AI Governance & Compliance
Your board wants AI governance. Your teams want to actually use AI. Here's how to give both what they need.
Mid-market companies are getting squeezed. There's pressure to adopt AI, pressure to do it safely, and none of the infrastructure that enterprises have. You don't have a Chief AI Officer. You probably don't have a dedicated risk team. But you're still getting asked about GDPR compliance, data protection, and what happens if something goes wrong.
Most governance frameworks are built for organizations with compliance officers and legal departments on speed dial. That's not your reality. You need something practical — rigorous enough to satisfy the board, light enough that people will actually use it.
What Usually Goes Wrong
IT discovers people are using ChatGPT for work but has no framework for deciding if that's okay or not. HR worries about privacy implications but doesn't know which questions to ask. Leadership wants innovation but also wants someone to sign off that it's "safe."
Everyone's working from different assumptions about what responsible AI adoption even means. The result? Either paralysis (better not touch it until we figure this out) or chaos (everyone doing their own thing until something breaks).
Neither works.
How Governance Fits Our Approach
Governance isn't a separate workstream in our work — it's woven through everything we do.
During Discovery, we map current AI use (shadow and sanctioned) and identify where your risk exposure actually sits. Not theoretical risk — the real gaps between what people are doing and what your data protection requirements need.
During Manager Enablement, we create clarity on acceptable use, decision frameworks for "should we try this tool?" conversations, and practical guidance managers can actually apply.
During Capability Building, we build data literacy and responsible AI practices into the learning — not as compliance training, but as core skills that make people more confident and capable.
During Measurement, we track compliance alongside adoption. Because governance that no one follows isn't governance — it's just documentation.
Our Framework
We've built a lightweight governance framework designed for mid-sized businesses. It covers the compliance essentials — GDPR requirements, data protection, accountability structures — without the enterprise bloat.
Five core principles:
Enhance, Don't Restrict — Policies enable responsible experimentation, not police curiosity
Transparency Over Fear — Clear communication about how AI is used and who's accountable
People First, Process Second — Every new tool comes with a learning plan, not just a risk assessment
Shared Accountability, Clear Oversight — Cross-functional input with executive ownership
Continuous Learning — Governance evolves with technology and culture
[Insert visual of the scalable governance model — the 5-role structure]
The model scales with your business but keeps the balance constant: one executive sponsor, one technical lead, one people lead, one business lead, one employee representative. Not a committee of twenty. A small, mixed team with the authority to decide and the curiosity to question.
Download the full framework: [AI Governance Starter Guide - PDF]
Who Owns What
You'll always own your governance. We help you build the capability and frameworks, but the decisions stay with you.
Our job is to make sure those decisions are informed, documented, and actually implementable by the people who'll need to live with them. We're not here to write policy documents that sit in a drawer. We're here to help you build governance that works in practice, not just on paper.
Next Steps
Want to talk about how this would work in your organization?