AI Readiness Audit Template
The structure and framework behind our AI Readiness Audit report. Use this to understand what a thorough AI assessment covers and how we evaluate opportunities.
Last updated: 2026-04-07
Executive Summary
A one-page overview designed to be shared with leadership without the full report. Covers the key finding, recommended action, and expected ROI at a glance.
- •Primary AI opportunity identified
- •Recommended action (go / no-go / conditional)
- •Expected ROI range (conservative to optimistic)
- •Critical risks and mitigation summary
- •Recommended next step
Opportunity Assessment
Detailed analysis of the identified opportunity — what it is, why it matters, how AI applies, and what the expected impact looks like.
- •Current workflow description and pain points
- •AI intervention point(s) identified
- •Technique assessment (classification, extraction, generation, etc.)
- •Expected accuracy and reliability range
- •Impact on operations (time, cost, quality)
ROI Model
A three-scenario financial model with transparent assumptions. Delivered as an editable spreadsheet the client can adjust with their own inputs.
- •Current cost baseline (time × rate × volume)
- •Conservative scenario — projected savings
- •Realistic scenario — projected savings
- •Optimistic scenario — projected savings
- •Implementation cost estimate
- •Payback period calculation
- •Key assumptions and sensitivity notes
Data Readiness
Assessment of data availability, quality, format, and accessibility for the recommended opportunity.
- •Data sources identified
- •Data quality assessment (completeness, accuracy, consistency)
- •Format and accessibility evaluation
- •Gaps identified and remediation effort
- •Regulatory or compliance considerations
Risk Analysis
Categorised risks with impact ratings and specific mitigation strategies. Covers technical, data, organisational, and regulatory dimensions.
- •Technical risks (complexity, accuracy, integration)
- •Data risks (quality, availability, privacy)
- •Organisational risks (adoption, change management, skills)
- •Regulatory risks (compliance, audit trail, data handling)
- •Impact rating per risk (low / medium / high)
- •Specific mitigation strategy per risk
Implementation Roadmap
A phased plan with milestones, dependencies, resource requirements, timeline, and estimated costs per phase.
- •Phase 1: Foundation (environment, data access, initial pipeline)
- •Phase 2: Core build (AI logic, integration, testing)
- •Phase 3: Production (hardening, deployment, monitoring)
- •Milestone definitions and success criteria
- •Dependencies and prerequisites
- •Resource requirements per phase
- •Estimated timeline and cost per phase
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