AI is speeding workforce turnover. But your next great hire may already be working for you

AI is accelerating a transformation of work unlike anything we have seen before. Roles are evolving, skills are shifting, and organizations are under constant pressure to adapt at speed. According to the World Economic Forum, 170 million new jobs will be created by 2030 – but 92 million will also be displaced, underlining the scale and urgency of this transition.

This trend is equally evident in China. According to the National School of Development at Peking University, skill mismatches in China’s labour market have intensified under the impact of AI; the share of jobseekers ending up in roles misaligned with their skills and education level rose from 52% to 64.9%. And experts from the Development Research Center of the State Council highlight a growing decoupling between the pace of technological change and the ability of the workforce to adapt in China.

AI is exposing weaknesses in workforce systems that were designed for more stable job architectures as most organizations lack the data and visibility to map skills to roles and opportunities: career pathways are harder to navigate, and transformation often arrives faster than people systems can respond. Even though capability exists within the organization, it is not always visible or accessible in a way that allows it to be effectively mobilized. This is where a familiar response to disruption begins to carry a hidden cost.

Based on our observations, many organizations today still instinctively look outside: Hire new skills, replace old roles and bring in new expertise. In many cases, this is seen as the fastest way to react to immediate capability gaps. But it can also become an expensive reflex action. In a labour market where skills are moving faster than job titles, buying in talent may address today’s vacancy, while leaving tomorrow’s adaptation challenge unresolved.

Drawing on a survey of more than 8,000 white-collar workers and 3,000 HR leaders, the Adecco Group and LHH’s 2026 Redeployment and Outplacement Trends Report directly questions the economic case for external hiring strategies:

The cost of external hiring is higher because the organization pays twice: first through lost capability, team instability and reduced morale, then again through the cost of rebuilding capability by looking elsewhere. This cycle also erodes trust among remaining employees, especially when support is promised on paper but is not visible or easy to access in practice.

What’s more, AI’s rapid evolution is also deepening the trust crisis between organizations and employees. While workers are ready to embrace and collaborate with AI, organizations are struggling to transform the AI ambitions into clear and actionable pathways. Our latest Business Leaders Global Report shows:

These findings reveal the trust cost behind the fire-and-rehire model. While employees need clear direction through AI-driven change, many organizations are still unprepared. As work evolves, employees are left asking not just: “Will my job exist?” but ‘Will my work still matter?”. In the absence of visible pathways and timely support, trust erodes quietly, leaving companies with a workforce that is increasingly disengaged.And while organizations fail to provide clear pathways for employees in an AI-driven environment, internal mobility weakens, increasing reliance on external hiring and further eroding trust.

In an AI-driven economy, workforce transformation is business transformation. This reinforces a broader shift toward human-centric AI strategies. Aligning people and technology is essential to turning AI readiness into real organizational progress. At its core, the question is how leaders can build organizations that keep adapting as work itself keeps changing. Our call to action is clear: Adopt a human-centric strategy that prioritizes skills investment and enables internal mobility at scale.

Examples from leading companies show how this can work in practice. In China, JD.com has emphasized employment stability, prioritizing internal redeployment and reskilling over lay-offs even under pressure, and has helped blue-collar workers upskill in robotics maintenance and smart warehouse operations. Globally, as a streaming service company facing AI disruption, Tubi enables employees to transition across roles and even relocate internationally with immigration support. The company also encourages employees to build internal AI agents to optimize workflows, with token usage even reflected in performance metrics. These highlight that the ability to reskill and redeploy talent at scale is rapidly becoming a defining capability for organizations navigating AI transformation.

The companies that do this well will create a stronger psychological contract with their people. They will be able to make a clear commitment that as work changes, employees are not left to navigate the future alone; they have visibility into where the business is going, what capabilities matter, and how they can grow with it.

And that is exactly what turns AI from a source of anxiety into a source of opportunity. The next great hire may already be inside the organization. The real test is whether leaders have built the system to find them, develop them and give them a reason to stay.