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1. Executive Summary

Purpose

Executive-level overview of the AI Project Blueprint: why AI projects fail and how this methodology prevents that.

1. What is this Blueprint?

A large proportion of AI projects never reach production — estimates range from 30% to over 80%, depending on organisational maturity [so-51]. Not through technical failure, but through missing governance, vague objectives and uncontrollable models. The AI Project Blueprint is built to prevent exactly that: a modular methodology (from idea to management) that approaches AI as behavioural steering — managing not only code, but also Objective Definition, Hard Boundaries, System Prompts and Evidence.

The Blueprint applies to both AI systems that support (such as advice, analysis or content generation) and systems that independently execute tasks within pre-established frameworks. As a system gains more autonomy, additional requirements apply for documentation, oversight and evidence, so that human ownership, controllability and accountability are maintained.

2. What questions does this Blueprint answer?

Question Answer in the Blueprint
How do I manage an AI project from idea to production? The AI Project Cycle with 5 phases, gates and standard deliverables
How do I define and validate an AI business case? Validation Pilot + Business Case template + Value Realisation
How do I build responsible AI-driven software? Specification-First Pattern + Hard Boundaries + Evidence Standards
How do I organise governance and compliance? Governance Model + Compliance Hub + EU AI Act
How do I work with agentic AI systems? Collaboration Modes + Agentic AI Engineering
How do I scale AI across my organisation? Three Tracks + 90-Day Roadmap + Organisation Profiles

3. Who is this for?

  • Board & MT: making choices, managing risks, justifying investment
  • Product & Business owners: selecting use cases, delivering value, ensuring adoption
  • IT/Engineering: building, testing, integrating, setting up operational management
  • Compliance/Legal/Privacy: making EU AI Act + GDPR verifiable, working audit-ready

4. What does this concretely deliver?

  1. Faster time-to-value via standard templates and gates
  2. Fewer incidents via Hard Boundaries + safety tests + incident process
  3. Audit-ready dossier (evidence package) for internal/external review
  4. Repeatability: every use case follows the same lifecycle and standard deliverables

5. How do you use the Blueprint (quick start)?

If you start today with 1 use case:

  1. Complete the Project Charter (1 A4).
  2. Do the Risk Pre-Scan and determine risk level.
  3. Create the Objective Card (incl. Hard Boundaries).
  4. Set up a Golden Set and test with the Golden Set Test.
  5. Record results in the Validation Report.
  6. Decide at Gate whether to proceed to Realisation/Go-live.
  • Week 1–2: choose 1 pilot use case + appoint core roles (AI PM, Tech Lead, Guardian).
  • Week 3–6: execute lifecycle (Modules 02–04), including Evidence Standards.
  • Week 7–8: go-live + management (Modules 05–06).
  • Week 9: evaluation + update Blueprint to v1.1 based on learnings.

7. Navigation (what should you read?)

  • Start: Reader's Guide & Executive Summary
  • Process: Discovery & Strategy through Monitoring & Optimisation
  • Governance: Compliance Hub + Evidence Standards
  • Templates: Toolkit & Templates (Project Charter through Validation Report)