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Singtel Singapore took a practical step into the AI conversation, launching a new programme called AI.dea designed to help small and medium enterprises actually do something with AI, rather than just talk about it. Developed in partnership with SIM Academy, the initiative focused on helping SMBs move from early experimentation to real-world deployment, a challenge many businesses were still struggling with.<\/p>\n
At the launch, the message was fairly clear. AI was no longer optional. But figuring out where to start, and more importantly, how to scale it safely, remained a challenge. According to Singapore\u2019s Digital Economy Report 2025, only 14.5% of SMBs had implemented AI solutions, compared to 62.5% of larger enterprises, highlighting a growing gap.<\/p>\n
The numbers driving the urgency are stark. According to the Infocomm Media Development Authority\u2019s (IMDA) Singapore Digital Economy Report 2025<\/u>, only 14.5% of SMBs have implemented AI solutions, compared to 62.5% of larger enterprises. That, said Singtel Singapore CEO Ng Tian Chong, is a competitive gap that simply cannot be allowed to widen.<\/p>\n
\u201cAI has quickly become a key driver of business transformation, but many organisations are still figuring out where to even begin,\u201d he said. \u201cSingtel Singapore\u2019s own journey has shown that success with AI requires more than just technology. It takes the right capabilities, governance, and mindset. With AI.dea, we are bringing these lessons to SMBs, helping them adopt AI applications before committing to full-scale deployment so they can realise tangible business outcomes.\u201d<\/p>\n
SIM Academy CEO Ho Seong Kim positioned the programme as a national contribution. \u201cAs Singapore advances its National AI Strategy, SMBs, the foundation of our business ecosystem, must be equipped to participate meaningfully in this transformation,\u201d he said. \u201cAs the selected learning partner for this programme, we leverage our expertise in applied, outcome-driven learning to help SMB leaders build in-house capabilities, develop actionable adoption strategies, and implement AI with confidence.<\/p>\n<\/p>\nTable of contents<\/p>\n
<\/default:svg><\/button><\/p>\n\n1. From hype to hands-on execution<\/li>\n 2. A structured path with real-world use cases<\/li>\n 3. The AI.dea programme: bridging AI experimentation and real-world implementation<\/li>\n 4. Case study: Care Corner\u2019s practical AI adoption<\/li>\n 5. A candid fireside chat<\/li>\n 6. A broader push for SMB digitalisation<\/li>\n<\/ol>\n<\/section>\nFrom hype to hands-on execution<\/h2>\n\nSIM Academy CEO Ho Seong Kim<\/p>\n
Photo: HWZ<\/p>\n<\/figcaption><\/figure>\n
Singtel framed AI.dea as a bridge between curiosity and capability. The programme was structured to guide businesses through identifying use cases, building proofs of concept, and eventually preparing for full implementation.<\/p>\n
The pitch is simple and pointed. AI.dea is built to help small and medium enterprises (SMBs) in Singapore move beyond AI experimentation and into real-world implementation. The programme runs over eight days across several weeks, in three phases, and eligible SMBs can receive up to 90% in funding from SkillsFuture Singapore. The programme fee is S$15,000 before GST<\/b>, meaning a qualifying SMB could pay only around 10% of the headline cost.<\/p>\n
During the session, speakers described the current AI landscape as something of a double-edged sword. On one hand, there was excitement and urgency. On the other hand, confusion arises with companies unsure which tools to use or how to avoid costly missteps. One analogy compared AI adoption to navigating a sea filled with \u201csirens\u201d, from fear of missing out to the promise of a silver bullet solution, all of which could derail organisations if not approached carefully.<\/p>\n
The programme aimed to counter that by introducing structure. Over multiple phases, participants would define their AI ambition, prioritise use cases, and test them through guided pilots before committing to larger investments.<\/p>\n
Phase One of the programme is for C-suite and director-level participants, who are taken through a process of assessing where they want to go and prioritising their needs. The facilitators challenge participants on every chosen project. Why is this one more important than the others? Does it genuinely transform the business? Phases Two and Three bring in project managers to plan and implement a proof-of-concept (POC). By the end of Phase Three, participants should be close to completing their POC and ready to present whether it has been successful.<\/p>\n
