Singapore builds a three-tier strategy to future-proof its workforce

The plan spans basic AI literacy to advanced development as technology reshapes jobs.

Singapore’s firms need to embrace investments in training and upgrading, as employers struggle to keep jobs relevant with artificial intelligence (AI), Deputy Prime Minister and Minister for Trade and Industry Gan Kim Yong said.

“Training is an investment—it takes time away from work, but it yields long-term returns for both workers and employers. Given rapid technological change, training has become even more essential today,” Gan told DBS Bank CEO Tan Su Shan during a fireside chat at the Singapore FinTech Festival 2025, held on the Festival Stage on 12 November.

Gan said Singapore’s AI strategy has three levels: basic literacy, integration capability, and development capability.

“First, we want to make sure that all companies, big and small, as well as customers – everybody – to have a basic understanding of AI,” he said.

Banks like DBS started with a “classic AI” model, and it took years of improvement.

“Setting up a data lake, making sure your process protocols are all in place, is so important. That's your bedrock. Then you can start putting in AI models that we put in quite a lot,” Tan said.

“We got worked on it. We went from a few 100 to 1,500 different models. We come up with a billion different nudges, for example,” she added.

Tan said DBS invests in continuous learning. “In the finance industry, we all have something called compulsory training hours. We need to spend that 1,015, hours a year,” she said. 

“At DBS, we developed an AI executive coach, modelled after Marshall Goldsmith, to help staff navigate their careers.” She added,

“If we’re curious and open-minded, anyone can learn,”

“Jobs will always evolve, and the pace is accelerating. It’s hard to keep one job relevant for long, but we can keep our people relevant through training and upgrading,” Gan said.

Gan called this a “shared responsibility between employers and employees.” 
Employers must allow time for training, individuals must take initiative, and the government will “provide the platforms and opportunities.”

Here’s a snippet of their conversation below:
Tan: How can a trusted hub like Singapore evolve into a trusted hub for digital flows? We don’t have much land for data centres, yet we want to be an AI-enabled country.

The government seems to be fully embracing the AI roadmap—reskilling, learning, and future readiness. But how do we balance the limits of physical space with the ambition to lead in the digital and AI-enabled economy?

Gan: AI is an important emerging technology that will impact the way we work, live, and learn.
It allows education and services to reach remote areas, transforming learning and accessibility. But AI also brings risks.

Singapore focuses on developing guardrails and guidelines for the safe and ethical development and deployment of AI. We’re working with other countries to set global standards.

If done right, AI brings great promise; if not, it can cause harm. I believe DBS is implementing many AI applications. Perhaps you can share what DBS has been doing in adopting AI.

Tan: We started almost ten years ago with what we call “classic AI.” The key lesson was ensuring proper data governance—creating a data lake with clear rules and uniform processes. Without that, you have duplication and inconsistency. Once that was in place, we built over 1,500 models, generating billions of nudges.

We also restructured our organisation—from vertical silos to horizontal teams across product, compliance, HR, etc.—using live dashboards to get real-time customer feedback.

Now, we’re layering in generative AI, experimenting with AI agents to handle repetitive work so humans can focus on building meaningful relationships.

Our philosophy: data must have purpose; it should be unsurprising, relevant, and explainable. It’s a cultural shift—requiring relearning, experimentation, and feedback—similar to how Singapore embraces change head-on.

Gan: First, we want to make sure that all companies, big and small, as well as customers – everybody – to have a basic understanding of AI. That means developing a fundamental level of AI literacy, an awareness of what AI is and what it can do today.

In this initial transition phase, our goal is to establish that baseline: every worker and every company should have this essential understanding of AI.

At the next level, we aim to build the capability to integrate AI into our systems. This involves developing AI system integrators—people who can look at a business and identify how AI can be used to enhance competitiveness, create new services, and enable things that weren’t possible before. These are individuals using AI tools to advance their businesses.

At the highest level are the AI developers—those who create new technologies, applications, and tools. Developing these advanced capabilities is also something we want to cultivate for Singapore.

Tan: Everyone should learn basic AI skills. My colleagues in China use AI for translation, and others use it to check policies and documents.

There are also deeper, specialised use cases—credit analysis, coding copilots, or agent creation. The key is attitude. If we’re curious and open-minded, anyone can learn.

Gan: Because Singapore is compact, it’s easier to roll out AI training programmes.
We also need to train users and customers so they can understand and trust AI tools—and recognise risks like scams.
We must also use AI responsibly to combat scams and cybercrime.

Tan: Yes, especially scams. Let’s turn to jobs, DPM. A few years ago, everyone wanted to be a computer scientist or data analyst. Job needs and skills are evolving fast—for both young graduates and older workers. How do we keep our workforce relevant?

Gan: Jobs will always evolve, and the pace is accelerating. It’s hard to keep one job relevant for long, but we can keep our people relevant through training and upgrading.

Singapore has invested heavily in lifelong learning for decades, but we must strengthen this culture further.

Even in good times, we must make time for training. The government subsidises training courses and works with companies to ensure programmes are relevant.

Training is an investment—it takes time away from work, but it yields long-term returns for both workers and employers. Given rapid technological change, training has become even more essential today.

Tan: In finance, we’re required to complete training hours yearly. It’s a good time to step back and learn new things. For young graduates, agility and the ability to pivot quickly are vital. At DBS, we developed an AI executive coach, modelled after Marshall Goldsmith, to help staff navigate their careers. Ultimately, we must take responsibility for our own growth.

Gan: It’s a shared responsibility between employers and employees. Employers should allow workers to go for training, and individuals must take the initiative. The government provides the platforms and opportunities, but we must take ownership. AI will also change how we educate—training will become faster and more personalised.