AI's Impact on Entry-Level Jobs: Future Workforce Challenges

Explore how AI impacts entry-level jobs and workforce development in Singapore. Discover strategies for balancing automation with employee growth.

**AI MAY REPLACE ENTRY-LEVEL WORK. WHO WILL BECOME TOMORROW'S EXPERTS?**

*Singapore's President Raises A Workforce Concern That Businesses Cannot Afford To Ignore*

Singapore President Tharman Shanmugaratnam has warned that artificial intelligence (AI) is reducing employment opportunities for fresh graduates, raising concerns about the future of entry-level work. Speaking at the IMF and World Bank annual meetings in Bangkok on 12 October 2026, he highlighted weakening demand for first jobs, particularly in industries heavily exposed to AI.

The warning raises an important management question. If businesses increasingly automate tasks traditionally assigned to junior employees, how will those employees gain the experience required to become tomorrow's managers, specialists and industry experts?

AI adoption promises greater productivity and lower operating costs. However, businesses must also consider how automation affects employee development, knowledge transfer and long-term organisational capability. While technology can perform routine tasks efficiently, companies still need people who understand how businesses operate and how decisions should be made.

**Entry-Level Jobs Have Always Served A Bigger Purpose**

Entry-level positions have traditionally provided employees with opportunities to understand daily business operations. Administrative work, data processing, documentation and routine activities may appear repetitive, making them attractive candidates for automation. However, these responsibilities also allow junior employees to learn how departments interact, why procedures exist, how customers behave and what happens when business processes fail.

An accounts assistant gradually develops an understanding of payment cycles and financial controls, while a purchasing executive learns to evaluate suppliers and coordinate delivery schedules. Similarly, a junior operations employee becomes familiar with the relationship between inventory, sales and customer expectations. These experiences help employees develop professional judgement that cannot always be obtained through formal training alone.

When companies eliminate too many entry-level opportunities, they may also weaken the traditional pathway through which experienced employees are developed. Although AI can complete certain tasks faster, it does not automatically replace the learning experience employees gain from handling real business responsibilities.

**AI Can Improve Productivity Without Eliminating Learning Opportunities**

Automation does not necessarily require organisations to remove junior positions. Instead, businesses can redesign these roles around higher-value responsibilities while allowing AI to handle selected repetitive tasks. This approach enables companies to improve productivity without removing important opportunities for employees to develop their professional skills.

AI agents can support activities such as information retrieval, routine reporting and workflow assistance. Employees can then spend more time investigating exceptions, communicating with stakeholders and understanding the reasons behind business decisions. Rather than measuring performance primarily through the number of transactions processed, managers can place greater emphasis on problem-solving, process understanding and analytical skills.

However, these benefits require deliberate management. Giving employees access to AI tools does not automatically develop their judgement. Businesses still need supervision, structured learning opportunities and clear responsibilities. Employees must understand how to evaluate information, recognise potential errors and make appropriate decisions instead of relying entirely on automated recommendations.

**Business Knowledge Must Not Remain With Individual Employees**

The workforce challenge extends beyond fresh graduates. Many organisations depend heavily on experienced employees who understand internal procedures, customer requirements and operational exceptions. Their knowledge often develops through years of handling different situations, resolving problems and making business decisions.

When these employees resign or retire, valuable knowledge may disappear with them. Although new employees can access existing documents, they may struggle to locate the correct information or understand why certain decisions were made. This problem becomes more serious when departments maintain separate spreadsheets, documents and communication records without a consistent method of organising information.

Businesses should therefore treat organisational knowledge as an important operational resource. Standard operating procedures, transaction histories, approval workflows and documented business rules should remain accessible to authorised employees. Centralised information can support training and operational consistency, allowing junior employees to learn from established procedures while helping managers maintain greater control over daily activities.

Preserving business knowledge also reduces dependence on individual employees. When information is properly documented and organised, companies can manage staff transitions more effectively and maintain operational continuity even when experienced employees leave the organisation.

