The programme is therefore broader than a course for machine-learning specialists. Its stated purpose is to help technology workers stay current as AI changes software development and the wider technology sector.
For Singapore citizens and permanent residents who are working tech professionals, AISG lists a post-funding programme fee of S$196.20, inclusive of 9% GST. The official AIxTech page separately describes the student invitation process and eligibility.
AIxTech focuses on practical skills across the software-engineering lifecycle. The programme’s learning goals include:
The emphasis is not simply on learning how to write better prompts. It is on incorporating AI into real engineering work while retaining human oversight, technical judgment and accountability.
Available programme information lists access to several AI coding assistants, including Claude, Codex, GitHub Copilot, Gemini, Kiro, GLM and Agnes. The tool mix may evolve as the programme develops, so the list should be treated as the currently reported set rather than a permanent catalogue.
OpenAI is also collaborating with IMDA and AISG under AIxTech. Its contribution includes access to Codex for hands-on training, optional learning modules and participation in community activities.
AIxTech is structured to combine a compact foundational course with ongoing practice.
The Power-Up phase consists of 10 self-paced online modules totalling 18 hours. It includes hands-on coding-workflow exercises and learner support from AISG and its community. The format is intended to let working professionals and students learn without having to pause their jobs or studies.
This phase gives participants a baseline in AI-assisted engineering and is the entry point to the programme’s more advanced support.
Participants who complete the initial phase can progress to the Master phase. Reported elements include:
The Master phase matters because AI tools and engineering practices are changing quickly. A one-off course can establish basic fluency, but continued access and peer support are intended to help participants apply those skills after the initial modules.
The official AIxTech programme page lists a subsidised fee of S$196.20, including GST, for Singapore citizen and permanent-resident tech professionals. It also says eligible final-year IDT students from local institutes of higher learning are invited through their institutions and AISG.
The reported Master-phase support includes S$600 in AI coding-tool credits. However, the available material does not establish that these credits are identical to the programme fee subsidy, nor does it provide a complete published breakdown of the government’s total AIxTech budget or every participant’s individual funding arrangement.
OpenAI’s separate commitment of more than S$300 million is for Singapore’s broader AI ecosystem. Although OpenAI is contributing to AIxTech, that figure should not be treated as the dedicated budget for the training programme.
AIxTech is one part of NAIIP’s broader workforce and enterprise strategy. NAIIP aims to:
The 100,000-worker target is aimed primarily at non-technical professionals who can apply AI within fields such as accountancy and law. AIxTech addresses the complementary technical side: the people who build, integrate, deploy and govern the systems those workers use.
In practical terms, the model pairs two capabilities. Domain professionals identify where AI can improve their work, while technology professionals provide the engineering and implementation capacity required to turn those ideas into reliable systems.
The case for AIxTech is based on more than adding another software tool to the developer toolkit. AI-assisted coding and agentic systems can automate parts of software production and alter how quickly services can be developed and delivered.
That creates a likely shift in the value of technical work. Routine code production may increasingly be assisted by AI, while human contribution becomes more concentrated in areas such as:
The final point is an inference from the programme’s combined focus on AI-enabled engineering and responsible AI, rather than a claim that AI will eliminate routine programming altogether.
This is why Singapore’s approach links technical training with enterprise adoption and non-technical workforce development. If AI changes the economics and organisation of service delivery, the country needs both workers who can use AI in their professions and engineers who can build dependable systems around it.