For Lincoln mid-market leaders. The clean definition, what the named regulators actually require, and why most companies don't have governance even when they have a policy.
Text Rosey · Schedule a call →AI governance is the system that decides how your organization makes AI decisions — who's accountable for what, what risks get tracked, how exceptions get escalated, and how the program changes when the technology or the regulators do.
Governance is broader than an AI policy. A policy says what's allowed; governance says how the organization keeps the policy current, audits compliance, identifies new risks, and accepts accountability when something goes wrong.
At a workable mid-market scale, AI governance has five components: named accountability, risk inventory, approval workflows, audit and incident reporting, and a quarterly change cadence with a named owner.
Most mid-market companies don't have governance, even when they have a policy. SHRM 2026 found only 49% of organizations have AI use policies, and of those, only 25% feel the policy is "future-proof." For nonprofits the gap is wider: Virtuous 2026 found 47% have no formal AI governance policy at all.
McKinsey 2025 found 28% of AI-using organizations report the CEO is responsible for AI governance, and only 17% report the board takes direct responsibility.
In regulated industries, the bar is explicit. NAIC's AI Model Bulletin (Nebraska IGD-H1, June 2024) requires insurers to maintain a written AIS Program. NITC Standard 8-609 governs AI for Lincoln-based vendors contracting with the State of Nebraska.
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