The toolkit
Use the complete toolkit — or start with the problem in front of you.
The 16 tools follow the lifecycle of an enterprise AI initiative, from initial idea through business-case development, architecture, governance, deployment, adoption, value realization, and enterprise scale. Each tool can be used independently. Together, they create an integrated method for managing AI across the enterprise.
16 practical tools · 7 enterprise AI pillars · 5 roadmap phases · One integrated operating framework
Group 1
Decide What Is Worth Pursuing
Separate promising opportunities from expensive distractions.
Chapter 1 · Phase 1
AI Project Reality Check
Screen an AI idea for the most common causes of failure before committing significant time or budget.
Screen a proposed AI initiative for the most common causes of failure before you commit budget.
Check an AI Project →Chapter 2 · Phase 1
AI Business Case Definition Tool
Turn an early idea into a structured, executive-ready business case before making a technology decision.
Define the business problem, stakeholders, and expected value before any technology decision is made.
You get: A shareable one-page Business Case Brief.
Build a Business Case →Chapter 3 · Phase 1
AI Opportunity & Data Readiness Scorer
Determine whether the initiative is a Quick Win, a Foundational Investment, a Capability Transformation, or a Strategic Bet.
Score an opportunity on value and readiness, and grade the data quality it depends on.
Score an Opportunity →Chapter 13 · Phase 3
AI Business Case Scorecard
A weighted scorecard that recommends one of seven paths: proceed to pilot, conduct discovery, build the foundation, redesign the process, use a simpler solution, monitor for later, or stop.
Applies the 8-part case-for-action test and recommends one of 7 concrete next steps, including 'Stop.'
Test the Case for Action →Group 2
Redesign the Work
Do not use AI to make a broken process run faster.
Chapter 6 · Phase 2
Process Redesign Readiness Survey
Assess a business process using the ESSIA framework — Eliminate, Simplify, Standardize, Integrate, Automate — and find the earliest unresolved stage.
Find out whether a process is ready for AI-enabled automation, or needs simplification first.
You get: A process-readiness ladder and prioritized redesign checklist.
Assess a Business Process →Chapter 7 · Phase 2
AI Solution Requirements Builder
Choose the appropriate autonomy level, then build requirements across 12 categories including business, process, functional, AI behavior, data, integrations, security, human oversight, evaluation, and operations.
Choose the right autonomy level and build a complete requirements set.
You get: A structured, exportable Requirements Specification.
Build Solution Requirements →Group 3
Design the Technical Foundation
The model is only one layer of an enterprise AI solution.
Chapter 8 · Phase 2
Enterprise AI Architecture Maturity Assessment
Examine the complete environment surrounding the model, not just the model itself.
Score your maturity across all 10 layers of the AI architecture stack.
You get: An architecture maturity profile showing missing, immature, and established layers.
Assess Your AI Architecture →Chapter 9 · Phase 2
Build vs. Buy AI Decision Tool
Compare the three primary sourcing paths against functional fit, differentiation, integration, data control, security, configurability, vendor dependency, implementation effort, operating cost, and long-term flexibility.
Compare sourcing options and get a recommended path with rationale.
You get: A recommended sourcing path with supporting rationale.
Compare Your Options →Group 4
Establish Governance and Accountability
Responsible AI requires more than a policy.
Chapter 10 · Phase 3
AI Governance Maturity Assessment
Assess governance from intake and evaluation through deployment, monitoring, review, and retirement — and check whether rigor increases as autonomy and business impact increase.
Evaluate whether your AI governance program covers the full lifecycle.
Assess AI Governance →Chapter 11 · Phase 3
AI Accountability & RACI Builder
Build a use-case-specific accountability matrix covering business outcomes, data, technology, model behavior, human oversight, security, compliance, monitoring, incidents, change management, value realization, and retirement.
Builds a complete accountability map for a specific AI use case across 12 dimensions.
You get: A shareable RACI-style accountability matrix.
Build an Accountability Matrix →Chapter 12 · Phase 3
AI Operating Model Diagnostic
Evaluate your current operating model against the failure patterns that stall enterprise AI programs.
Checks your AI operating model against 7 named anti-patterns and the central-vs-business-unit split.
You get: A recommended division of responsibilities across the AI use-case lifecycle.
Diagnose Your Operating Model →Group 5
Move Safely Into Production
A successful demonstration is not a production-ready system.
Group 6
Prove Value and Build Adoption
Adoption and value do not appear automatically after launch.
Chapter 15 · Phase 4
AI Value Realization Calculator
Guide teams through three stages — Estimate, Validate, Realize — connecting baseline performance, target outcomes, AI contribution, implementation and operating costs, value-capture mechanisms, and actual production results.
Move an AI initiative from estimated ROI to proven, realized value.
You get: A value case showing baseline, target, actual performance, total cost, net value, and current evidence status.
Build a Value Case →Chapter 16 · Phase 4
AI Change & Adoption Readiness Survey
Use leadership and employee modes to identify gaps between executive confidence and frontline experience.
Pulse-check trust and readiness across the 12-part change management framework.
Assess Change Readiness →Group 7
Scale the Enterprise Capability
You cannot scale AI by rebuilding the foundation for every use case.
Chapter 17 · Phase 5
AI Platform Investment & Scaling Assessment
Evaluate shared platform maturity, how AI investment is funded, and scale across users, transactions, functions, business units, autonomy, and strategic importance.
Check whether you have the shared platform services and funding model needed to scale AI.
You get: A recommended platform-investment priority.
Assess Platform Maturity →Capstone · Phase 5
Enterprise AI Blueprint Maturity Assessment
Evaluate your organization across all seven pillars, identify the capabilities limiting progress, and receive a recommended roadmap for building a sustainable enterprise AI capability.
The definitive, book-spanning diagnostic across all 7 pillars of enterprise AI maturity.
You get: An overall maturity score, a seven-pillar profile, a recommended roadmap phase, and a prioritized action list.
Start the Flagship Assessment →