As AI systems become more capable and autonomous, the question is no longer whether AI will shape industries and societies but whether people can trust it to do so safely and reliably. At International Scientific Exchange on AI Safety and ATxSummit 2026 week, Singapore took another step towards answering that challenge together with our assurance and testing community.
On 18 May 2026, Minister for Digital Development and Information, Josephine Teo announced the AI Tester Accreditation Programme (AI TAP), the first initiative of its kind in Asia to recognise competent third-party AI testing providers and codify what good AI testing looks like.
AI TAP aims to strengthen confidence in AI systems by supporting credible, independent testing. Industry interest has already emerged from organisations including AIDX, Asenion, Knovel Engineering, PwC, Resaro, and Vulcan.
AI TAP will:
Building assured credibility together
Watch the highlight reel of AI Assurance Exchange at ATxSummit 2026
At ATxSummit 2026, our Executive Director Lee Wan Sie highlighted in her TechTalk that trustworthy AI is built through rigorous testing, independent validation, and credible assurance.
She shared how the Global AI Assurance Sandbox is helping to advance this vision by facilitating the technical testing of real-world Generative and Agentic AI applications by independent testers, guided by Singapore’s governance frameworks, including AI Verify testing framework and the Starter Kit for testing LLM-based applications. To date, the Sandbox has supported the testing of 30 applications from 14 sectors across 12 geographies.
Pre-qualified Sandbox testers also joined Wan Sie on stage to expand on why credible testing matters now more than ever.
Fion Lee-Madan (Asenion) shared how Accreditation acts as the last mile for AI testing companies, “we can prove that we are competent, there is independence, there is a consistent process and technique we follow.”
April Chin (Resaro) also echoed this sentiment, “Accreditation brings independent body of evidence to help us know how the AI product was built and how it will perform in the real world. It also helps to establish the common vocabulary and definition of what a trustworthy product is.”
AI is a learning system and as such, assurance for AI needs to be a continuous living system too.
The Global AI Assurance Sandbox sharing session brought together the latest cohort of 13 pairs of AI deployer and testing firm pairs. More than 80 industry practitioners from around the world joined the discussion, exchanging perspectives on the evolving practice of AI assurance and the role of testing in building confidence and trust in AI systems.
Featured sharing included:
These projects demonstrate the growing diversity of AI testing and assurance use cases, spanning recruitment, healthcare, education, legal services, finance, customer service, and enterprise productivity.
Read the case studies from the Sandbox here to learn more about the testing approaches, findings, and lessons from these real-world deployments.
The sessions concluded with the networking reception at Capella Singapore, bringing together more than 200 global assurance leaders, practitioners, industry players, and policymakers.
We were also pleased to welcome Ng Cher Pong (Chief Executive Officer, IMDA), who joined the reception and connected with members of the AI Verify Foundation community. The gathering provided an opportunity for participants to exchange perspectives, forge new partnerships, and continue advancing the development of a trusted and vibrant AI assurance ecosystem.
As shared by Denise Wong (Assistant Chief Executive, Data Innovation and Protection Group, IMDA), trusted AI assurance cannot be built in isolation; it requires collaboration across deployers, testers, industry, researchers, and policymakers to turn testing insights into practical standards for real-world AI systems.
From testing to accreditation to ecosystem building, Singapore has a unique opportunity to continue building a trusted AI assurance ecosystem.
And we are all building it together!
Announcements made during ISE and ATxSummit 2026:
Your organisation’s background – Could you briefly share your organisation’s background (e.g. sector, goods/services offered, customers), AI solution(s) that has/have been developed/used/deployed in your organisation, and what it is used for (e.g. product recommendation, improving operation efficiency)?
Your AI Verify use case – Could you share the AI model and use case that was tested with AI Verify? Which version of AI Verify did you use?
Your experience with AI Verify – Could you share your journey in using AI Verify? For example, preparation work for the testing, any challenges faced, and how were they overcome? How did you find the testing process? Did it take long to complete the testing?
Your key learnings and insights – Could you share key learnings and insights from the testing process? For example, 2 to 3 key learnings from the testing process? Any actions you have taken after using AI Verify?