AI & Automation · AI Transformation · Hard · 35-45 min

Redesigning the Workforce Around AI

Redesigning the Workforce Around AI is a hard AI & Automation ai transformation case interview that runs 35-45 min. A 12,000-person services company believes AI can automate or augment large parts of its knowledge work. A strong answer works through 5 phases: Move from 'jobs' to 'tasks'; Quantify the productivity opportunity and where headcount vs capacity actually changes; Design the operating model; Plan the change; Recommend a phased approach that captures value while protecting capability and trust.

Last updated 2026-09-05

The brief

A 12,000-person services company believes AI can automate or augment large parts of its knowledge work. The CEO wants a workforce strategy: where AI replaces tasks, where it augments people, what new roles emerge, and how to manage the change without gutting morale or capability. The board wants productivity gains; the CHRO is worried about a talent exodus and union exposure.

How to approach it

  1. Move from 'jobs' to 'tasks' — decompose roles into tasks and assess each for automate / augment / unchanged
  2. Quantify the productivity opportunity and where headcount vs capacity actually changes
  3. Design the operating model — new roles (AI supervision, prompt/workflow design), reskilling paths, governance
  4. Plan the change — communication, reskilling vs redundancy, union/legal exposure, retention of key talent
  5. Recommend a phased approach that captures value while protecting capability and trust

What a strong answer does

  • Analyzes at the task level rather than declaring whole jobs gone
  • Distinguishes augmentation (capacity uplift) from replacement (headcount reduction) and is honest about the mix
  • Treats change management, reskilling, and trust as core to value capture, not an afterthought
  • Names the new roles AI creates and the governance needed
  • Phases the rollout to learn and protect against capability loss

Red flags interviewers score down

  • Equates AI adoption with immediate mass layoffs
  • Ignores reskilling, morale, union, and legal exposure
  • Assumes productivity gains drop straight to the bottom line with no adoption friction
  • No governance for how AI-augmented work is supervised

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