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Key Takeaways
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SAP Labs East Asia Singapore will hire and train 50 AI scientists and machine learning engineers through Singapore’s TechSkills Accelerator program.
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The initiative strengthens Singapore’s position as a global engineering hub supporting SAP’s Business AI portfolio.
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The partnership with IMDA focuses on building enterprise AI capabilities including generative AI, agentic AI, and machine learning systems.
SAP Labs East Asia Singapore is partnering with Singapore’s Infocomm Media Development Authority (IMDA) to expand its artificial intelligence (AI) talent pipeline by hiring and training AI scientists and machine learning engineers.
Announced at the SAP d‑com Singapore developer conference, the initiative will hire and train 50 AI scientists and machine learning engineers over the next three years through IMDA’s TechSkills Accelerator (TeSA) program.
The program is designed to build capabilities in areas such as generative AI, model orchestration, and enterprise AI agents that power SAP’s Business AI portfolio. Participants will undergo a structured 12‑month training and mentorship program and may also have opportunities for short‑term placements at SAP Labs locations in Germany, the United States, and India.
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The announcement underscores SAP’s continued investment in Singapore as a global engineering hub for enterprise AI development. SAP Labs East Asia Singapore has played a growing role in building AI technologies embedded across SAP’s cloud applications, including enterprise AI agents integrated into core SAP systems.
Singapore Strengthens Its Role as an AI Engineering Hub
SAP’s Singapore lab has expanded rapidly in recent years as the company increases investment in enterprise AI capabilities. The growth also comes amid broader organizational changes across SAP’s regional engineering network.
Earlier in 2026, SAP made leadership appointments that reflect its regional focus on expanding AI and engineering capabilities across Asia, naming Manik Saha as Managing Director of SAP Labs East Asia. The regional research and development unit brings together SAP Labs in Singapore, Vietnam, Japan, and Korea, with the Singapore lab playing a central role in advancing SAP’s Business AI initiatives and strengthening the company’s R&D footprint in Asia.
Saha said SAP’s expanded investment in Singapore reflects its broader strategy to accelerate enterprise AI innovation while building one of the company’s key global AI talent hubs. Since 2023, SAP has focused on developing AI talent and career pathways in the region while expanding engineering capacity.
“Our teams in Singapore are developing foundational generative, agentic, and multimodal AI capabilities that are being embedded across SAP’s core solutions worldwide,” he added. Saha noted that Singapore’s strong talent pipeline and national AI strategy position the country as “a strategic engine for SAP’s long-term AI product roadmap.”
AI Capabilities Built in Singapore Power SAP Applications
Engineering teams at SAP Labs East Asia Singapore are involved in developing AI capabilities used across SAP’s enterprise applications.
Examples include AI‑driven scenarios for SAP S/4HANA, SAP Intelligent Spend and Business Network solutions, and SAP SuccessFactors that support information retrieval, navigation, and automated information extraction.
The team has also developed generative AI features within SAP SuccessFactors designed to improve employee productivity, including tools that generate compensation insights, career insights, and goal recommendations. SAP Labs East Asia Singapore teams are also advancing Document AI capabilities for extracting information from business documents and supporting additional languages and file formats.
What This Means for SAPinsiders
Enterprise AI development requires regional engineering hubs. SAP’s investment in Singapore illustrates how global R&D locations can support the development of enterprise AI capabilities. Regional engineering teams contribute to product innovation while connecting local talent ecosystems to global technology platforms.
Government–industry partnerships are shaping enterprise AI ecosystems. Collaboration with national digital programs such as IMDA’s TechSkills Accelerator expands the available AI workforce. These partnerships help technology vendors scale innovation while strengthening local technology economies.
Enterprise AI depends on sustained talent pipeline investment. Programs like this combine hiring with structured training to build specialized AI engineering skills. For large organizations adopting enterprise AI, vendor ecosystems with deep talent pools can accelerate innovation and deployment.
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