AI Hype vs. Human Potential in China: Why Cutting Early Careers Is a Strategic Mistake
China’s rapid ascent as a global AI powerhouse has triggered a wave of transformation across industries—from smart manufacturing and fintech to healthcare and logistics. But amid this acceleration, a troubling trend is emerging: some companies are downsizing entry-level roles in pursuit of short-term automation gains. This is not just a talent issue, it’s a strategic misstep.
In this blog we’ll look at the dangers of stripping your early talent pipeline to chase AI gains, and what leaders should do instead. Because chasing small-term gains is not an innovation, it’s erosion.
If you're in the C-suite, now is the time to pause, assess and lead with clarity. The decisions you make today will define whether your organization thrives or stagnates in the AI era.
The Illusion of Efficiency in China’s AI Boom
China’s AI sector is projected to exceed ¥1 trillion in annual revenue by 2030. With over 4,300 AI firms and state-backed initiatives like the Next-Generation AI Development Plan, the pressure to automate is intense. Yet, the reality is more nuanced.
As James Milligan, Global Head of Technology, Engineering and Contracting at Hays, puts it: “What we’re seeing isn’t a collapse in demand, but a transformation in how and where graduates are being hired.” The decline in early-career roles isn’t solely driven by AI, it’s also shaped by economic pressures and shifting hiring preferences.
With economic turmoil impacting many organizations in recent years, it’s understandable that some may see AI and automation tools as an easy way to get back on track. However, cutting junior roles before fully understanding the technology’s capabilities is a strategic misstep.
The risk of a hollow organization
Gen Z will make up 27% of China’s workforce by 2025. They are digital natives, fluent in AI tools like DeepSeek and Feishu, and eager to lead innovations. Removing them from the equation means losing:
- Creating a knowledge vacuum: Junior staff often handle foundational tasks that build institutional memory. Without them, you lose the ability to transfer knowledge upward and across teams. This weakens continuity and increases reliance on external hires who lack context.
- Weakening your talent pipeline: Entry-level roles are the launchpad for future leaders. If you eliminate these roles, you’ll face a bottleneck in two to three years when mid-level talent is needed. Succession planning becomes reactive, expensive and risky.
- Stalling innovation: Gen Z are digital natives. They’re already using AI tools and can help drive adoption from the ground up. Cutting them out of the equation means losing the very people who could help you integrate AI meaningfully and responsibly.
Action for leaders: Audit your early-career roles not for redundancy, but for reinvention. Identify where AI can support, not replace, junior talent. Build hybrid workflows that combine automation with human oversight and ensure mentorship structures are in place to accelerate development.
Lead with strategy, not hype
AI is evolving but it hasn’t yet delivered the large-scale transformation many anticipated. According to James Walsh, Business Director for Cyber, Cloud and Data at Hays UK&I: “Organizations are assessing whether AI will actually deliver, and not many are confident it can do more than enhance, at this moment in time.”
That’s why the smartest leaders are resisting hype and investing in structured AI training for early talent. This approach doesn’t just retain ambitious Gen Z professionals, it builds a workforce equipped to work with AI, not being replaced by it.
Amanda Whicher, Hays UK&I Technology Director added: “The hype around AI is much bigger than the reality of what we're actually seeing across organizations.” Cutting entry-level roles now is a knee-jerk reaction to a technology that’s still maturing.
Medium-term thinking is your competitive advantage
Ben Carter, Director of Emerging Talent Solutions at Hays UK&I, puts it plainly: “If AI is impacting early careers, I would say those companies are lacking medium-term thinking. They will choke an ecosystem when they need mid-level roles if they automate the early career roles.”
Here’s what medium-term thinking looks like in practice:
- Embed AI learning across disciplines: Don’t silo AI knowledge in IT or data teams. Make AI literacy a core part of onboarding, training and leadership development. This builds resilience and cross-functional capability.
- Invest in upskilling at every career stage: AI adoption isn’t a one-time event; it’s a continuous evolution. Equip junior talent with foundational AI skills, but also ensure senior leaders are fluent in its strategic implications.
- Empower early talent to lead AI adoption: Gen Z are already experimenting with AI tools. Give them space to innovate, test and share learnings. Create reverse mentoring programs where younger employees teach senior staff how to use AI effectively.
Action for leaders: Build a three-year talent roadmap that aligns AI adoption with workforce development. Identify which roles will evolve, which will be created and how early-career talent can be nurtured to fill future gaps.
Final Thought: Build, Don’t Burn
China’s AI revolution is real—but it’s still maturing. The smartest companies won’t chase hype. They’ll invest in people.
Gen Z in China is digitally resilient, purpose-driven, and eager to shape the future. Your job is to make sure they’re still in the room.
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