Course Objective & Scope
A major reason AI initiatives fail to scale is organisational friction: business units complain that central IT is a bottleneck, while central teams worry about business units spinning up ungoverned shadow AI tools. This course helps leaders design an enterprise AI operating model that balances speed with control.
Centralised, federated (hub-and-spoke) and decentralised archetypes, cross-functional product pods, shared platform services, funding mechanisms and RACI decision rights are explored in depth. Participants design a target AI operating model blueprint and transition plan suited to their organisation's maturity.
Who Should Attend?
- Executive team members, strategy and transformation leaders
- CIOs, CDOs, CTOs and managers responsible for IT organisation design
- HR, organisational development and agile transformation leaders
- Business unit directors and PMO managers
Key Takeaways
- Evaluate centralised, federated (hub-and-spoke) and decentralised AI operating models in the organisation's context
- Draw clear boundaries between central AI platform/CoE teams and embedded business-unit roles
- Define the end-to-end AI delivery workflow and RACI matrix from intake to production monitoring
- Design tiered self-service guardrails that curb shadow AI while empowering business teams
- Prepare a phased transition plan from the current setup to the target AI operating model
Curriculum
AI Operating Model Archetypes: Centralised, Federated and Decentralised
- Comparing centralised, decentralised and hub-and-spoke structures
- Selecting the right archetype based on company size, regulatory intensity and AI maturity
- How the operating model evolves as organisational maturity grows
Organisational Layers: Platform, CoE and Business Pods
- Role of the AI Platform team providing infrastructure, model gateways and security tooling
- The Hub / CoE setting standards, reusable assets and coaching
- Cross-functional business-unit pods (Spokes) turning domain knowledge into value
End-to-End Delivery Workflow and Decision Rights (RACI)
- Intake, triage, PoC, security/ethics review, production release and lifecycle management
- Fast-track vs. full-governance lanes based on risk tier (internal assistant vs. external agent)
- RACI matrix across business sponsor, product owner, AI engineer, CISO and compliance
Funding Mechanisms, Metrics and Shared Service Catalogue
- Balancing central seed funding with business-unit co-funding
- Internal service catalogues and chargeback rules that reward asset reuse
- Velocity, quality and adoption metrics that measure operating-model health
Target Operating Model Design Workshop
- Diagnosing current friction points and decision bottlenecks
- Sketching the tailored organisation chart, interaction modes and governance bodies
- Defining the first six-month transition steps and communication plan
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