Executive AI Governance

Innovation is moving faster than policy.

Shadow AI is already in your organization. Employees are using generative models to write code, draft emails, and analyze financial data. Without definitive governance, semantic leakage—the exposure of proprietary data into public models—is an unmanaged, boardroom-level risk.

The ISO/IEC 42001 Standard

We don't invent frameworks; we apply global standards. Our methodology is built entirely on ISO/IEC 42001, the world's first AI management system standard.

Risk Management

Identifying acceptable vs. unacceptable AI use-cases within your enterprise.

Impact Assessments

Evaluating the operational, financial, and reputational risks of AI systems.

Continuous Oversight

Establishing the internal audit controls required for defensible compliance.

Our Engagements

1

Executive Gap Analysis

Strategy Phase

A rapid, executive-level diagnostic of your current AI posture compared against ISO 42001 requirements. We interview key stakeholders, review existing policies, and deliver a prioritized risk matrix.

✓ Executive stakeholder interviews
✓ Preliminary semantic leakage audit
✓ Red-line policy drafting recommendations

2

The Deep Audit

Remediation Phase

A rigorous, technical, and operational inspection of your AI ecosystem. We build the complete AI Governance Playbook, establish the AI Steering Committee, and operationalize the controls.

✓ Formal ISO 42001 alignment roadmap
✓ Vendor risk management framework integration
✓ Board-level compliance reporting

Executive Briefing (FAQ)

Why can't the IT department manage AI governance?

IT departments are built to deploy technology and secure networks. AI Governance is a business accountability concerning legal exposure, data privacy, and ethical use. It requires cross-functional oversight from HR, Legal, and the C-Suite, not just IT.

What exactly is Semantic Leakage?

Semantic leakage occurs when employees input sensitive, proprietary, or regulated corporate data into public generative AI models (like ChatGPT). Those models can train on your data, potentially exposing your trade secrets or customer data in future public outputs.

We don't build AI models. Do we still need governance?

Yes. The vast majority of corporate AI risk comes from consumption, not production. If your vendors use AI in their SaaS products, or your employees use AI tools to increase productivity, you carry third-party AI risk that requires formal governance.

Take control of your AI exposure.

Start by evaluating your current posture across 5 critical dimensions of governance.

Schedule a Gap Analysis Take the Free Assessment