As 2025 draws to a close, layoff announcements have sharply increased, driven by the dual pressures of generative AI adoption and economic tightening. Corporations across various sectors are aggressively restructuring, often cutting middle management and entry-level roles that AI can now perform more cheaply and efficiently. While this move may yield immediate cost savings, experts warn it could undermine the critical process of skill development and career advancement within organizations.
Traditionally, employee growth depended on the expert-novice relationship—learning by doing alongside more experienced colleagues. This hands-on mentorship, which has been fundamental to human learning for millennia, is now at risk. Generative AI accelerates workflow, but it also reduces opportunities for novices to gain the practical experience needed to ascend the corporate ladder. Without these foundational roles, companies may face a “market failure” in cultivating future middle managers and senior experts.
Studies show that in jobs where AI can perform most tasks, worker numbers have declined by about 14% over five years. This trend is visible even in high-skill fields; for example, junior surgeons now participate minimally in robotic surgeries, a pattern expanding with AI-assisted tasks. Employers, concerned about the short-term costs and talent poaching risks, may hesitate to invest in training young workers, further jeopardizing the talent pipeline.
By 2030, nearly 40% of workers’ core skills worldwide are expected to be disrupted by AI and digital technologies. However, AI is currently limited in handling complex interpersonal and judgment-based tasks, such as client advising by senior lawyers. The challenge lies in how organizations will prepare early-career employees for these advanced roles if entry-level jobs continue to vanish.
Experts emphasize the urgent need for companies to rethink their workforce models. This includes integrating advanced technology while preserving opportunities for novices to learn through experience. Public policy interventions and external training intermediaries may be necessary to address this looming crisis.
Ultimately, firms that successfully blend automation with workforce development are poised to thrive. Those that prioritize short-term savings at the expense of training risk long-term difficulties in sustaining growth and innovation. The future of work, shaped by AI, demands a balance between efficiency and the preservation of human expertise to ensure a robust talent pipeline for years to come.