A structured path with real-world use cases<\/h2>\n Rather than focusing purely on theory, AI.dea leaned heavily into practical application. Participants were expected to design and validate AI use cases tailored to their business needs, with support from practitioners with real deployment experience.<\/p>\n
The programme also addressed less glamorous but equally critical areas such as governance, data protection, and risk management. These were highlighted as key barriers for SMBs, especially those without dedicated internal expertise.<\/p>\n
In one example shared during the discussion, a social service organisation explored using AI to simulate client interactions for training purposes. The idea was to shorten the time needed for staff to reach competency while maintaining consistent quality in feedback and supervision.<\/p>\n
The AI.dea programme: bridging AI experimentation and real-world implementation<\/h2>\n\nSingtel Singapore CEO Ng Tian Chong<\/p>\n
Photo: HWZ<\/p>\n<\/figcaption><\/figure>\n
Singtel also drew on its internal experience to shape the programme. The company shared that its AI transformation had moved from a \u201clet 1,000 flowers bloom\u201d approach, where departments experimented independently, to a more structured, coordinated model.<\/p>\n
Three key areas emerged from that journey:\u00a0<\/p>\n
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\nFirst, building the right technology stack.\u00a0<\/li>\n Second, identifying meaningful use cases.\u00a0<\/li>\n Third, and perhaps most challenging, is managing workforce transformation across multiple generations and mindsets.<\/li>\n<\/ul>\n<\/div>\nThat last point came up repeatedly. AI adoption was not just about tools, but about culture, training, and change management. Without employee buy-in, even well-designed systems risked failing to deliver value.<\/p>\n
Case study: Care Corner\u2019s practical AI adoption<\/h2>\n\nCare Corner CEO Christian Chao<\/p>\n
Photo: Singtel<\/p>\n<\/figcaption><\/figure>\n
Care Corner Singapore, a social service agency and nonprofit, sought a clearer strategy and roadmap to move beyond being just a productive user of AI to becoming a transformative one. The agency, led by CEO Christian Chao, seized the opportunity when approached by Singtel about the AI.dea programme, with Chao bringing two other agency heads along for the journey.<\/p>\n
Chao emphasised the importance of responsible AI adoption for a nonprofit: \u201cAs a nonprofit, every resource we invest is precious. You do not want to commit to something and then realise there has been a lot of waste, and that the promises you thought would materialise simply do not. So we felt this was the more responsible way to approach AI adoption. As you know, there is so much excitement and noise around AI, and the responsible thing as leaders is to take it seriously and make the investment wisely.\u201d<\/p>\n
Key Outcomes of Phase One<\/h3>\n In Phase One, Chao\u2019s cohort identified pain points and use cases. The programme structure, which incorporated perspectives from the other agencies, helped Care Corner prioritise its initiatives. The agency decided to focus on using AI to reduce the time-to-readiness (or time-to-competence)<\/b> for staff in certain work areas:<\/p>\n\n
\nFocus on Training and Supervision:<\/b> For social workers and counsellors, critical training often involves supervisors working directly with new staff. Care Corner aims to use AI to reduce the time needed for certain parts of this training and, consequently, the time supervisors spend on it, allowing staff to move from training time to actual client time sooner.<\/li>\nImproving Training Quality with Simulations:<\/b> The team\u2019s concept is to leverage AI to run simulations where staff practice engaging with various client types. The AI would provide feedback, and supervisors would review this data, making their subsequent one-on-one sessions with workers more targeted. While the team is exploring options (starting verbally), Chao noted that visual simulations are ultimately the \u201crichest and most informative mode,\u201d but cost considerations need to be weighed in the next planning phase.<\/li>\nReturn to Fundamentals:<\/b> Phase One also imposed \u201creal discipline\u201d by forcing the agency to answer fundamental questions like: \u201cWhy do we want to adopt AI? What role do we want AI to play? What value will we see, and how will we measure it?\u201d<\/li>\n<\/ul>\n<\/div>\n The Role of Governance and Security<\/b><\/p>\n
A crucial part of the process was gaining access to legal and security expertise, which helped change how Care Corner sequences its work:<\/p>\n
