ](/services/ul-3115-ai-safety-certification-services-ai-enabled-products) ![Northbrook Labs Robotic Arm Testing 25](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:4d73ed28-9092-48b1-9a18-5ca3df64255e/as/4d73ed28-9092-48b1-9a18-5ca3df64255e.webp?&max-quality=90&width=400) #### How our AI safety certification works We conduct independent, third-party assessments aligned with UL 3115 to evaluate whether an AI-enabled product or system has implemented appropriate safety measures for its intended use and risk profile. The evaluation considers how safety is addressed in design, governance and ongoing oversight, as well as how the system behaves in real-world operation, examining outcomes alongside underlying algorithms and architecture. This approach provides objective insight into system reliability, predictability and resilience, helping organizations demonstrate that AI safety considerations are integrated throughout the product life cycle as systems evolve and scale. ![A humanoid robot is ironing clothes in a modern, stylish home, holding a jacket on a hanger while pressing a shirt on an ironing board. The futuristic AI assistant demonstrates smart home automation, showcasing advanced robotics in daily household chores. The bright, contemporary interior emphasizes a seamless blend of technology and everyday life.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:d898f15c-836b-4f3a-b673-4e8237f5fb13/as/d898f15c-836b-4f3a-b673-4e8237f5fb13.webp?&max-quality=90&width=400) #### Governance, documentation and life cycle AI systems evolve over time, which makes governance and documentation critical. UL 3115 considers how organizations manage change, maintain records and monitor performance throughout the AI life cycle. This includes anticipating future states, tracking risks and supporting accountability. ## AI stewardship, claims verification and training Many organizations need support for AI-based products beyond compliance with relevant standards and regulations. AI stewardship focuses on how AI systems are managed over time, including how safety and performance expectations are maintained, how AI‑related marketing claims are communicated and how teams build the skills needed for responsible deployment and ongoing oversight. ### AI stewardship and marketing claim verification *keyboard\_arrow\_down* Independent, third-party verification of AI‑related marketing claims helps organizations communicate system performance and behavior more clearly and credibly. UL Solutions’ Marketing Claim Verification (MCV) services help manufacturers substantiate claims related to algorithm reproducibility, data privacy and model transparency, supporting clearer communication with customers, partners and regulators. [ Learn more ](/services/ai-stewardship) ### Training your teams *keyboard\_arrow\_down* Many organizations have strong technical talent but limited internal experience with global AI safety standards, AI governance expectations and evaluation practices. AI training services can help teams build a shared understanding of risk, oversight and documentation — so they can deploy AI systems with clearer decision-making and accountability. [ Learn more ](/services/ul-training-and-personnel-certification-artificial-intelligence-foundations) ![Latin American teacher in a STEM class at the engineering lab developing a robotic arm using a laptop computer - education concepts](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:ac299e2b-046c-47fa-9a65-0bf81ce4c546/as/ac299e2b-046c-47fa-9a65-0bf81ce4c546.webp?&max-quality=90&width=400) ![Artificial Intelligence concept.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:aab716b5-3d90-41f4-a6b8-bf4d62161531/as/aab716b5-3d90-41f4-a6b8-bf4d62161531.webp?&max-quality=90&width=400) ![Latin American teacher in a STEM class at the engineering lab developing a robotic arm using a laptop computer - education concepts](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:ac299e2b-046c-47fa-9a65-0bf81ce4c546/as/ac299e2b-046c-47fa-9a65-0bf81ce4c546.webp?&max-quality=90&width=400) #### AI stewardship and marketing claim verification Independent, third-party verification of AI‑related marketing claims helps organizations communicate system performance and behavior more clearly and credibly. UL Solutions’ Marketing Claim Verification (MCV) services help manufacturers substantiate claims related to algorithm reproducibility, data privacy and model transparency, supporting clearer communication with customers, partners and regulators. [ Learn more ](/services/ai-stewardship) ![Artificial Intelligence concept.](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:aab716b5-3d90-41f4-a6b8-bf4d62161531/as/aab716b5-3d90-41f4-a6b8-bf4d62161531.webp?&max-quality=90&width=400) #### Training your teams Many organizations have strong technical talent but limited internal experience with global AI safety standards, AI governance expectations and evaluation practices. AI training services can help teams build a shared understanding of risk, oversight and documentation — so they can deploy AI systems with clearer decision-making and accountability. [ Learn more ](/services/ul-training-and-personnel-certification-artificial-intelligence-foundations) ## Meet our experts “Establishing AI system safety is crucial for building public trust and fostering the responsible adoption of AI technologies.” ![Young Lee](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:23b2568f-ea8a-418d-b16a-4feca3a09db0/as/23b2568f-ea8a-418d-b16a-4feca3a09db0.webp?&smartcrop=Square&max-quality=90&width=400) ### Young M. Lee, Ph.D. Principal Engineer for AI, UL Solutions [ Learn about Young *arrow\_forward* ](/about/people/young-m-lee-phd) “Successful AI isn’t just built — it’s engineered, governed and maintained for real-world operation.” ![Douglas Brooks SME Headshot](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:961915be-a802-4031-9b6b-ac9cc425624c/as/961915be-a802-4031-9b6b-ac9cc425624c.webp?&smartcrop=Square&max-quality=90&width=400) ### Douglas Brooks, Ph.D., PMP Head of Artificial Intelligence Incubation and Innovation, UL Solutions [ Learn about Douglas *arrow\_forward* ](/about/people/douglas-brooks-phd) “I envision a future of machine-human harmony for a better world.” ![UL Headshots - Sravya Prabhala](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:44ac8d68-b5be-49a4-9569-1b0d8fcd3f64/as/44ac8d68-b5be-49a4-9569-1b0d8fcd3f64.webp?