Taking Stock
Map what is actually happening before trying to govern it.
Online book
90 Days to Responsible AI Governance
A leadership playbook for building accountable AI systems, told through a practical 90-day governance challenge.
The 90-Day Structure
The book follows a newly appointed Head of Responsible AI through three clear stages: understand the terrain, diagnose the gaps, and design governance that can last.
Diagnosing Gaps
Find where risk, ownership, and accountability break down.
Designing Governance
Build a credible structure that leaders can support and teams can use.
Chapter Outline
The book is divided into three original sections, each covering one month of the 90-day governance challenge.
Section I - Month 1
Taking Stock
You cannot govern what you cannot name. The opening section maps the terrain before trying to change it.
Chapter 1
The Illusion of Control
The new Responsible AI lead enters an organisation that believes AI is already under control.
Focuses on fragmented ownership, reassuring board narratives, compliance theatre, and the gap between policy and operational reality.
Chapter 2
Speaking the Language of AI
Leaders reset the vocabulary needed to make sound governance decisions.
Clarifies AI versus automation, model versus system, provider versus deployer, and why shared language prevents false confidence.
Chapter 3
Why Responsible AI Is Hard
The organisation confronts why principles often fail to become practice.
Covers framework overload, legacy processes, ethics statements without structural change, and the difficulty of turning values into controls.
Chapter 4
The Listening Tour
The protagonist maps AI use across teams, systems, vendors, and decision points.
Introduces a practical AI system mapping workshop and a first view of hidden dependencies across the business.
Feature
Tools in Month 1
- AI System Mapping Workshop
- Executive Vocabulary Reset
- Framework Orientation Map
Section II - Month 2
Diagnosing AI Challenges
Governance fails where accountability is unclear. This section diagnoses risk, ownership, and structural gaps.
Chapter 5
Where Risk Actually Lives
Risk is traced through workflows, procurement, monitoring gaps, and daily operations.
Moves attention away from the model alone and toward the organisational settings where AI decisions create impact.
Chapter 6
The Accountability Gap
The team asks who is answerable when an AI-enabled decision goes wrong.
Explores diffused responsibility, human-in-the-loop myths, unclear escalation routes, and weak sign-off authority.
Chapter 7
Governance Illusions
The organisation learns that policy, registries, and committees are not governance by themselves.
Separates documentation from oversight and shows where governance needs authority, cadence, and consequences.
Chapter 8
From Principles to Practice
Responsible AI values are translated into concrete business processes.
Uses the model value to decision point to process control, helping readers turn abstract commitments into operational changes.
Feature
Tools in Month 2
- Accountability Mapping Session
- Risk Tiering Workshop
- Values-to-Process Workshop
- Values-to-Process Matrix
Section III - Month 3
Designing the Governance Structure
Responsible AI must become structural. The final section turns diagnosis into governance design, controls, monitoring, and board strategy.
Chapter 9
The Governance Architecture
The protagonist designs the layers, roles, cadence, and escalation paths of the governance model.
Defines the relationship between board oversight, executive ownership, risk review, product teams, and operational monitoring.
Chapter 10
Practical Controls
The governance model becomes a set of review, vendor, monitoring, and sign-off controls.
Introduces system review templates, vendor due diligence, deployment thresholds, and exit criteria.
Chapter 11
Sustaining Responsible AI
The organisation prepares for monitoring, model drift, incident review, and regulatory change.
Focuses on lifecycle governance, review cadence, incident learning, and preventing uncontrolled AI sprawl.
Chapter 12
Day 90: Presenting to the Board
The final chapter turns the 90-day journey into a credible governance strategy.
Ends with a board-ready roadmap, accountability map, governance structure, and 12-month implementation plan.
Feature
Tools in Month 3
- Responsible AI Governance Blueprint
- Responsible AI System Review Template
- Vendor Due Diligence Framework
- Post-Deployment Monitoring Dashboard
Tools and Templates
The book includes a small practical toolkit that readers can adapt inside their own organisations.
AI System Mapping Workshop
Identifies systems, owners, decision points, and vendor dependencies.
Executive Vocabulary Reset
Creates shared language for AI governance conversations.
Accountability Mapping Session
Clarifies who is accountable, responsible, consulted, and informed.
Risk Tiering Workshop
Classifies AI systems by impact, automation depth, and exposure.
Responsible AI Governance Blueprint
Defines roles, reporting cadence, escalation, and review thresholds.
Post-Deployment Monitoring Dashboard
Tracks incidents, drift, complaints, ownership, and review cadence.