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\nExpert Guidance:<\/b> Drew & Napier provided training on AI governance, while the Cyber Security Institute (CSI) covered cybersecurity. (This mirrors Singtel\u2019s Cyber Elevate programme, which uses Drew & Napier for legal and an incident response company for breach handling.)<\/li>\nData Sensitivity and Sequencing:<\/b> This examination led Care Corner to prioritize training simulations because they require less sensitive data. The data used is \u201caggregated and constructed,\u201d not real client data, which is \u201ceasier to manage from a data security standpoint.\u201d Chao explained, \u201cThe moment you bring in live personal data, it is a completely different situation. So that also helped us stage the process. Get this project done first, build experience and confidence, and then approach something more ambitious while being fully aware of the risks involved.\u201d<\/li>\n<\/ul>\n<\/div>\nA candid fireside chat<\/h2>\n\nExample of AI.dea training class<\/p>\n
Photo: Singtel<\/p>\n<\/figcaption><\/figure>\n
The launch\u2019s most candid stretch came in the fireside chat moderated by Ho, with Minister of State for Digital Development and Information Jasmin Lau as the guest of honour.<\/p>\n
The Prime Minister, Ho, noted that he has recently emphasised that AI is being scaled across government, enterprises, and society. The question is no longer whether to adopt AI, but how to do so effectively, securely, and responsibly at scale. How is the government accelerating AI adoption across the economy, especially for SMBs?<\/p>\n
Minister Lau began by drawing the boundary of her own experience. \u201cLet me first explain the context in which my answers sit. I am not an SMB owner. I have never run a business, so I am always careful when I talk about SMBs, because I cannot prescribe solutions. But I can give you a sense of the world we are in.\u201d<\/p>\n
Singapore, she said, is quite good at getting its people and businesses excited about a new technology. Sometimes there is hype, people get over-excited, and then they realise it is not quite what they expected. But at least they respond, and that puts the country in a reasonable position. \u201cWe are small enough that when we say something important is coming, people sit up and pay attention.\u201d<\/p>\n
She was careful to push back on the idea that Singapore had simply chosen AI as a pillar by preference. \u201cAI is going to hit the world whether we like it or not. So we choose to focus on it, not because we think it is automatically the right answer, but because it is coming, and we need to position Singapore to give it the best possible chance of success.\u201d<\/p>\n
That framing, she said, explains everything that follows. \u201cWhy are we getting SMBs to adopt AI? Why are we getting all our workers to learn about it? Because it is going to hit Singapore hard, just as it is hitting the rest of the world. We want to put ourselves in the path of possible success, and give as many of our workers as possible a good chance at a good job in the future.\u201d<\/p>\n
From her conversations with SMB leaders, the Minister said most have gone through a recognisable cycle. First, excitement. Then the realisation that it is not so straightforward, that doing a proof of concept does not mean the thing can actually go into production. Then questions about risk. Do you open your data? What happens if something scrapes it? Then it becomes a conversation about change management. Are workers fearful? If a leader says, \u201cI want AI\u201d, how does the rest of the organisation feel about that? Is AI being forced on them, or do they genuinely believe it is a tool to help them?<\/p>\n
\u201cThe initial excitement is great, but SMBs are now moving into a phase where they are realising deployment into production is genuinely hard.\u201d That, she said, is precisely where partners like Singtel and SIM Academy come in, alongside large corporations that have departments and resources SMBs simply do not have.<\/p>\n
It is not, she stressed, a problem unique to SMBs. The Government has the same challenge. \u201cMany agencies are extremely excited about AI right now. Everyone wants to build a new dashboard or an AI-enabled checklist. But if you really ask, what is the problem we are actually trying to solve? What service do citizens actually want? That takes a lot more time to figure out, and it is not the glamorous part.\u201d<\/p>\n
The most striking part of her message, though, was a permission slip. \u201cNot every SMB has to use AI. Just as not all individuals need to use every AI tool available. But every SMB should go through the process of thinking about the possibilities, and then intentionally deciding yes or no. If an SMB decides AI is not for them right now, that is an equally valid and important decision. The key is that it is made intentionally.\u201d<\/p>\n