Commentary: Workers shouldn’t have to figure out AI on their own

The Economic Strategy Review can set the national direction for Singapore’s AI transition but turning that into real change for employees means redesigning work, job by job, says NTU’s Trevor Yu.

SINGAPORE: No worker really experiences “economic transformation”. They feel the change in a new system to learn or a job scope that keeps shifting. Increasingly, it is a manager asking them to “use more AI”.

For many workers, artificial intelligence raises uncomfortable questions: Will I simply be expected to do more with fewer resources? Am I automating myself out of a job? If my employer wants me to use AI, why can't someone explain what using it well actually looks like?

Managers are asking difficult questions too: Which tasks should be delegated to AI and which should remain with my team? How do I evaluate performance when employees use AI to do the work? How do I encourage my staff to experiment when I am still learning the technology myself?

Part of what makes this change difficult is that everyone is still feeling their way forward.

The recommendations from the Economic Strategy Review (ESR), released in May, matter because they recognise AI as a national workforce challenge, not simply a technology issue. They put AI literacy alongside the uniquely human strengths that will complement it – critical thinking, communication and empathy – while strengthening support for lifelong learning and career transitions.

The challenge now is turning these national priorities into changes that workers can actually experience in their jobs.

AI IS CHANGING THE JOB WE ALREADY HAVE

Singapore has successfully navigated previous waves of economic restructuring. But those transitions often involved helping workers move into higher-value industries and better jobs. AI has made today's challenge different.

Workers may not need to move into entirely new jobs across sectors. For many, the job they already have is changing beneath their feet.

Consider a customer service officer using an AI assistant. The system may summarise previous interactions, suggest responses and recommend solutions.

So beyond serving the customer, the employee now also needs to decide whether to trust those recommendations, when to probe further, and how to respond empathetically when a customer's situation falls outside what the AI can recognise.

The technology does not eliminate the need for judgment. The same is true for many other knowledge workers, from HR professionals and analysts to accountants and marketers.

As AI increasingly takes on routine tasks such as information gathering, drafting content and initial analysis, human work can shift towards interpreting information, making decisions, solving problems, exercising judgement and building relationships.

DON’T LEAVE WORKERS TO FIGURE IT OUT THEMSELVES

But employers cannot simply introduce AI and expect productivity to improve. Nor can they expect workers to figure things out for themselves.

Yet much of the discussion about helping workers adapt to AI has focused on acquiring new skills. Upskilling and reskilling remain important, but skills alone will not determine success. Technology creates value only when organisations redesign work so that people and AI complement one another.

Organisations need to be able to answer practical questions: Which tasks should AI perform and which remain human-led? How should responsibilities change? How should performance be measured when workers use AI tools?

We are still at the early stages of this deeper redesign. The first Ministry of Manpower (MOM) report on AI adoption earlier this year found that while 28.5 per cent of firms have begun adopting AI, only 3.8 per cent are integrating it into their core processes.

A 2025 digital economy survey by the Infocomm Media Development Authority (IMDA) found that 63 per cent of firms already using AI expect to redesign jobs to better integrate it into daily operations.

The risk in the meantime is that AI simply gets added onto existing jobs. Employees will surely be expected to continue meeting existing targets while also learning new tools and incorporating AI into their daily work.

AI then starts to feel less like a tool to help workers and more like yet another demand placed on them.

SUPPORT IN EVERYDAY WORK

Meaningful support has to show up in the way work is designed and managed, not just in courses and workshops.

Workers need opportunities to develop new skills, but employers also need to create opportunities to apply those skills. That means giving people time to practise, permission to experiment, colleagues to learn alongside and managers who can coach rather than simply supervise.

This places new demands on HR leaders. Many HR systems were designed for a world in which jobs changed gradually and could be clearly defined.

Today, work is evolving much faster. Job descriptions, competency frameworks, career pathways and performance management systems will need continual review as technologies reshape work.

Line managers may face an even more immediate challenge. Change becomes real for employees, not through government announcements or corporate town halls, but through their managers’ day-to-day decisions – what work is prioritised, what constitutes good performance and what support looks like.

Yet many managers are navigating these questions for the first time themselves.

Perhaps the most important leadership skill in this environment is not having all the answers. It is creating the conditions for teams to confront uncertainty and learn together.

Managers who explain the purpose of change, encourage experimentation, acknowledge uncertainty and involve employees in redesigning work are more likely to build trust than those who simply instruct staff to "use more AI".

Employers therefore have to make job redesign a deliberate effort.

THE REAL TEST

The organisations most likely to succeed will not be those that simply invest the most in technology or training. They will be those that redesign work while building cultures where learning is continuous, informal and embedded in everyday work.

Workers should not have to figure out AI on their own. Neither should managers.

The ESR provides an important roadmap for navigating Singapore's next phase of economic transformation. Its success, however, will ultimately depend on millions of decisions made every day inside organisations which determine whether AI leads to better-designed jobs or simply becomes more change for workers to cope with.

Kang Yang Trevor Yu is an associate professor in the division of leadership, management and organisation at the Nanyang Business School, Nanyang Technological University.