EY · Manufacturing / Operations · Intermediate · 25-35 min

Build an AI implementation roadmap for manufacturing supply chain

Build an AI implementation roadmap for manufacturing supply chain is an intermediate EY manufacturing / operations case interview that runs 25-35 min. Sequence AI initiatives by impact and feasibility, align with data and infrastructure investments, and identify early wins to fund later phases. A strong answer works through 5 phases: Use case prioritization matrix; Data readiness assessment; Capability building plan; Technology and infrastructure investment; Expected business impact by phase.

Last updated 2026-09-05

The brief

A large manufacturing company wants to use AI to optimize supply chain operations—demand forecasting, inventory management, and logistics routing. They have fragmented data systems and limited AI capabilities. Build a 3-year implementation roadmap.

How to approach it

  1. Use case prioritization matrix
  2. Data readiness assessment
  3. Capability building plan
  4. Technology and infrastructure investment
  5. Expected business impact by phase

What a strong answer does

  • Sequence AI initiatives by impact and feasibility, align with data and infrastructure investments, and identify early wins to fund later phases.
  • Start with high-impact, high-feasibility use cases (demand forecasting), consolidate data infrastructure in parallel, build internal AI talent, and scale to more complex optimization over 3 years.

Practice drills

  • Rank supply chain AI use cases by ROI and implementation effort.
  • Outline how to gather and integrate fragmented supply chain data.
  • Design a phased talent building plan (hire vs. develop vs. outsource).
  • Estimate savings from implementing demand forecasting AI.

Why this case

Tests sequencing decisions, data strategy thinking, and ability to balance quick wins with longer-term transformation.

Adapted from EY Operations & AI case (official sample).

Cases are written in each firm's style, written and reviewed by working consultants; they are not the firms' own published cases.

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