Due Diligence for the AI Buildout

Due Diligence for the AI Buildout · sixteen-essay series

Due Diligence for the AI Buildout

A sixteen-essay framework for AI infrastructure due diligence. Each essay maps one workstream from scoping through post-close validation, with question banks, worked examples, and cross-references to the AI Power Chain vendor screen. Reference material for PE sponsors, corporate development teams, and target-side operators preparing for capital events.

16essays
Aug 18 → Sept 4 2026publishing window
Question banks + workbooksreference material

01The essays

  1. 01
    The scoping decision
    What DD covers before the data room opens
  2. 02
    Team, timeline, and the anatomy of a data room
    Five internal DD roles, sequencing, and reading the seller's room
  3. 03
    Market and demand-side DD
    Testing whether demand is what the CIM says it is. Bottom-up sizing
  4. 04
    Customer, pricing, and competitive DD
    What the target captures from the demand base. Concentration + pricing power
  5. 05
    Product architecture and technology DD
    Product-spec fit, roadmap evidence tiers, differentiation audit
  6. 06
    Manufacturing, IP, and supply chain DD
    Capacity vs demand, yield, IP audit, tier 1/2 supply chain risk
  7. 07
    Quality of earnings and working capital DD
    Add-back discipline, dynamic working capital, QoE walk to normalised EBITDA
  8. 08
    Capex, growth economics, projection stress-testing
    Capex per revenue $, unit economics, three downside scenarios
  9. 09
    Organisational, key personnel, culture, systems DD
    Whether people + culture + systems can execute the DD thesis
  10. 10
    Legal and contract DD
    Corporate structure, change-of-control, non-competes, IP, litigation
  11. 11
    Regulatory, CFIUS, environmental, cyber DD
    Approvals that gate closing, liabilities that follow, cyber that walks the R&W
  12. 12
    Deal structure, R&W, escrow architecture
    How DD findings translate into the transaction paper
  13. 13
    Financing structure, covenants, closing risk
    How the deal gets paid for; covenants; what stops closing after signing
  14. 14
    Post-close validation + the DD improvement loop
    100-day validation, six-month scorecard, feeding lessons back into DD
  15. 15
    The Question Banks
    250+ questions organised by workstream + AI Power Chain layer
  16. 16
    Seller-side prep: the DD workbook
    The framework inverted for target-side founders + CEOs + sell-side teams

The AI Power Chain vendor screen

Named vendors across every layer, scored on moat, execution risk, and chokepoint. Cross-referenced from every essay in this series.

Vendor screen →
Also see: Case Studies for how the framework applies to specific transactions, Financing the AI Buildout for capital-structure essays, and Tech Spotlights for vendor + technology deep-dives.
FrameworkThe Due Diligence framework, canonical definition of the 14 workstreams organized across four stages, with two companion reference assets.