AI policy documents exist but are not operationalised
Teams do not know what they can and cannot do with AI in their specific role — policy without training and configured tooling produces non-compliance, not safety.
Governance & Compliance Enablement
AI Governance Framework
Operationalise your enterprise AI governance framework — MCT-led programs covering responsible AI policy design, Microsoft Purview configuration, Azure AI Content Safety, and Entra ID identity governance.
Responsible AI Policy DesignMCT-Led DeliveryMicrosoft Purview for AIAzure AI Content SafetySC-5008-A Certification Readiness
Updated for EU AI Act 2025 compliance readiness
Why This Matters Now
The challenges that bring enterprise teams to this conversation
Purview, Entra ID, and content safety are provisioned but not configured for AI
Microsoft governance tools are licensed but remain in default state — AI data governance, access controls, and content safety require deliberate configuration against specific AI workloads.
No process for reviewing AI output accuracy, bias, or regulatory compliance
Deploying AI in regulated industries without output review processes exposes the organisation to audit findings, regulatory penalties, and reputational risk.
Strategic context: Enterprise AI governance is not a policy document — it is an operating system of policies, access controls, content safety, audit trails, and team accountability working together.
Capability Coverage
What the program covers
Responsible AI Policy Design & Operationalisation
Design and operationalise responsible AI policies covering data handling, output review, bias assessment, and accountability chains for your specific industry and regulatory context.
Microsoft Purview for AI Data Governance
Configure Purview sensitivity labels, data lineage tracking, AI data scanning, and compliance controls to govern the data used in and produced by AI applications.
Azure AI Content Safety & Prompt Shield
Deploy and configure Azure AI Content Safety filters and Prompt Shield to enforce content policies and prevent prompt injection in production AI deployments.
Entra ID & Identity Governance for AI
Implement access governance for AI resources using SC-5008-A-aligned Entra ID configuration, entitlement management, and structured access review processes.
AI Audit Trail & Monitoring Design
Design logging, audit trail, and monitoring architecture for AI workloads to support compliance reporting, incident response, and continuous governance requirements.
Role-Specific AI Governance Training
Deliver governance training stratified by role — executive accountability, engineering controls, and business user policies — to operationalise the framework across the organisation.
Delivery Approach
How we deliver this
01
Assess
AI Governance Maturity Assessment
Evaluate current AI policy documentation, Purview configuration state, content safety controls, and accountability structures against governance best practice and regulatory requirements.
02
Design
Governance Framework & Operating Model
Design the AI governance framework covering policy structure, Purview configuration scope, content safety rules, access governance design, audit logging, and accountability model.
03
Enable
AI-102, AI-103, SC-5008-A + Governance Workshops
Deliver certification programs (AI-102, AI-103, SC-5008-A) alongside governance workshops that translate policy into configured Microsoft tooling and team operating practices.
04
Adopt
Live Policy with Configured Controls & Accountability
Close with operationalised AI policy, configured Purview and content safety controls, assigned accountability owners, and a governance review cadence for continuous compliance.
Capability Programs
Programs for this area
Proof & Perspectives
Implementation evidence and strategic context
Representative Healthcare Product Team
Product and engineering teams needed to evaluate AI and generative AI use cases while building implementation capability in a governed enterprise setting.
Azure OpenAIResponsible AIEnterprise Prototyping
Read engagement detailsStrategy6 min read
AI Readiness: The Work That Happens Before You Touch a Model
Organisations that struggle to get value from enterprise AI investments almost never fail because of model capability. They fail because the data is not ready, the teams are not aligned, and the governance layer does not exist. This post outlines the readiness work that precedes meaningful AI adoption.
AI StrategyEnterprise AIData ReadinessGovernance
Read insightReady to Begin
Start your AI Governance Framework program
Work with our team to design an enablement program matched to your team's readiness, platform priorities, and delivery timeline.
Responsible AI Policy Design
MCT-Led Delivery
Microsoft Purview for AI
Azure AI Content Safety
