I keep hearing a familiar statement in leadership meetings:
“As AI scales, we’ll need fewer entry-level hires.”
It sounds logical. Automation takes over repetitive tasks. Senior professionals handle the complex work. The base of the pyramid shrinks.
But as I look across Global Capability Centers (GCCs) and large enterprises, the real story is more complex. Yes, early-career hiring has slowed, but declaring the bottom of the pyramid dead is premature. The real pressure point may, in fact, be in the middle.
Reach out to discuss this topic in depth.
Why the entry level workforce still matters
They’re the culture carriers. Entry-level professionals drive the energy, curiosity, and collaboration that make organizations dynamic. Remove that layer and you risk losing the cultural backbone that keeps teams evolving.
They’re more AI-ready than we think. This new generation isn’t resisting Artificial Intelligence (AI), they’re building with it. From automating workflows to using copilots for analytics, they’re already experimenting where experienced professionals are still adapting. In a recent GCC leader pulse, over 70% said entry-level staff were more open to AI experimentation than mid-career colleagues.
They’re highly adaptable. Mid-career professionals are unlearning; entry-level hires are learning anew. In a world where skills depreciate fast, adaptability is what sustains competitiveness.
The real story behind cost and capability
A fresher in a financial services India GCC tech role today earns around Indian Rupee (INR) 11 lakhs, while someone with eight to nine years’ experience in the same function earns about INR 40 lakhs. That’s natural career progression, and with increasing responsibilities.
But organizations are realizing something interesting: When you combine entry-level adaptability with AI-driven automation, you can reconstitute work that once depended on mid-level execution. Everest Group analysis shows that 60–70% of standardized workflows, code testing, reconciliations, report generation, can already be AI-enabled and managed by trained early-career professionals.
This does not mean experience is redundant. It means experience must move up the value chain, toward orchestration, insight synthesis, and stakeholder engagement.
The data reality check
Yes, some entry-level roles are under pressure. Stanford’s Digital Economy Lab found employment for workers aged 22–25 in AI-exposed roles dropped 13% since late 2022. The biggest impacts are in highly codifiable tasks, software engineering, customer service, and data entry, where automation substitutes, not augments, work.
But here’s the nuance: roles where AI complements human work, analytics interpretation, creative content, domain-specific operations, are holding steady or even expanding. Harvard Business Review warns that cutting entry-level pipelines entirely is “dangerously short-sighted,” as it removes the talent feeders organizations depend on for future leadership.
In other words, the quantity of entry-level work might shrink, but its strategic importance is rising.
The middle that must move
If AI is transforming execution and entry-levels are adapting fastest, the mid-layer must evolve to stay relevant. That evolution looks like this:
- From execution to orchestration. Leading hybrid teams where human judgment meets AI precision
- From expertise to systems thinking. Understanding how business, data, and tech interconnect
- From knowledge protection to knowledge flow. Acting as enablers who scale learning rather than gatekeeping it.
The middle layer that fails to shift risks being overtaken by both automation, and the ambition of the entry-level workforce.
The new productivity equation
AI is amplifying the productivity of early-career professionals, but increased throughput can bring higher churn. The leadership challenge is to preserve continuity without stifling innovation. That requires three enablers:
- Dynamic knowledge management – Living repositories that evolve daily, not static documentation.
- Mentorship and enablement – Redefining the mid-layer as coaches who unlock, not control.
- AI-augmented business engagement – Tightening the loop between task execution and business outcomes.
Organizations investing in these enablers are seeing compounding returns in speed, innovation, and engagement.
Let’s stop writing the entry level workforce layer’s obituary
AI may have slowed the growth of hiring for the entry level workforce, but it hasn’t nullified its necessity. This generation brings curiosity, digital fluency, and a bias for learning that algorithms alone cannot replicate.
The most successful organizations won’t be those that automate the most tasks. They’ll be those that combine automation with human adaptability, judgment, and cultural energy. And no one represents that better than the entry level workforce that’s learning with AI.
Final thought
AI will reshape the bottom of the pyramid, not erase it. If companies get mentorship, knowledge systems, and role design right, entry-level professionals will continue to be the foundation, not the casualty, of the AI-powered enterprise.
If you found this blog insightful, you might also enjoy our recent piece, The Rise Of Holistic Global Capability Center (GCC) Set-up Solutions: Partnerships, Playbooks, And Pitfalls | Blog – Everest Group, which explores another topic relating to GCCs.
To discuss more on the ever-evolving landscape of GCCs and AI, please contact Bharath M ([email protected]).
For the first time ever, Engage is coming to India – live in Bengaluru on November 13, 2025. This one-day event marks a pivotal moment for leaders across Global Capability Centers (GCCs), Global Business Services (GBS), and shared services organizations navigating fast-evolving priorities.
For more information, visit Home | Engage – Bengaluru 2025
