AI is becoming a mainstream feature of work. In 2023, McKinsey research found only 30 percent of employees reported using AI at work. By 2025, 76 percent reported using AI in some capacity. Beyond copilots and new tools, AI is changing the content of work—how we complete tasks, make decisions, and measure our effectiveness.
With such rapid change in how work gets done, it would be easy to assume that what employees value is changing just as quickly. Four years of research points to a more grounded conclusion: work is transforming, but what employees fundamentally value remains strikingly consistent.
Early careers: Fewer roles, lower mobility, but steady priorities
The earliest signals of change are emerging among early-career employees. Research points to shifts in entry-level roles as AI automates routine tasks:
- According to a McKinsey survey from 2025 on the new era of work, 51 percent of organizations reported that generative AI was reducing their need for entry-level roles.
- Data from the U.S. Bureau of Labor Statistics (BLS) show that unemployment among college graduates aged 23-27 rose from 3.25 percent in 2019 to 4.59 percent in 2025.
- High-frequency payroll data from ADP, cited by Erik Brynjolfsson and his colleagues, reveal that early-career workers in AI-exposed fields saw a 16 percent relative decline in employment, while roles for more experienced workers remained stable.
Historically, employees in their first three years were the most likely to want to change jobs, seeking supportive environments to learn and advance, and the job market supported those transitions. Employees and employers now face a different dynamic.
Between 2023 and 2025, McKinsey found that the intent to quit fell sharply among early-tenure employees. Among those with a tenure of up to one year, it dropped from 37 percent in 2023 to 32 percent in 2025, approaching the level of employees with a tenure of three years or more (30 percent).
While fewer early-career employees intend to leave, McKinsey research finds that levels of development, leadership quality, and overall experience have not meaningfully improved. This suggests that reduced mobility may be less a function of better fit and more a reflection of a tighter labor market.
Organizations that built talent strategies assuming high early-career turnover should reassess. Mobility has slowed, but aspirations have not changed, creating an opportunity to deliberately engage, develop, and shape the next generation of leaders. Hiring class sizes and career development models may need to adapt to a workforce that may stay longer, while ensuring organizations continue to bring in and build the right capabilities.
AI proficiency: High engagement, high flight risk
An employee's AI proficiency is beginning to define their experience and opportunities as AI becomes embedded in everyday work.
In 2025, clear patterns emerged across AI user segments. AI creators and heavy users report the highest levels of engagement, energized by new tools at their disposal. Yet, paradoxically, these same employees report the highest intent to quit. AI creators and heavy users are seven percentage points more likely than light users and 10 percentage points more likely than non-users to plan on quitting their jobs in the next 3-6 months. They know their skills are in high demand and are keenly aware of their market value.
External labor-market data reinforce this. An analysis of nearly 10 million job postings conducted by Oxford Internet Institute researchers Alejandra Castañeda, Matthew Bone, and Fabian Stephany showed that roles requiring AI skills were more likely to advertise remote work, positive culture signals, and parental leave—alongside significant salary premiums. AI roles advertising parental leave paid roughly 12 percent more, while those signaling a strong culture paid about 20 percent more.
For leaders, the implication is twofold. First, organizations must raise AI fluency broadly across the workforce. Second, advanced AI talent requires deliberate engagement and retention strategies.
Employee expectations: Rebalancing without reinvention
Despite significant changes in how work is done—and who feels those changes first—the core elements of the employee value proposition have remained stable.
Employees continue to cite meaningful work, workplace flexibility, career development and advancement opportunities, reliable and supportive coworkers, and adequate rewards and recognition as primary reasons for staying. Likewise, the top reasons for leaving are consistent: inadequate rewards and recognition, uncaring and uninspiring leadership, lack of career development and advancement opportunities, lack of workplace flexibility, and unsustainable work performance expectations.
While the list itself is stable, the emphasis has shifted slightly. The importance of flexibility peaked during the transition to hybrid work and has since moderated, while concerns about leadership quality have steadily increased. Adequate rewards and recognition remain a consistently powerful factor.
This points to a rebalancing of priorities, not a total reinvention of what matters to employees.
Leadership priorities: Staying grounded while adapting
Three priorities emerge for organizations seeking to navigate AI-driven disruption without losing focus on the details that sustain performance:
- Concentrate on leadership fundamentals. With AI reshaping roles and hybrid work maturing, employees' expectations for clear, supportive leadership are rising. Investing in manager and leader effectiveness continues to be critical, particularly as organizations navigate increasing complexity and rising expectations for human-centric leadership.
- Build AI capability broadly—while being intentional about advanced users. Baseline AI fluency is becoming essential for everyone, requiring organizations to invest in broad capability building while empowering managers to drive adoption. However, the most advanced users are often the biggest flight risks, as the external market competes aggressively for their skills. Organizations should create targeted engagement and retention plans for this critical group, with an emphasis on workplace flexibility, well-being, and resource accessibility.
- Rethink early-in-career strategies. With intent to quit among early-tenure employees now approaching long-tenure levels, assuming natural churn risks missing an opportunity to build long-term capability through coaching and skill development, while foregoing entry-level hiring risks weakening the future leadership pipeline. In addition, deliberate early-career performance management and career pathing should be emphasized.
The organizations best positioned to attract, develop, and retain top talent in this new era will be those that remain grounded in the fundamentals of a strong employee experience. In a period of rapid technological change, staying steady on what truly motivates people may prove to be a competitive advantage that lasts.
The authors wish to thank Yueyang Chen and Marino Mugayar-Baldocchi for their contributions to this blog post.
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This blog post is part of a People and Organization Blog series that explores how organizations will be transformed by agentic AI. Follow us on LinkedIn and keep an eye on the blog for our latest insights and how these technologies will shape organizations today and tomorrow.