AI Identity & Governance Advisory

• Deliver a compact, high-impact briefing for boards and executive leadership teams on what agentic AI means for the organisation's security and risk posture.
• Conduct the engagement in 90-min to 3-hours executive briefing format.  
• Explore the evolving agentic threat landscape, including shadow agents, over-permissioned copilots and machine-speed compromise.
• Discuss how peer organisations and major identity vendors are approaching AI security and governance.  
• Present the identity-first response model, with an optional tabletop exercise simulating an AI agent compromise to demonstrate how incidents unfold and where accountability gaps exist.  

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• Gain a realistic understanding of AI-related security and governance risks.  

• Enable executive leadership to make informed decisions that reduce organisational risk.  

• Improve board-level confidence in AI governance and strategic planning.  

• Strengthen regulatory preparedness through greater awareness of emerging AI frameworks.  

• Align business, security and technology leadership around a common AI governance strategy.  

• Build a strong executive foundation for secure, responsible and scalable AI adoption.

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• Conduct a structured, evidence-driven assessment to determine where AI exists within the enterprise and evaluate organisational exposure.  

• Inventory sanctioned and shadow AI, including AI agents, copilots, model integrations and AI-enabled SaaS applications.  

• Map AI identities to human ownership, entitlements, data access and potential blast radius.  

• Assess identity, access and data foundations against the requirements of agentic AI, including RBAC currency, non-human identity governance, credential hygiene and monitoring coverage.  

• Produce a risk-ranked AI exposure register and organisational readiness scorecard.  

• Recommend quick-win containment activities together with a phased remediation roadmap for the highest-priority findings.  

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• Gain complete visibility into AI identities and organisational exposure.  

• Replace assumptions with evidence-based insight into AI governance maturity.  

• Identify ownership, entitlement and access gaps across AI deployments.  

• Prioritise remediation based on measurable business risk.  

• Improve organisational readiness for secure AI adoption.  

• Establish a clear roadmap for strengthening AI identity governance.  

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• Deliver a transformation programme that designs and embeds how the enterprise will govern AI identities on a permanent basis.  

• Define the target-state AI agent identity architecture, including the Identity Fabric, delegation and runtime authorisation models, Model Context Protocol (MCP), agent gateway patterns and vendor strategy across existing identity platforms.  

• Design an operating model aligned to the EU AI Act, NIST AI RMF and ISO/IEC 42001, including AI use-case risk classification, policies, standards, accountability, registration, certification and decommissioning processes.  

• Establish human oversight, escalation procedures, Security Operations Centre integration and agent-aware incident response capabilities.  

• Build audit evidence for every AI agent action to strengthen governance, compliance and accountability.  

• Develop a sustainable governance capability that evolves alongside future AI adoption.  

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• Build a scalable governance model for secure AI adoption.  

• Establish consistent ownership and accountability for AI identities.  

• Strengthen compliance through structured governance and audit readiness.  

• Integrate AI governance into existing identity investments and operating models.  

• Improve organisational resilience with repeatable governance processes.  

• Enable future AI initiatives to be deployed faster, more securely and with greater confidence.

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