Corporate Operating Model
Complete enterprise operating model with governance structure, steering committees, board oversight, organisational charts, and reporting lines.
Governance Structure
The Corporate Operating Model establishes a multi-layered governance structure for AI oversight, balancing strategic direction, operational execution, and independent assurance. This structure ensures AI initiatives align with corporate strategy, regulatory requirements, and ethical commitments.
Three Lines of Defence Model
| Line | Function | Key Activities | Reporting |
|---|---|---|---|
| First Line | Business & Operations | Own AI risks, implement controls, daily compliance | Business Unit Leader → Executive |
| Second Line | Risk, Compliance, Legal | Set standards, monitor compliance, advise | CRO / Chief Legal Officer → Board Risk Committee |
| Third Line | Internal Audit | Independent assurance, control effectiveness testing | Head of Internal Audit → Audit Committee |
AI Governance Hierarchy
- Board of Directors — Ultimate accountability for AI strategy and risk appetite. Receives quarterly AI governance reports.
- Board Risk Committee — Oversees AI risk framework, approves risk appetite statements, reviews major incidents.
- AI Ethics Board — Independent body reviewing high-risk AI use cases, bias assessments, and ethical appeals.
- AI Steering Committee — Executive body chaired by CTO/CIO with cross-functional membership. Meets fortnightly.
- AI Centre of Excellence — Central team providing standards, tooling, training, and expert support to product teams.
- Product AI Teams — Embedded teams responsible for AI system development, operation, and compliance in their domains.
Independence of AI Ethics Board
The AI Ethics Board must include at least 50% external or independent members with no reporting line to business unit leadership. Board members serve staggered 2-year terms.
AI Steering Committee
The AI Steering Committee is the primary executive body for AI governance, responsible for directing AI strategy, approving high-risk projects, resolving cross-functional issues, and monitoring the AI governance programme.
Committee Composition
| Role | Responsibility | Attendance |
|---|---|---|
| Chair | CTO or CIO | Mandatory |
| Permanent Members | CRO, Chief Legal Officer, CISO, Chief Data Officer, Head of AI Ethics | Mandatory |
| Rotating Members | Product VP, HR Director, Procurement Lead, Customer Success Lead | As required by agenda |
| Secretary | AI Governance Manager | Mandatory (non-voting) |
Decision Authority Matrix
| Decision Type | Authority | Escalation Path |
|---|---|---|
| AI Strategy & Budget | AI Steering Committee | Board of Directors |
| High-Risk AI Project Approval | AI Steering Committee (unanimous) | Board Risk Committee |
| Medium-Risk AI Project Approval | AI Steering Committee (majority) | AI Steering Committee (unanimous) |
| Low-Risk AI Project Approval | AI Centre of Excellence Lead | AI Steering Committee |
| AI Policy Changes | AI Steering Committee | Board Risk Committee |
| Ethics Appeals | AI Ethics Board | Board of Directors |
Organisational Structure & Reporting Lines
The following organisational structure depicts the formal reporting lines, dotted-line relationships, and functional alignment for AI governance across the enterprise.
Executive Reporting Structure
- CEO → Board of Directors (quarterly)
- CTO/CIO → CEO (monthly operational, quarterly strategic)
- CRO → CEO (monthly risk dashboard)
- Chief Legal Officer → CEO (as required, quarterly compliance summary)
- CISO → CTO/CIO (weekly security operations, monthly strategic)
- Chief Data Officer → CTO/CIO (monthly data governance report)
- Head of Internal Audit → Audit Committee (quarterly assurance report)
AI Centre of Excellence Structure
| Function | Lead Role | Team Size | Key Deliverables |
|---|---|---|---|
| AI Governance | AI Governance Manager | 2-3 | Policy, standards, compliance monitoring, reporting |
| ML Engineering | Principal ML Engineer | 4-8 | Model development, MLOps, validation frameworks |
| AI Security | AI Security Lead | 2-4 | Threat modelling, adversarial testing, security reviews |
| AI Ethics & Bias | AI Ethics Officer | 1-2 | Ethics assessments, bias audits, training programmes |
| AI Operations | AI Operations Manager | 3-5 | Monitoring, incident response, capacity planning |
| Data Engineering | Principal Data Engineer | 3-6 | Data pipelines, quality frameworks, lineage tools |
Scalability Guidance
For organisations with fewer than 500 employees, the AI Centre of Excellence may be consolidated into a 3-person team (Governance, Engineering, Operations). For enterprises exceeding 10,000 employees, each business unit should establish a dedicated AI liaison reporting to the central CoE.