**ERP And AI Agents Can Support More Structured Learning**

Enterprise Resource Planning (ERP) systems provide a foundation for connecting business activities across departments. Purchasing, inventory, sales, finance and other functions can operate within a more consistent information environment, helping employees understand how their responsibilities affect the wider organisation.

For procurement employees, professional development involves more than learning how to create purchase orders. They also need to understand purchasing approvals, inventory availability, supplier performance and the financial consequences of procurement decisions. Access to connected business information can help employees recognise these relationships and develop a broader understanding of operational processes.

AI agents can further support this environment by assisting authorised users with information retrieval, operational records and matters requiring attention. Instead of spending excessive time searching through different documents or systems, employees can focus on reviewing information, investigating problems and understanding business requirements.

Nevertheless, technology should support learning rather than replace it. Companies must continue providing appropriate training and ensuring that employees understand the information presented by AI. Human judgement remains essential, particularly when decisions involve financial risks, customer relationships or operational exceptions.

**Human Resource Management Must Evolve Alongside Automation**

As AI changes job responsibilities, human resource management must also adapt. Traditional job descriptions may no longer accurately reflect the skills employees need to perform effectively. Organisations should review how they recruit, train and evaluate employees, recognising that analytical thinking, communication, adaptability and business judgement may become increasingly valuable alongside technical knowledge.

Human Capital Management (HCM) systems can support workforce administration, employee information management and structured HR processes. These capabilities provide an operational foundation for managing employees as organisations introduce new technologies and adjust existing responsibilities.

However, technology alone cannot create a successful workforce development strategy. Management must determine which skills should be retained, which responsibilities can be automated and how employees will gain practical experience. Businesses also need to ensure that experienced employees have opportunities to transfer their knowledge to younger colleagues.

A sustainable workforce strategy should consider productivity improvements alongside employee development rather than treating them as competing objectives. Companies that invest in both technology and people may be better positioned to adapt to changing business requirements while maintaining the expertise needed for long-term growth.

**Multiable Supports Connected Business Operations**

Multiable's aiM18 enterprise solutions bring together ERP, HCM and AI Agent capabilities to support more connected business operations. Its ERP capabilities help organisations manage business information and operational processes across departments, while HCM supports human resource management. AI Agent capabilities can assist with selected business activities and information access, helping employees work more efficiently within established operational processes.

Multiable's no-code and low-code capabilities also allow organisations to configure workflows according to operational requirements, helping businesses adapt processes as responsibilities evolve. By maintaining more consistent business information and structured workflows, organisations can reduce unnecessary manual data handling while improving operational visibility.

For companies adopting AI, the objective should extend beyond reducing manual work. Reliable information, consistent processes and appropriate access controls can help employees work more effectively while preserving organisational knowledge. These capabilities provide a foundation for businesses seeking to combine digital transformation with long-term operational development.

Importantly, connected enterprise systems can support employees at different stages of their careers. Junior employees benefit from clearer business processes and accessible information, while experienced employees can focus on more complex responsibilities that require professional judgement and operational expertise.

**The Future Workforce Still Needs A Starting Point**

President Tharman's warning highlights a challenge that businesses should address before entry-level opportunities become increasingly limited. AI can process information, automate routine activities and support operational decisions, but companies still require employees who understand customers, exercise judgement and take responsibility for business outcomes.

If organisations focus exclusively on immediate labour savings, they risk weakening the talent pipeline needed to sustain future operations. Today's junior employees are potential future managers, specialists and business leaders. Without sufficient opportunities to gain practical experience, companies may eventually face difficulties developing the expertise required for more complex responsibilities.

The more valuable approach is to use AI to improve productivity while creating opportunities for employees to develop skills that technology cannot fully replace. The future of work should not simply involve fewer people performing fewer tasks. It should involve better business processes, stronger organisational knowledge and employees who are equipped to contribute at a higher level.

**[Contact Multiable today](https://wa.me/+6585225261)** to discover how aiM18 ERP, HCM and AI Agent solutions can support connected operations, workforce management and sustainable digital transformation.