How AI Governance Check Works
AI Governance Check is a free decision-support tool that helps small and mid-sized organizations evaluate a proposed or existing use of artificial intelligence and determine how much governance that use may require. It is a companion to the Practical AI Governance Toolkit from LTECwithLance, a practical resource designed for department leaders, IT and HR professionals, administrators, faculty leaders, nonprofit directors, and business owners who need to make responsible decisions about AI without specialized legal or technical expertise.
The tool walks you through a short structured assessment covering the purpose of the AI use, the people it affects, the sensitivity of the data involved, the autonomy of the system, the level of human oversight, and the regulatory or specialized context. A deterministic, rule-based classification engine then produces one of four organizational governance levels — LOW, MODERATE, HIGH IMPACT, or STOP / ESCALATE — along with a plain-language explanation, the specific factors that drove the result, a prioritized list of recommended actions, and the exact toolkit documents to complete.
The approach is built on a simple principle: complexity should increase only when risk increases. A person using AI to brainstorm a non-sensitive marketing idea should not go through the same governance process as an organization using AI to screen job applicants, grade students, make medical recommendations, or autonomously take consequential actions. The governance model uses five plain-language stages that map to established frameworks such as the NIST AI Risk Management Framework and ISO/IEC 42001, without requiring users to learn regulatory terminology.
The five governance stages
KNOW
Identify which AI systems and use cases exist across the organization. You cannot govern what you cannot see, so the first stage is building a clear inventory of AI tools, vendors, and intended purposes.
OWN
Assign a named business owner and accountability for each AI use. Clear ownership ensures someone is responsible for the system's outcomes, risks, and ongoing review — not just its initial deployment.
ASSESS
Determine the level and nature of risk the AI use creates. This includes the sensitivity of data involved, the impact on people, the autonomy of the system, and the consequences of error.
CONTROL
Apply safeguards appropriate to the assessed risk. Higher-risk uses require stronger controls: human oversight, output verification, vendor review, transparency, and monitoring.
MONITOR
Review the system over time and respond to problems. AI systems change, vendors update models, and new risks emerge — governance is an ongoing practice, not a one-time approval.
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