Published: October 12, 2026
The first step into a professional career may be changing as employers adopt artificial intelligence tools that can perform some routine analysis, drafting, customer support and administrative tasks. At the IMF and World Bank meetings in Bangkok on October 12, Singapore President Tharman Shanmugaratnam warned that demand for first jobs was already weakening in sectors most exposed to AI. His remarks put a growing challenge into focus: how can graduates gain the experience needed to progress when some traditional entry-level tasks are being automated?
Why entry-level roles matter
Junior positions have traditionally done more than provide a salary. They give graduates an opportunity to learn how an organisation works, practise professional communication, understand customers and receive feedback from experienced colleagues. Tasks may include preparing first drafts, compiling data, checking records or answering common questions—work that can also be suitable for automation.
If employers reduce junior hiring without creating alternative ways to learn, the effect could extend beyond new graduates. Organisations still need experienced workers, but future senior employees must first acquire judgement and practical knowledge. A narrow focus on immediate labour savings can therefore create a skills pipeline problem over time.
AI is changing tasks, not every job in the same way
The effect of AI differs by profession, company and task. Some workers can use AI to complete routine work faster and spend more time on analysis, relationships or creative problem-solving. In other cases, employers may reorganise teams or reduce the number of people doing repeatable work.
The IMF has warned that AI could affect about 40% of jobs globally through a mix of augmentation, transformation and potential displacement. That figure should not be interpreted as a forecast that 40% of people will lose their jobs. It highlights the breadth of potential change and the need for policies that help workers adapt.
What graduates can do now
Graduates can strengthen their position by developing a combination of digital literacy and human-centred skills. Learning to use AI tools productively is valuable, but so is the ability to question their outputs, verify facts, protect confidential information and explain decisions clearly.
Employers continue to need people who understand a field deeply enough to recognise mistakes. A finance graduate who checks AI-generated analysis against the underlying data, a communications graduate who understands an audience and an IT graduate who can troubleshoot systems offer more than automated output alone.
Portfolio projects, internships, volunteering, supervised placements and practical case studies can help demonstrate capability when candidates have limited formal experience. The goal is to show how a person identifies a problem, chooses appropriate tools, evaluates results and communicates what they learned.
How employers can redesign junior work
Employers should consider which tasks are suitable for automation and which are essential learning experiences. Rather than eliminating every repetitive assignment, organisations can redesign entry-level roles so AI handles low-value steps while people practise validation, customer interaction and decision-making with supervision.
Clear mentoring structures can help graduates build judgement faster. Managers can set progression milestones, review work, explain how decisions are made and provide safe opportunities to handle more complex assignments. If teams use AI, they should also teach new staff how to evaluate results and recognise when human review is required.
Education providers face a practical challenge
Universities, colleges and training providers need to connect theory with modern workplace practice. That may involve teaching responsible AI use, project-based assessments, teamwork, communication and domain-specific problem solving. Assessment design can reward reasoning and verification rather than only the production of a polished final answer.
Industry partnerships can create supervised placements and applied projects that help learners build experience before graduation. Short courses and modular credentials may also give workers a way to update skills as tools and job requirements change, provided employers value those credentials and training remains accessible.
Policy can help avoid a wider divide
AI adoption may create new gaps between workers who have access to effective tools and training and those who do not. Public policy can help through affordable retraining, career guidance, digital infrastructure and support for small employers that lack the resources to train staff independently.
Governments and institutions also need better information about changes in hiring. Job advertisements, entry-level vacancies, wages, training opportunities and employer demand can provide a more useful picture than broad statements about automation alone. Data helps identify which sectors are changing and where targeted support may be needed.
How job seekers should assess opportunities
Candidates should look for roles that provide learning, feedback and a path to greater responsibility, not just a job title that mentions AI. During recruitment, useful questions include how new employees are trained, which tools the team uses, what work is reviewed by humans and how performance is evaluated.
Job seekers should also be wary of exaggerated promises from training providers or recruiters. No short course can guarantee employment in a changing market. Training is most valuable when it is tied to demonstrable skills, recognised by employers and complemented by real practice.
Rebuilding the first rung of the career ladder
AI may make some routine tasks cheaper, but it does not eliminate the need to develop future professionals. Employers, educators and governments will need to build better pathways that combine productivity tools with supervised learning and practical experience.
For graduates, the strongest response is neither to ignore AI nor to assume that learning one tool will secure a career. It is to become adaptable, build evidence of capability and learn to use automation responsibly. For employers, the challenge is to gain efficiency without closing the very pathways through which skilled workers are developed.
Sources for context: Reuters reporting from the IMF and World Bank annual meetings, October 12, 2026; IMF material on AI and labour markets.
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