AI Is Reshaping Jobs in Singapore — Can Retraining Keep Up?

At the same time, the company has also been restructuring its workforce around AI, moving roughly 7,000 employees into roles focused on AI-related products such as agents and AI-driven applications. The pattern emerging in many tech companies is not simply smaller teams—but fewer traditional roles and more AI-focused ones.

Together, these changes illustrate a broader trend: AI adoption can simultaneously create new specialized jobs while eliminating others.

Banking Faces Similar Pressure

The shift is not limited to technology companies. The financial sector is experiencing similar changes as banks deploy automation to streamline operations.

Standard Chartered’s chief executive Bill Winters said the bank would reduce certain roles as it increases AI usage, describing the changes as "job role reductions in favour of the machines." The bank plans to cut more than 15% of its support staff by 2030 as part of its automation strategy.

The comments sparked controversy in Singapore after Winters described the roles affected as "lower-value human capital." Former president Halimah Yacob criticized the remark as “disturbing” and “demeaning,” urging companies to treat retrenched workers with dignity and humanity.

The backlash highlighted a growing concern: as AI automates routine tasks, the way companies frame job losses—and the speed of workforce restructuring—matters politically and socially.

Singapore’s Strategy: Retraining at National Scale

Singapore’s response has been to push AI adoption while simultaneously investing heavily in workforce adaptation.

The government’s National AI Impact Programme (NAIIP) aims to support 10,000 enterprises in adopting AI and train 100,000 workers to apply AI tools in their jobs over the next three years. The initiative builds on the country’s broader National AI Strategy and seeks to embed AI capabilities across sectors, from finance and law to small businesses.

The goal is not to turn every worker into a machine-learning engineer. Instead, policymakers want professionals to become “AI‑bilingual”—people who can combine domain expertise with practical AI tools to redesign workflows and improve productivity.

This approach reflects Singapore’s long‑standing economic strategy: adopt new technologies early while helping workers transition to higher‑value roles.

Government Pressure on Firms to Create Better Jobs

Singapore’s leadership has also urged companies to use AI in ways that upgrade jobs rather than simply eliminate them.

Deputy Prime Minister Gan Kim Yong has called on financial institutions to prioritize training and job redesign instead of focusing solely on cost-cutting. AI should create better roles and opportunities for workers, he said, not just reduce staffing.

The message reflects a policy dilemma: while governments can fund training programs, corporations ultimately decide whether productivity gains translate into job redesign or job cuts.

The Real Challenge: Speed

Economists note that the key issue may be timing. AI can automate tasks rapidly, but retraining workers and redesigning job roles typically takes longer.

Even large training programs cannot guarantee that displaced workers will move directly into new roles. Success depends on several factors:

• whether companies redesign workflows so workers supervise or augment AI
• whether new AI-driven products and services create additional demand for labor
• whether training programs lead to real job transitions rather than credentials alone

If companies primarily deploy AI to remove layers of routine work without expanding new roles, workforce programs may struggle to keep pace.

A Mixed Future for AI and Employment

Singapore is often cited as one of the most proactive countries in preparing for AI’s economic impact. Its combination of national AI policy, corporate incentives, and large-scale workforce training is among the most ambitious in the region.

But the recent wave of layoffs underscores a reality seen worldwide: global corporate strategies can reshape local job markets faster than national policies can respond.

The likely outcome is not a simple story of jobs disappearing or being saved. Instead, Singapore’s workforce may see a continuing shift—fewer roles built around routine tasks, and more jobs centered on managing, applying, and building AI systems.

Whether retraining keeps pace will depend less on the size of training programs and more on whether companies redesign work as quickly as they automate it.