&smartcrop=Square&max-quality=90&width=400) ### Sravya Prabhala AI Safety Scientist, AI Incubation and Innovation, UL Solutions [ Learn about Sravya *arrow\_forward* ](/about/people/sravya-prabhala) ## Additional artificial intelligence resources ![Three page brochure](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/three_page_brochure.svg) ### Navigating the EU AI Act: What AI-Enabled Medical Product Manufacturers Need to Do Now Stay ahead of the EU AI Act. Learn how medical device manufacturers can turn regulatory pressure into a competitive edge with proactive AI governance and compliance. [ Learn more *arrow\_forward* ](https://www.ul.com/insights/navigating-eu-ai-act-what-ai-enabled-medical-product-manufacturers-need-do-now) ![Video](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/video.svg) ### Impacts of Artificial Intelligence (AI) on Functional Safety UL Solutions experts present the impacts of AI on functional safety. Gain insight into the present and future of AI in functional safety. [ Watch webinar *arrow\_forward* ](/resources/impacts-artificial-intelligence-ai-functional-safety) ![Megaphone](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/megaphone.svg) ### UL Solutions Launches Landmark Artificial Intelligence Safety Certification Services New AI safety certification aims to build public trust and enable the responsible adoption of beneficial AI technologies. [ Read press release *arrow\_forward* ](/news/ul-solutions-launches-landmark-artificial-intelligence-safety-certification-services) ![Megaphone](/modules/custom/ul_component/components/brand_icon/assets/brand-icons-positive/megaphone.svg) ### UL Solutions Issues First Certifications Under AI Safety Testing Service for AI-Enabled Products Qcells and Omniconn achieved certification after completing independent evaluations that confirmed the robustness, reliability, transparency and accountability of their autonomous AI systems. [ Read press release *arrow\_forward* ](/news/ul-solutions-issues-first-certifications-under-ai-safety-testing-service-ai-enabled-products) ![little Girl Building Robotic Arm At School](https://delivery-p133222-e1298791.adobeaemcloud.com/adobe/assets/urn:aaid:aem:e8dfb732-1240-44bb-8a6d-58232fb84d22/as/e8dfb732-1240-44bb-8a6d-58232fb84d22.webp?&smartcrop=Portrait&max-quality=90&width=400) ![UL Solutions](/modules/custom/ul_component/components/brand_element/assets/brand-element-positive/mobius.svg) ![UL Solutions](/modules/custom/ul_component/components/brand_element/assets/brand-element-reverse/mobius.svg) ## Get connected with our team Explore our offerings for AI‑enabled products — and let’s talk about how we can help. [ Contact us ](#form) ## Frequently asked questions ### What is UL 3115, and how does it apply to AI‑based products? *add* *remove* UL 3115 is the OOI for the Safety of AI‑Based Products. It provides a structured approach for evaluating AI safety across a wide range of products and systems, focusing on how AI is designed, developed and deployed rather than on specific algorithms or use cases. ### How does the UL Solutions AI safety certification process work? *add* *remove* Through AI safety certification aligned with UL 3115, UL Solutions conducts an independent, third‑party assessment to evaluate whether an AI‑based product has implemented appropriate safety measures based on its intended use and risk profile. The assessment focuses on requirements and evidence, while responsibility for design and operation remains with the organization. ### How do UL 3115 and the NIST AI RMF complement each other? *add* *remove* UL 3115 and the NIST AI RMF address AI safety from complementary perspectives. The NIST framework provides voluntary, organization‑level guidance for identifying and managing AI risks across the life cycle. UL 3115 applies those concepts at the product level, offering a structured framework for evaluating whether a specific AI‑based product meets defined safety expectations for its intended use. Used together, UL 3115 and NIST AI RMF can help organizations manage AI risk consistently and demonstrate product‑level safety in practice. ### How does UL 3115 differ from ISO/IEC 42001? *add* *remove* ISO/IEC 42001 is an organization‑level standard for AI management systems. It sets requirements for governance, policies, roles and processes that guide how an organization develops, deploys and manages AI across its activities. UL 3115, by contrast, specifies safety requirements and provides guidelines for safer design, development and deployment of AI-based products. It covers the following governance-related AI safety principles: data collection and data analysis, documentation and reporting, life cycle management, accountability, control and oversight, and transparency and explainability. These principles are applied while evaluating whether a specific AI‑based product is safe for its intended use. ### What’s the difference between AI safety certification and Marketing Claim Verification (MCV)? *add* *remove* AI safety certification evaluates an AI‑based product’s compliance with defined safety expectations based on its intended use and risk profile, while MCV focuses on verifying the accuracy of specific AI‑related marketing claims for algorithm reproducibility, data privacy and model transparency through an objective, science‑based assessment. While both draw on shared AI safety principles, they serve different purposes. ### How can organizations operationalize AI life cycle governance and documentation? *add* *remove* Operationalizing AI life cycle governance involves establishing clear processes for oversight, documentation and monitoring from design through deployment and beyond. This includes defining roles, managing change and maintaining records that support accountability as AI systems evolve over time. ### Does UL Solutions offer services to support AI used in safety‑critical systems, such as automotive or medical technologies? *add* *remove* Yes, UL Solutions can evaluate a wide range of AI-based products and systems, including those operating in safety‑critical contexts. The applicable approach depends on the intended use, risk profile and regulatory expectations associated with the specific application. ### How do AI stewardship and marketing claim verification help build trust in artificial intelligence? *add* *remove* AI stewardship and marketing claim verification help organizations demonstrate responsible AI practices beyond compliance. Third-party verification and clear communication about how AI systems behave and what claims are being made can help reduce uncertainty and strengthen confidence among customers, partners and regulators.