Advisory Service
AI Readiness & Secure Agents
Move from AI risk to AI readiness with governance frameworks, secure agent deployment, and Copilot controls—before shadow AI and unmanaged costs become enterprise liabilities.
The Problem: What Goes Wrong Without AI Governance
Shadow AI Proliferation
Employees adopt AI tools without IT or security involvement. Sensitive data flows to unvetted APIs. By the time leadership learns, exposure has already occurred—and remediation requires unwinding embedded workflows.
Copilot Cost Creep
Microsoft Copilot and Azure OpenAI consumption scales unpredictably. SCU costs mount without visibility into which agents, users, or processes drive consumption. CFOs see charges; CIOs cannot explain them.
Unmanaged Agent Risk
AI agents access internal systems, databases, and APIs. Without governance, an agent misconfiguration or prompt injection can exfiltrate data, modify records, or create compliance violations—all within seconds.
Regulatory Uncertainty
The EU AI Act, Canadian AIDA proposals, and sector-specific requirements create compliance uncertainty. Organisations deploying AI without documented governance face regulatory exposure they cannot quantify.
Failure Patterns We See
- A financial services firm discovers employees have been uploading client documents to ChatGPT for six months—only after a compliance audit.
- A healthcare organisation's Copilot deployment surfaces PHI in meeting summaries shared with external participants.
- Azure OpenAI costs reach $180,000/month before leadership understands which processes are consuming SCUs.
- An AI agent with database access modifies production records after an adversarial prompt—and there is no audit trail.
- A board asks "what is our AI risk posture?" and the CISO cannot provide a structured answer.
What Changes in 30–90 Days
AI Inventory Completed
Comprehensive mapping of all AI tools, agents, and APIs in use—sanctioned and shadow—with data flow analysis.
Governance Charter Established
AI governance framework aligned to ISO 42001 principles with policies for acceptable use, data handling, and agent deployment.
Copilot Security Configured
Microsoft Copilot deployment with sensitivity label enforcement, DLP policies, and user access controls.
SCU Cost Controls Active
Azure OpenAI consumption dashboards with budget alerts, quotas, and business unit cost allocation.
Agent Security Framework
Controls for AI agent deployment: authentication, authorisation, audit logging, and prompt validation.
Board-Ready AI Risk Report
Executive dashboard showing AI risk posture, governance maturity, and cost trends with quarterly cadence.
How We Work
Phase 1
Discovery & Assessment
- AI tool and agent inventory
- Shadow AI identification
- Data flow and sensitivity mapping
- Current governance maturity assessment
Phase 2
Strategy & Design
- AI governance charter development
- Risk classification framework
- Acceptable use policies
- ISO 42001 alignment roadmap
Phase 3
Controls & Implementation
- Copilot security configuration
- Agent authentication controls
- DLP and sensitivity enforcement
- Cost management setup
Phase 4
Testing & Validation
- Control effectiveness testing
- Agent security validation
- Prompt injection testing
- Data leakage scenarios
Phase 5
Transition & Empowerment
- Governance board establishment
- Training for AI champions
- Operational runbooks
- Escalation procedures
Phase 6
Ongoing Support
- Quarterly governance reviews
- Emerging AI risk briefings
- Policy updates for new tools
- Regulatory change monitoring
Deliverables
- AI Governance Charter
- AI Tool and Agent Inventory
- Risk Classification Framework
- Acceptable Use Policy
- Copilot Security Configuration Runbook
- Agent Deployment Standards
- SCU Cost Management Dashboard
- Prompt Security Guidelines
- Incident Response Playbook (AI-specific)
- Training Materials for AI Champions
- Regulatory Compliance Mapping (EU AI Act, AIDA)
- Board-Ready AI Risk Report Template
Timeline & Stakeholders
Typical Timeline
10–14 weeks for governance framework and initial controls. Ongoing governance operates in quarterly cycles with continuous monitoring.
Stakeholder Engagement
- Executive Sponsor: CISO, CIO, or Chief AI Officer
- Governance Board: Legal, compliance, privacy, security
- IT & Security: Cloud architects, identity team, SOC
- Business Units: AI champions, power users
- Finance: CFO or finance lead for cost governance
Proof: Industry Examples
Aviation & Simulation
Global Simulation Provider
A flight simulation company needed to deploy Copilot without exposing proprietary training data. We implemented sensitivity-aware Copilot configuration, established AI governance aligned to defence sector requirements, and reduced shadow AI tools from 23 to 4 sanctioned platforms—while enabling 2,400 users with controlled Copilot access.
Financial Services
Regional Credit Union
After discovering unmanaged ChatGPT usage across 14 departments, we deployed a comprehensive AI governance program. Within 75 days: an AI governance charter, Copilot with member data protections, Azure OpenAI cost controls saving $47,000/month, and a trained governance board reviewing all AI deployments.
What We Will Not Do
- Launch pilots without governance: We do not enable Copilot or AI agents without establishing the governance framework they require.
- Deploy agents without controls: We do not implement AI agents that access internal systems without authentication, authorisation, and audit logging.
- Ignore cost governance: We do not enable AI consumption without visibility, budgets, and business unit accountability.
- Create theoretical frameworks: We do not deliver AI governance that exists only in documents. Every policy has implementation and enforcement.
Prepare Your Organisation for AI
Request an assessment to understand your AI risk posture and create a roadmap to governed, secure AI adoption.