There are many SkillsFuture courses out there. Which are the right ones to take?

Paul is a marketing executive at a small boutique digital firm in Singapore. He hopes to move into a regional role at a global bank or fintech firm, where customer acquisition and digital campaigns are increasingly data-driven. To bridge this gap, he wants to pursue training in his free time to acquire the skills needed for the role.

In preparation, he considers using his SkillsFuture Credit to take courses in prompt engineering, digital advertising and data analytics. All these courses are readily available.

The difficulty is not in finding courses. It is knowing which one will actually improve his chances of getting hired.

Does the multinational value a prompt engineering certificate? Would data analytics matter more? Or is practical experience still far more important than either qualification?

These are tough questions for any worker to answer.

Employers themselves face similarly challenging questions around business decisions. The recent Economic Strategy Review report highlights how new technologies, particularly artificial intelligence, are reshaping jobs, while firms face growing competitive pressures. 

For working professionals, career paths have become less predictable. Workers increasingly see job tasks evolve with technology, move across occupations during their careers, and repeatedly update their skills even within the same profession. 

Against this uncertain backdrop, workers constantly need to adapt and remain transition-ready. But before they can do so, they need to know which investments in skills are worth making. 

Training is one of the most effective ways to prepare workers for these transitions and gain valuable skill sets.

Yet, as Paul’s example shows, the challenge facing workers isn’t so much a lack of options in the market. Rather, it is deciding which training is worth taking.

A crowded training landscape

Singapore has made significant progress in expanding access to training and building a national system for lifelong learning. 

Through SkillsFuture Credit, employer-supported programmes and partnerships with training providers and industry, adult learning has become substantially more accessible than a decade ago before the establishment of the SkillsFuture scheme.

Today, workers can choose from thousands of SkillsFuture-supported courses in a wide array of areas such as digital technologies, sustainability, healthcare, business and advanced manufacturing. 

The expansion of choice is an important achievement. But more choice also creates a more crowded and complex marketplace. 

Training is an investment whose returns are difficult to observe beforehand. Workers rarely know the value of a course before taking it.

Instead, they rely on a confusing, inconsistent mix of signals. Employers advertise desired skills in job postings. Training providers highlight completion rates or testimonials. Friends recommend courses based on their personal experience. Online discussions suggest which skills are “hot” or “future-proof”. 

But a skill that is highly valued in one industry may have limited value in another. Depending on the training curriculum and how it’s designed, a data visualisation course may be useful for someone moving into consulting, finance or business analytics, but much less relevant for a worker applying for a front-line sales role. A cybersecurity certification may be critical for an IT security specialist, but may carry little weight for someone hoping to move into healthcare administration.

Information becomes useful only when workers can judge whether it applies to their own circumstances.

For example, a mid-career operations manager hoping to move into data analytics needs to know whether his existing experience is transferable, whether he would have to start again in a junior role and which skills would actually help with the transition.

Without these answers, even highly motivated workers may postpone training, choose familiar courses instead of more suitable ones, or avoid career transitions altogether.

The greatest risk, therefore, is not that workers fail to train. It is that they invest substantial time, money and effort in courses that have limited value for their intended career path. Such mismatches reduce confidence in lifelong learning and delay successful career transitions.

Where worker training comes in 

Admittedly, not all training decisions are made by workers themselves.

A significant share of workforce development occurs through enterprise-led training, where employers identify emerging skill requirements and train employees accordingly. Firms generally have better visibility over changing technologies, business strategies and future workforce needs.

When a manufacturing company introduces automation, for example, it can train production staff to operate new equipment before it is deployed. Likewise, when a bank adopts artificial intelligence tools, it can retrain customer service officers to use these technologies as part of their daily work.

Such training tends to produce strong outcomes because firms know precisely how new skills will be applied. Workers acquire capabilities that are immediately relevant to their jobs while building experience that can often be transferred to other employers.

However, enterprise-led training cannot solve every workforce challenge.

Companies naturally prioritise training that supports their own business needs. They may invest less in broader skills that benefit workers beyond the firm. Smaller businesses may also lack the resources to design comprehensive training programmes. Moreover, workers changing industries or occupations often need new skills before an employer is prepared to hire them.

This is where worker-led training becomes particularly important.

Workers making independent training decisions face much greater uncertainty because they lack employers’ information about future hiring needs. Strengthening worker-led training therefore requires stronger links between training providers and employers, so that workers can better identify courses leading to genuine employment opportunities.

Singapore’s place-and-train programmes provide a useful example. Employers hire workers before or at the start of training, allowing them to acquire new skills while earning a salary. Because training is directly connected to an actual job, workers face much less uncertainty about whether their investment of time and effort will lead to employment.

Similar approaches can help reduce uncertainty in other parts of the training system. Training providers could work with employers to build pathways where completing a course leads to an employer-recognised assessment, an industry project or a short work attachment that includes interview opportunities for relevant roles. This would help workers see a clearer link between their investment in training and labour-market outcomes.

What comes next

As the training ecosystem matures, simply encouraging workers to embrace lifelong learning is no longer sufficient. The system itself must become easier to navigate.

The next stage of SkillsFuture should focus not only on expanding training opportunities but also on improving the quality of information supporting workers’ decisions.

First, workers need clearer career pathways. Rather than presenting thousands of individual courses, training platforms could better illustrate how different courses combine into recognised career pathways, showing which skills are typically acquired first, what occupations they lead to, and how careers progress over time.

Career Health SG is a promising step in this direction. As a national initiative, it helps workers assess their career health, understand possible career moves and identify the skills needed for different transitions. This helps workers understand how a course fits into a broader career path.

Second, workers need better evidence on outcomes. Beyond course descriptions, they should be able to see which industries employ course graduates, what occupations participants typically enter, how long transitions usually take, and whether graduates experience meaningful wage or career progression. Such evidence would allow workers to compare courses based on labour-market outcomes rather than marketing materials alone.

Third, workers need more personalised guidance. Two individuals considering the same cybersecurity programme may require different advice depending on their education, work experience and career objectives. Better access to career coaches, sector specialists and AI-powered advisory tools can help workers assess whether a particular pathway is realistic for someone with their background, identify any missing skills and recommend suitable training options based on labour-market data.

Finally, employers themselves have an important role. Firms can make clearer which credentials they value in hiring, promotion and job redesign. Publishing preferred credentials, partnering with training providers, and participating in curriculum design would help workers distinguish between qualifications that are merely available and those that are genuinely rewarded in the labour market.

The Economic Strategy Review rightly recognises that lifelong learning should be closely connected to real work. Training policy should therefore place greater emphasis on matching, guidance and credible labour market signals, alongside expanding training provision. As labour markets become more dynamic, stronger connections between workers, employers and training pathways become increasingly important.

Singapore has been highly successful in expanding access to lifelong learning. The next phase should focus on helping workers navigate that system more effectively, so they can make informed and confident decisions about their careers.

A resilient workforce is not simply one with more training opportunities. It is one where workers can identify, choose and benefit from the right ones.