The Biggest AI Skill Isn't Technical, Says UOB HR Chief and NUS-ISS

Problem-solving, curiosity, and the willingness to adapt matter more than technical coding ability when it comes to thriving alongside AI, according to two of Singapore's most senior voices on workforce transformation. In a wide-ranging interview on The Business Times' "Lens on Singapore" podcast, UOB's head of group human resources Dean Tong and Victor Chua, deputy CEO of the National University of Singapore's Institute of Systems Science, argued that the most valuable workers in the AI era will be those who combine domain expertise with the ability to apply AI tools effectively.

Chua described a yawning shortage not just of AI specialists like data scientists and ML engineers, but of what he calls "AI bilinguals" — professionals in fields like accounting, law, and HR who know their domain deeply and can also wield AI to do their jobs better. "It is AI plus X, X being your respective domain knowledge," he said, adding that experience becomes augmented rather than rendered obsolete. Tong echoed the sentiment, pointing out that UOB's recent workforce reductions had "nothing to do with AI" but were driven by process redesign, while the bank continues to hire actively for roles in anti-money laundering, financial crime prevention, and its new Innovation Group focused on AI rollout.

The conversation underscored a reality that Singapore's corporate landscape is beginning to grapple with: the skills that make someone irreplaceable are shifting from the purely technical toward the distinctly human. Chua put it bluntly: "AI does not confer onto you legitimacy." What does, he argued, is judgment, accountability, trust, and the ability to make sense of complexity. "AI should take the robot out of me. The way I stand apart from the robot is I need to become more human." Tong added that the best predictor of success in UOB's internal reskilling programme — which boasts an 80 per cent success rate — is simply the employee's willingness to change.

Why it matters for Singapore: As Singapore pushes to become a global AI hub, the temptation is to focus on churning out more engineers and data scientists. But the UOB and NUS-ISS perspective suggests the real bottleneck may be softer: a shortage of workers across every sector who can bridge the gap between domain expertise and AI capability. That has implications for SkillsFuture, university curricula, and corporate training budgets — and suggests that Singapore's competitiveness in AI will depend as much on humanities graduates who learn to code as on computer science graduates.