Chapter 12 · Group 4: Establish Governance and Accountability
Divide responsibility between the centre and the business units.
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. This tool applies the framework from Chapter 12 of The Enterprise AI Blueprint by W. Perry Underdown and returns a directional, structured read — not an audit finding.
Approximately 12 minutes · Results saved to your workspace · Free to start
Common failure patterns tested
- Centralized bottlenecks
- Uncontrolled decentralization
- Innovation theater
- Pilot proliferation
- Technology-led prioritization
- Governance after deployment
- Unowned production systems
Output: A recommended division of responsibilities across the AI use-case lifecycle.
What the assessment covers
Section 1
Part A — Anti-Pattern Check
Section 2
Part B — Responsibility Split
Section 3
Part C — Lifecycle Coverage
Continue the journey
Other tools in Establish Governance and Accountability
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.
Assess AI Governance →
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.
Build an Accountability Matrix →
Create your workspace and start AI Operating Model Diagnostic.
Your answers, scores, and reports stay in one workspace so you and your team can track progress across all 16 tools.