At Davos 2026, IMF Managing Director Kristalina Georgieva warned AI could hit the labor market like a “tsunami,” citing estimates that 60% of jobs in advanced economies and 40% globally could be affected—enhanced, transformed, or eliminated.

The most operationally useful insight is distribution: impacts aren’t uniform. Entry-level and routine cognitive tasks are more exposed, while roles that combine domain knowledge, judgment, and human interaction often shift toward “AI-assisted.” That tends to reward workers who can supervise, validate, and integrate AI outputs—creating a wage premium for “AI-complementary” roles.

For employers, the near-term risk is mismanagement of transition. If firms treat AI as a blunt headcount lever, they may weaken pipelines for talent development. Entry-level roles are where institutional knowledge is built. Removing them can create future gaps in leadership and specialized expertise.

A better approach is job redesign:

• convert some junior tasks into supervised AI workflows
  
• increase the ratio of coaching and review work
  
• invest in training that teaches employees how to verify AI output quality
  
• define responsibility boundaries clearly to avoid accountability ambiguity
  

The bottom line: AI is likely to be a productivity shock—but the organizations that benefit most are those that treat it as a workforce operating model change, not just a software rollout.