Our Approach to AI Governance in North Center
We start with a use case inventory. Most North Center businesses using AI have adopted tools piecemeal: a team member started using ChatGPT to draft emails, the office adopted an AI scheduling tool, a partner started using an AI document review assistant. The first governance step is mapping every current and planned AI use, the data those uses touch, and the regulatory frameworks that apply to each one.
From that inventory, we build a tiered classification system. Some AI uses are low-risk and require minimal governance: AI-powered grammar checking, scheduling automation with no sensitive data, and internal brainstorming tools. Others are high-risk and require robust controls: AI systems that process client health information, generate financial recommendations, or produce legal documents. The governance framework allocates oversight resources proportionally to actual risk rather than applying the same heavy process to every AI interaction.
We then design the policy and documentation layer. This includes acceptable use policies that specify which AI tools are approved for which purposes, data handling standards that govern what information can be processed through external AI systems, human review requirements that specify when AI output requires professional sign-off before use, and incident response procedures for when AI generates content that contains errors or creates compliance issues.
The monitoring and audit component is where governance moves from policy to practice. We implement logging and audit trail systems that track AI use across your operations, creating the documentation record that regulators and professional liability insurers increasingly expect to see. For North Center healthcare providers, this means HIPAA-compliant logging of AI system access to patient data. For financial advisors, it means documentation of AI use in client communication and investment recommendations.