Why Early Careers Hiring Still Matters in the AI Era

HR and TA leaders across APAC are being confronted with a new, and slightly uncomfortable question: if AI can already complete much of the work once given to graduates, does early careers hiring still have a place in the budget? For some organisations, AI is now handling tasks like first-pass research, drafting and data summarisation with frightening accuracy - duties that used to sit with junior hires. However, AI and early careers talent solve fundamentally different problems, and treating them as substitutes risks a gap that can become visible too late, and very expensive to close when discovered.

Why the Short-Term Case for AI Looks Compelling

Leading companies are adopting AI over existing early careers initiatives for three key reasons: AI is available immediately, has reached cost economies of scale that early careers programmes cannot match, and can be scaled up or down without a headcount commitment. For organisations managing cost pressure, that is genuinely attractive, and it is part of why some businesses are pausing or shrinking early careers intakes.

This perspective however does ignore the long-term costs that eventually transpire. Organisations that reduce early careers hiring during a downturn or a technology shift often find, several years on, that they have an insufficient layer of mid-level professionals who understand the business from the ground up. Early careers hires are how organisations transfer institutional knowledge, build a leadership pipeline and shape culture. When there are fewer people in an organisation ready to step into senior or management roles, the cost to fill these roles can add up quickly, especially in a climate where industry or niche expertise is more expensive and competitive in supply than ever.

What AI Currently Replaces – and Where It Struggles

Across Asia, employers report that AI is having the strongest impact on functions where work is highly process‑driven, data‑intensive or operational in nature. Robert Walters observes in its Jobs of Tomorrow e-guide that 43% of employers in Asia report AI impact in administration & business support, with incrementally lower impact in IT & digital transformation (35%), finance & accounting (32%). Also notable is the significantly reduced impact in the HR (17%) and sales & marketing spaces (11%).

From this, we can draw that AI cannot replace judgement built through nuanced repetition and an understanding of how the business actually works. Robert Walters’ data also suggests that hiring patterns shifting toward roles combining technical fluency with applied judgement, rather than a reduction in the need for junior talent. The nature of early careers work is changing, but the need for people who will eventually lead teams persists.

Where will Early Careers Talent Still Matter?

AI can do more of the work graduates used to do, but it cannot build the judgement, client trust or knowledge redundancy that early careers hiring provides. Organisations that keep investing in both are the ones best placed for what comes next – Robert Walters identifies key aspects of your organisation where these should be prioritised the most.

Long-term Organisational Success

It is imperative to adopt and implement AI as a complementary tool to human talent, not as its replacement. The key factor here is long-term operational success. Despite its short-term growth, AI in its current form is still very much a new technology, with the first version of ChatGPT only launching in November 2022. Early careers talent, in comparison, has been an integral part of organisational growth since the existence of companies themselves, and the value they retain in the realms of deep thinking, relationship-building, and proactive human innovation cannot be taken lightly.

Knowledge Transfer and Security

Governance conversations around AI are increasingly looking at resilience, not just output quality. Many organisations are asking what happens if an AI system used for core processes fails, is taken offline, or is compromised by a malicious actor. Relying solely on AI to hold or process proprietary information can create a single point of failure – crippling when compromised, and a red flag for clients and regulators in all industries. Early careers hires, when deployed in tandem, build a working understanding of an organisation’s proprietary processes and information that won’t be wiped out with an errant on-off switch or data wipe. This knowledge that sits with people becomes a practical stopgap if an AI tool is unavailable or access needs restricting quickly.

Human-centric Outcomes

In sectors such as banking, insurance, professional services or healthcare, client and stakeholder relationships depend on trust built through repeated interaction rather than a single output. AI here performs a supplementary role to support these roles with research and preparation, but it cannot build the personal credibility a relationship manager, client advisor or patient-facing professional has cultivated over time. Early careers hiring is often the starting point for these client-facing paths, where new starters develop relationship-building skills, the judgement to read a room, and nuanced context of the industry’s present and future. Where an industry's advantage sits in the strength of its relationships, a pipeline of people trained for that human element is something AI cannot substitute.

Building Early Careers and AI Into the Same Plan, Not Competing Ones

The more useful question is not whether to choose AI or early careers talent, but how to combine them. Organisations are now training graduates to work alongside AI tools from day one, so hires learn to direct, check and optimise AI output rather than compete with it. Job descriptions are changing accordingly as well, with early careers programmes demanding AI literacy alongside educational degrees and industry proficiency.

HR and TA leaders should therefore reframe the decision as a workforce planning question beyond simple cost comparison. Audit which early careers tasks suit AI and which still need graduate-level judgement to build. Consider flexible hiring models like Robert Walters’ emerging talent solutions that lets intake volume move with demand, build AI fluency into onboarding through organisation-wide talent development methodologies, and assign strategic and stewardship of proprietary knowledge and client relationships across teams and platforms.

If your organisation is reassessing how early careers hiring fits alongside AI adoption, reach out for a conversation with one of our Robert Walters experts, who can help paint the bigger picture around your short- and long-term talent strategy. Our experience with many global clients around the world have taught us that every organisation works best with a bespoke balance of permanent, contingent, and AI-powered capabilities – we can show you how the best in the business get it right, efficiently and at scale.