AI Governance and Risk Review.
Most companies started using AI tools before anyone wrote a policy. This engagement identifies where your AI usage creates data and security risk and gives you a practical starting framework for governing it.
AI tools moved faster than the security team.
An engineer starts using an LLM in the development workflow. Someone adds a copilot to the codebase. A customer service team starts feeding support tickets into a third-party AI tool. Customer data ends up in a prompt. Nobody wrote down a policy. The security team finds out later, if at all.
Investors and enterprise customers are starting to ask specific questions about AI governance. Regulators are catching up. Getting ahead of this does not require a hundred-page policy. It requires knowing what you have, where the risk is, and what practical controls to put in place.
Common situations where this applies.
- Companies using LLMs for internal tooling or customer-facing products
- Startups with AI features and no formal data governance policy
- Teams where individual employees use third-party AI tools with company or customer data
- Organizations facing investor or enterprise customer questions about AI risk
- Companies in regulated industries where AI data handling has compliance implications
What you get.
- Inventory of AI tools and usage patterns across the organization
- Data flow review for AI-adjacent processes
- Risk assessment by tool and use case
- Governance framework starter covering policies, acceptable use, and data classification
- Recommended controls and monitoring approaches
- Executive summary suitable for investor or board review
Available as a standalone engagement or as an add-on to an active retainer.
Not sure what your exposure actually is?
That is exactly the point of this engagement. Book a call and we will figure it out together.