AI Governance & Operating Model Transformation
Designing a governed route from AI opportunity discovery through assessment, decision making and controlled implementation.
The Client Challenge
AI opportunities were emerging across multiple business functions, but there was no consistent organisational route for determining which opportunities should progress, how they should be assessed, who had authority to make decisions, what controls were required, or how approved initiatives should move into implementation.
The challenge was therefore broader than AI policy or governance oversight. The organisation needed an operating model connecting business need, AI suitability, risk, decision making, governance and delivery.
What We Found
The presenting requirement was to govern AI. The diagnosis showed that the underlying problem was how AI initiatives progressed through the organisation.
Business Problem Before AI
AI should be considered in response to a defined business need, rather than treating AI adoption itself as the objective.
Governance Needed to Control Progression
Governance needed to influence when and how initiatives progressed, rather than operating primarily as retrospective oversight.
Approval Was Not Implementation Readiness
Approval to proceed did not establish the controls, evidence, validation and delivery conditions required for implementation.
One Connected Route from Business Need to Assurance
MABY designed an end to end operating model connecting AI opportunity discovery, assessment and governance with implementation and assurance.
Discover & Define
Business need, opportunity and requirements.
Assess
AI suitability, feasibility, risk and controls.
Govern & Decide
Decision rights, human oversight and approval.
Prepare
Implementation readiness and governed baseline.
Implement
Controlled delivery, change and quality management.
Validate & Assure
Evidence, acceptance and release readiness.
AI Governance & Operating Model
Defines how opportunities are identified, assessed, governed and approved before entering delivery.
- Opportunity discovery
- Problem definition and requirements
- AI suitability assessment
- Risk and controls
- Decision rights
- Human oversight
- Governance gates
- Implementation readiness
Governed Delivery Blueprint
Translates approved initiatives into controlled implementation, validation and release.
- Requirements traceability
- Architecture decisions
- Delivery governance
- Change control
- Implementation controls
- Quality and validation
- Testing and acceptance
- Release readiness
Key Design Decisions
The model was shaped around the organisational problems that needed to be solved, rather than starting from a predefined technology or governance framework.
Business Need Before Technology
Problem definition and requirements precede AI suitability, ensuring technology selection remains grounded in a genuine organisational need.
Governance Controls Progression
Decisions, evidence and authority are embedded into the lifecycle rather than being applied retrospectively after consequential decisions have already been made.
Human Accountability Remains Explicit
AI can assist and software can enforce controls, but consequential organisational decisions remain with accountable people.
Designed for Organisational Reuse
Approved governance and delivery structures can be reused and adapted by future initiatives rather than recreated project by project.
From Design to Implementation
The operating model was translated into practical governance, delivery and assurance structures that could support real implementation rather than remaining a conceptual framework.
From Fragmented AI Activity to Repeatable Organisational Capability
Before
After
It was a repeatable organisational capability for moving AI opportunities from business need through controlled implementation and assurance.
What MABY Established
The engagement created connected organisational capability across operating model design, governance, controlled delivery and scale.
Operating Model
- End to end AI lifecycle
- AI suitability assessment
- Implementation readiness
- Connected governance and delivery model
Governance
- Decision rights
- Governance gates
- Human oversight
- Evidence requirements
Delivery Control
- Requirements traceability
- Change control
- Validation
- Release readiness
Organisational Scale
- Reusable governance baseline
- Reusable delivery blueprint
- Repeatable project bootstrap
- Future initiative adoption
Have an AI Transformation Challenge to Solve?
Talk to us about the business problem, where governance or delivery is breaking down, and what needs to be established to move AI initiatives into controlled implementation.
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