At the centre of this is a set of national AI missions in four core sectors - Advanced Manufacturing, Financial Services, Connectivity, and Healthcare. Businesses can lower AI implementation costs, access shared infrastructure and upskill their workforce with initiatives under the Missions.
Singapore has deepened partnerships with local and global AI leaders — a move aimed at strengthening the talent pipeline and advancing responsible AI deployment. Google and OpenAI have each signed a Memorandum of Understanding (MoU) with MDDI to co-develop AI solutions across the public and private sectors.
Singapore is also developing Punggol Digital District (PDD) as a frontier testbed for embodied and applied AI. This “physical AI industry” will allow companies to test robotics and AI systems in real world conditions, starting with Grab’s exploration of integrating robotics into F&B operations and logistics.
On the sidelines of ATxSummit, Digital Industry Singapore (DISG) also hosted a panel and networking session that brought together government and industry leaders. The discussion focused on one of Singapore’s four AI Missions – connectivity, with Singapore Airlines, SATS, and Changi Airport Group exploring how AI can unlock new capabilities and ease operational constraints in air connectivity.
Led by EDB, together with A*STAR, Enterprise Singapore (ESG), JTC and local firms, the Singapore pavilion at Hannover Messe in Germany showcased Industry 4.0 solutions from 13 local enterprises including a model of Jurong Innovation District alongside AI-powered systems and robotics solutions.
Manufacturers typically find it challenging to adopt AI due to three issues: limited in-house AI expertise, poor or unstandardised factory data, and uncertainty over whether AI systems will hold up in live operations. Singapore’s ecosystem is structured to address each of these barriers directly, pairing manufacturers with research institutes or industry partners to move AI pilots into reliable production-line deployment.
Sunningdale Tech, a precision plastic components manufacturer, was able to work with A*STAR’s Sectoral AI Centre of Excellence for Manufacturing (AIMfg) to deploy AI-powered defect detection and inspection systems. This improved quality and consistency while reducing manual inspection load. The use case shows how a mid-sized manufacturer can access national-level R&D capability that would otherwise require significant in-house investment.
Microsoft and A*STAR have since signed an MOU to explore agentic and deployable AI solutions for manufacturing, targeting the same AI adoption barriers outlined above.
The SonarQube Remediation Agent is an AI-powered solution that automatically identifies code issues and applies fixes, helping organisations confidently scale AI-assisted development. It builds on AutoCodeRover, an LLM-based software engineering agent developed by researchers at the National University of Singapore (NUS) and acquired by Sonar in 2025. The Swiss software firm’s decision to base development in Singapore underscores the country’s strength in translating academic research into commercial AI applications, supported by strong industry-academia linkages and a deep technical talent pool.
4. NVIDIA and KPMG join growing wave of leading firms building AI centres and hubs in Singapore
Singapore is currently home to more than 70 AI Centres of Excellence (AI CoE). New additions to the ecosystem in the last quarter will boost AI innovation and deployment activity, while deepening the pool of AI talent and partners. Here is a recap of AI CoEs, hubs, and labs that opened in the last quarter.
- NVIDIA picks Singapore for its second Asia-Pacific AI research lab The lab will focus on advancing embodied AI and efficient AI computing in collaboration with university researchers, industry partners and government agencies. Both strategic domains will see numerous potential applications in manufacturing.
- Sea establishes AI CoE to drive AI-native innovation and capacity building With support from DISG, the AI CoE is expected to create demand for at least 100 R&D and innovation-centric roles in AI research, engineering, and product development over the next three years, and will help deepen homegrown capabilities in advanced foundation models, production-ready solutions, and new AI operating models. It will also deepen Sea’s suite of large language models, tailored for Southeast Asian languages and e-commerce contexts, which already powers Shopee features at a fraction of typical commercial LLM costs.
- KPMG’s Trusted AI CoE helps businesses embed AI as a trusted, enterprise-ready asset The capability hub reinforces Singapore’s position as a trusted node in the global community, co-creating knowledge, accelerating innovation and strengthening Singapore’s AI ecosystem across businesses, academia and the public sector. A notable capability from the AI CoE includes its Trusted AI Assurance, which provides a multi-faceted evaluation of organisations’ AI deployments across governance, systems, compliance and security.
- Publicis Groupe APAC establishes AI development hub to build and scale proprietary marketing technologies The new hub will embed AI solutions across creative optimisation, content development, influencer marketing, and media planning, with the aim of reducing manual campaign execution time by 20–30% while improving speed, quality, and delivery capacity across regional teams. It will also partner with Institutes of Higher Learning in Singapore to cultivate a pipeline of emerging digital talent, offering internships and applied research opportunities in AI, data science and human-centred design. This initiative supports Singapore’s broader efforts to attract, develop, and retain AI talent within the country’s growing AI innovation ecosystem.
- Temus launches its AI Foundry to strengthen production-grade AI delivery for enterprises Supported by DISG, the AI foundry will accelerate Temus’ AI hiring, with 50 new roles to support enterprise projects in financial services and precision health. The foundry deepens Temus’ partnership with AI Singapore (AISG) to drive joint prototypes, multilingual models, reusable delivery frameworks, and large-scale enterprise deployments.
5. Accenture report: CEOs who align their AI strategy with their talent strategy are pulling ahead on revenue and profits
Accenture’s report found that 46% of Singapore companies have yet to redesign job roles or responsibilities to match the AI they have already deployed. Without work redesign, AI adoption risks becoming a technical upgrade rather than a true engine for new capabilities, new sources of value and long-term growth.
Citing DBS as a success story, the report highlights what can be achieved when leadership backs AI as a driver of true enterprise-wide transformation.
DBS built its AI readiness and advantage by focusing on three key aspects: embedding automation into everyday workflows, investing early and heavily in high-quality data, and nurturing a culture that rewards experimentation and learns from failure. These moves were set in motion by leadership decisions in 2014 and reinforced consistently over the years. DBS's decade-long head start suggests AI advantage compounds and that making early, sustained investment in data and culture is more valuable than a fast follow approach.
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