Forrester: Half of AI-Driven Layoffs to Be Reversed at Lower Pay

TL;DR: Forrester Research’s “Predictions 2026: The Future Of Work” report forecasts that approximately 50% of AI-attributed layoffs will be reversed through quiet rehiring at reduced compensation or offshore positions. The research reveals 55% of employers already regret laying off workers due to AI, with more investment leaders expecting headcount increases (57%) than decreases (15%) over the next year.

Research Findings

Forrester’s analysis suggests many organisations made premature workforce reductions based on anticipated AI capabilities rather than proven performance:

  • Layoff Regret: 55% of employers now regret AI-attributed workforce reductions
  • Hiring Outlook: 57% of AI investment leaders expect headcount increases vs 15% anticipating decreases
  • Rehiring Pattern: Approximately half of laid-off workers will be quietly rehired at lower compensation or through offshore arrangements

The report indicates companies eliminated positions based on AI’s theoretical promise whilst the technology remained incapable of fulfilling anticipated roles.

HR Function at Risk

The research identifies human resources functions as particularly vulnerable to aggressive AI-driven staffing cuts:

  • Potential staffing reductions of 50% in HR departments
  • Expectations to maintain service levels despite reduced headcount
  • Increasing reliance on AI tools for recruitment, performance management, and employee services

This projection raises questions about organisations’ capacity to manage complex workforce issues—including AI-related restructuring itself—with significantly reduced HR capabilities.

Market Evidence

Several high-profile cases support Forrester’s predictions:

Klarna: Initially announced aggressive AI replacement strategy but subsequently revised plans after quality concerns emerged

Duolingo: Modified AI implementation approach following performance issues

Salesforce: Cut 4,000 customer support positions

Amazon: Recently announced elimination of 14,000 corporate positions, partially attributed to generative AI adoption

The pattern suggests organisations are making workforce decisions ahead of AI capability validation.

”AI-Washing” Concerns

The report warns that many organisations rely on “vendors’ AI-washed product offerings” rather than genuinely effective AI technology. This creates a scenario where companies:

  1. Reduce workforce based on vendor AI claims
  2. Discover actual capabilities fall short of marketing promises
  3. Quietly rehire to address performance gaps
  4. Negotiate lower compensation with returning workers who have reduced bargaining power

Strategic Implications for UK Businesses

Forrester’s predictions reveal several workforce planning considerations:

  1. Capability Validation: Before making AI-driven workforce reductions, organisations should pilot AI systems in production conditions to verify claimed capabilities match actual performance

  2. Retention Cost Analysis: The research suggests rehiring costs (recruitment, onboarding, knowledge loss during gaps) may exceed the savings from AI adoption, particularly if workers return at lower compensation but with reduced morale and commitment

  3. Legal and Reputational Risk: UK employment law implications of mass redundancies followed by rehiring at lower pay merit legal review. Workforce trust damage from this pattern may impact future recruitment and retention

  4. HR Capability Preservation: With HR functions identified as particularly vulnerable, organisations should carefully assess which HR capabilities require human judgment (complex investigations, strategic workforce planning, employee relations) before pursuing 50% staffing cuts

  5. Vendor Scrutiny: Given warnings about “AI-washed product offerings,” UK businesses should demand proof of concept results and reference customers before committing to workforce reductions based on AI vendor claims

The research suggests that organisations pursuing aggressive AI-driven workforce reductions risk creating expensive, demoralising rehiring cycles whilst damaging employer brand and employee trust. A measured, evidence-based approach to AI adoption appears more prudent than speculative workforce cuts.

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