Higher pay, but who will hire? Budget 2027’s AI warning for fresh graduates — Low Kah Choon and Chong Say Lee

OCTOBER 13 — Silicon Valley may be offering an early warning about the future of graduate employment. As artificial intelligence (AI) becomes increasingly capable of performing tasks traditionally assigned to junior employees, the greatest concern may no longer be workers losing their jobs, but fresh graduates struggling to secure their first one.

An August 2026 Stanford University study found that employment among Americans aged 22 to 25 in highly AI-exposed occupations was approximately 19 per cent below where it would have been had it grown alongside less-exposed occupations. More significantly, the adjustment appeared primarily through reduced hiring rather than increased dismissals (Brynjolfsson et al., 2026). Although the study does not establish that AI caused the entire employment gap, it raises a troubling possibility: companies may not need to replace existing employees. They may simply stop hiring as many newcomers as possible.

While Silicon Valley is beginning to question how many entry-level employees businesses still need, Malaysia is moving towards higher wage expectations. These two developments may soon present employers with a difficult choice.

On October 9, 2026, Prime Minister Datuk Seri Anwar Ibrahim announced an increase in the national minimum wage from RM1,700 to RM2,000, alongside a proposed RM2,500 wage floor for semi-skilled workers and graduates. Government-linked companies (GLCs) and government-linked investment companies (GLICs) also committed to raising their living-wage benchmark from RM3,100 to RM3,400, potentially benefiting approximately 230,000 employees (Prime Minister’s Office of Malaysia, 2026).

Interestingly, the same Budget encourages greater AI adoption. It allocates RM30 million to help 4,000 micro, small and medium enterprises adopt AI and automate operations, alongside initiatives for AI training and certification (Prime Minister’s Office of Malaysia, 2026). These initiatives reflect two ambitions. The government wants workers to receive better remuneration while encouraging businesses to adopt technologies that improve productivity and reduce operating costs. Both objectives are important, but their interaction deserves closer examination.

As artificial intelligence (AI) becomes increasingly capable of performing tasks traditionally assigned to junior employees, the greatest concern may no longer be workers losing their jobs, but fresh graduates struggling to secure their first one. — AFP pic

What happens when the cost of hiring inexperienced workers increases while AI makes some of their responsibilities cheaper to perform?

Consider a company recruiting fresh graduates to prepare reports, process invoices, maintain records and perform routine administrative duties. These responsibilities provided newcomers with opportunities to enter the workforce and gradually acquire practical experience. Today, AI can automate substantial portions of such tasks, although human supervision and accountability remain necessary. From an employer’s perspective, the decision is increasingly about costs and productivity.

Would it be more economical to hire additional graduates at higher salaries, together with the necessary training and supervision, or invest in AI-assisted operations that could achieve comparable output with fewer employees?

Higher wages may improve motivation, employee retention and recruitment quality. However, they do not automatically generate equivalent increases in productivity. If remuneration expenses rise without corresponding improvements in output or revenue, profit margins may come under pressure, encouraging employers to reconsider their recruitment and operational strategies.

For example, a manufacturer employing 40 entry-level workers at RM2,000 monthly would incur an additional RM240,000 in annual basic payroll if their salaries increased to RM2,500. For a hypothetical company earning RM500,000 in annual profit before tax, this would represent 48 per cent of its existing profit, assuming revenue and other costs remain unchanged.

Such a scenario does not suggest that higher wages inevitably cause unemployment. Nevertheless, it illustrates why employers may consider automation, restructuring or more selective recruitment when labour costs rise faster than the value generated.

The concern becomes particularly relevant if higher wage requirements are eventually expanded across the private sector. For now, the RM3,400 living-wage benchmark applies to participating GLCs and GLICs, not all private corporations or fresh graduates. No universal private-sector expansion has been announced. However, before considering similar requirements for other employers, their financial capacity and industry conditions must be carefully assessed. A labour-intensive manufacturer operating on narrow margins may face considerably greater pressure than a highly profitable technology company.

The challenge becomes more complicated when we examine Malaysia’s existing graduate employment problem. According to the Department of Statistics Malaysia, 35.2 per cent of employed tertiary-educated individuals were working in semi-skilled or low-skilled occupations in the second quarter of 2026 (Department of Statistics Malaysia, 2026). Similarly, the World Bank’s April 2026 Malaysia Economic Monitor reported that only 24.6 per cent of recorded formal private-sector vacancies in 2025 were classified as high-skilled, despite employers continuing to experience shortages in specialised technical and professional occupations (World Bank, 2026).

These findings reveal an important contradiction. Malaysia produces graduates, yet many cannot secure employment appropriate to their qualifications. At the same time, employers struggle to recruit individuals with certain technical competencies, industry-specific knowledge and practical problem-solving abilities. The problem is therefore not simply whether graduates are sufficiently qualified. It also concerns whether universities are developing the competencies required by employers and whether the economy is creating enough suitable jobs to utilise those competencies.

Academic qualifications provide important foundations, but workplace experience remains essential. A fresh graduate may understand management principles without yet possessing the judgment needed to resolve production disruptions, evaluate complex business decisions or manage unexpected operational problems.

