Governance Fails When It’s Only Documentation
Governed AI & automation isn’t only a design problem—it’s an operating problem. Most failures happen when teams:
- don’t share the same risk appetite and decision rights
- build without consistent controls, logging, and evidence expectations
- review inconsistently (or too late), creating governance debt
This programme makes governance usable across leadership, builders, and reviewers—so delivery can move fast without creating audit risk.
Practical Standards Teams Can Actually Use
Participants leave with reusable, review-ready assets (tailored to your tooling where applicable):
- control-by-design patterns (approvals, traceability, exception handling)
- builder checklists (what evidence to capture, where, and why)
- reviewer checklists (sampling, testing, evidence expectations)
- steering templates (decisions, exceptions, escalation paths)
- simulation packs (incident drills, remediation actions)
Role-Based by Design
One System, Four Perspectives
Executive & Leadership (EX)
Set risk appetite, define decision rights, and create a steering rhythm that holds as adoption scales.
Outcomes:
- clear governance ownership and decision mechanics
- prioritised roadmap with what’s allowed / needs review / not allowed
- a steering cadence that teams can sustain
Common Formats:
- executive briefing (2–3 hrs)
- steering committee working session (½ day)
Builder & Practitioner (BU)
Build review-ready solutions by default—controls, logging, and evidence designed in from day one.
Outcomes:
- reusable control patterns (approvals, traceability, exceptions)
- consistent evidence capture (audit-ready by design)
- safer GenAI/coplay adoption practices (data handling + prompt governance)
Common Formats:
- foundations workshop (1 day)
- design labs (½ day blocks)
- platform clinics (Power Platform + Copilot, UiPath, ServiceNow—tool-aligned)
GRC & Audit (GR)
Review AI and automation consistently—testing, sampling, and evidence expectations that are defensible and practical.
Outcomes:
- repeatable review approach and sampling checklist
- consistent evidence expectations across domains/tools
- readiness for investigations: “what changed, who approved, what was the impact?”
Common formats
-
review playbook workshop (½–1 day)
-
audit simulation lab (1 day)
Joint Workshops (JT)
Align stakeholders and practise incidents before they happen.
Outcomes:
- one shared framework (roles, gates, escalation paths)
- a tested incident playbook with improvement actions
- faster alignment between build reality and review expectations
Common Formats:
- framework co-design (1 day)
- incident simulation (½–1 day)
A Practical Catalogue You Can Mix and Match
EX Courses
EX-101 Governed AI & Automation for Leaders (2–3 hrs): Technology, risk, and governance basics for boards and ExCo.
EX-201 Strategy, Risk & Roadmap (½–1 day): Prioritise domains, align risk appetite, and stress-test the governance roadmap.
EX-301 Steering Committee Deep-Dive (½ day): Roles, approvals, and oversight mechanics.
BU Courses
BU-101 Foundations of Governed Automation (1 day): Core patterns for RPA/workflows with controls, logging, and evidence.
BU-201 Designing RPA & Workflows with Controls (2–3 × ½ days): Patterns, reviews, and failure modes.
BU-202 Secure Data & GenAI Use (1–2 × ½ days): Safe Copilot/LLM adoption, data handling, and prompt governance.
BU-301/302 Solution Design Labs (Invoice-to-Pay; Onboarding & Access): Domain-specific labs with checklists and review templates.
GR Courses
GR-101 Automation & AI Risk Fundamentals (1 day): Shared vocabulary for GRC/audit teams.
GR-201 Reviewing Automated & AI-Driven Flows (1–2 × ½ days): How to test, sample, and evidence governance requirements.
GR-301 Audit Simulation Lab (1 day): From request to findings with realistic artefacts.
JT Workshops
JT-101 Framework Co-Design (1 day) & JT-201 Incident Simulation (½–1 day): Cross-functional practice with EX/BU/GR roles.