Industrial training helps narrow this gap. However, a four- to six-month placement, as practised in some university programmes, may offer limited opportunities to develop independent problem-solving abilities, particularly when students are assigned predominantly routine administrative work. This brings us back to the employer’s dilemma.

If companies must invest heavily in training inexperienced graduates while paying higher starting salaries, will they continue doing so when AI offers increasingly capable alternatives for routine entry-level tasks?

The concern is not that fresh graduates are undeserving of better remuneration. Rather, higher wage expectations without corresponding improvements in graduate capabilities and the creation of productive jobs may intensify the existing mismatch between employers’ expectations and the available workforce.

The immediate consequence could be fewer entry-level opportunities, particularly in occupations where routine cognitive tasks are increasingly automated. This does not necessarily mean mass layoffs or an immediate increase in national unemployment. As the Stanford findings suggest, the adjustment may instead appear through reduced recruitment, longer job searches and greater difficulty securing suitable employment.

Higher salaries could therefore benefit graduates who successfully enter the workforce while leaving others facing increasingly competitive recruitment conditions. Whether this happens will depend on how employers balance automation, training and business expansion. Yet the longer-term consequence may be even more concerning.

Today’s junior executives are tomorrow’s managers, engineers and organisational leaders. Their professional judgment develops through years of practical experience, mentoring and progressively greater responsibilities. If companies increasingly depend on experienced employees supported by AI while reducing graduate recruitment, who will replace those professionals when they retire or leave?

A company may achieve immediate cost savings by reducing entry-level positions, only to discover years later that it has weakened its own talent-development pipeline. AI can assist with analysis and decision-making, but it cannot automatically transfer the practical judgment accumulated through years of workplace experience.

An immediate improvement in operational efficiency could eventually create a shortage of experienced professionals. This is why Malaysia should not treat higher wages, AI adoption and graduate education as separate policy objectives. If businesses are expected to offer better remuneration, universities and industries must also strengthen the pathways through which graduates acquire productive competencies.

Malaysia already introduced the two-year university and two-year industry (2u2i) model in 2016. According to the Malaysia Higher Education Blueprint 2026-2035, work-based learning and 2u2i initiatives had expanded to 130 programmes by 2024 (Ministry of Higher Education Malaysia, 2017, 2025).

Rather than introducing another education model, greater attention should be given to improving the quality and reach of existing industry-integrated learning. Students should be exposed to genuine organisational challenges, practical problem-solving and AI-assisted work, rather than merely completing routine administrative assignments. However, stronger graduate preparation must also be accompanied by the creation of more high-skilled positions.

Budget 2027’s AI initiatives present an opportunity to support this transition. Instead of encouraging businesses to view AI primarily as a substitute for inexperienced employees, incentives could promote AI-assisted graduate development, structured workplace training and the creation of higher-value employment.

Before expanding wage requirements more widely, policymakers should therefore examine not only employers’ financial capacity but also their willingness to recruit and develop young workers. The success of wage reform should be measured through graduate hiring, skills-related underemployment, productivity growth and long-term career progression, rather than salary improvements alone.

Higher wages remain an important objective, particularly as young Malaysians face increasing living costs. However, better remuneration cannot independently resolve the structural mismatch between education and industry, especially when AI is changing the nature of entry-level employment.

Malaysia must ensure that wage reform does not move faster than the development of productive employment opportunities and workplace capabilities. Otherwise, a policy intended to improve graduates’ welfare could unintentionally make the first step into professional employment more difficult.

Malaysia’s challenge is not simply raising graduates’ starting salaries, but ensuring employers remain willing to hire them. Sustainable wages require productive capabilities, not policy enforcement alone. Education must equip graduates with the skills to create real value for industry, while businesses must continue investing in young talent. After all, what good is a higher minimum salary for graduates if fewer employers are willing to offer them their first job?

* Dr Low Kah Choon is a Senior Lecturer at the School of Government (SoG) and a Research Fellow at the Institute of Local Government Studies (iLGS) and Dr Chong Say Lee is a part-time lecturer for Professional and Continuing Education (PACE), both at Universiti Utara Malaysia, and can be reached at [email protected] and [email protected].

** This is the personal opinion of the writer or publication and does not necessarily represent the views of Malay Mail.

References:

Brynjolfsson, E., Chandar, B., & Chen, R. (2026). Canaries in the coal mine? Six facts about the recent employment effects of artificial intelligence (Revised version, August 12, 2026) [Working paper]. Stanford Digital Economy Lab.

Department of Statistics Malaysia. (2026, August 27). Labour market review (LMR), second quarter 2026.

Ministry of Higher Education Malaysia. (2017, October 10). 2u2i.

Ministry of Higher Education Malaysia. (2025). Malaysia higher education blueprint 2026-2035.

Prime Minister’s Office of Malaysia. (2026, October 9). Speech: The fifth Madani Budget 2027 by YAB PM.

World Bank. (2026). Malaysia economic monitor, April 2026: Raising the ceiling, raising the floor — The jobs agenda as a productivity agenda.