AI governance consulting that your staff will actually follow

What does AI governance consulting include?

It includes an inventory of current AI use, a risk-tiering method, an acceptable-use policy, vendor and data-term checks, logging and monitoring rules, an incident process and training for managers. We write it to fit the size of your company, so a 60-person firm does not end up with a policy built for a global bank.

The output is practical. A sales rep should be able to read one page and know whether they can paste a customer contract into Claude or Copilot. An operations manager should know the steps to get a new AI tool approved. And leadership should get a monthly view of which tools are in use, what they cost and whether anything went wrong.

• AI inventory with owner, purpose, data types and vendor terms.
• Risk tiers: low, medium and high, each with required controls.
• Acceptable-use policy in plain language.
• Prompt and output logging for production tools.
• Incident and rollback process.

What is the NIST AI RMF and do we need to follow it?

The NIST AI Risk Management Framework 1.0, published in January 2023, is a voluntary US framework organized around four functions: Govern, Map, Measure and Manage. No private company is required to adopt it, but it is the most widely recognized structure for showing that AI risk is managed.

We use it as the backbone of our AI governance work because customers, insurers and auditors recognize it. Govern covers roles and policy. Map covers the inventory and the context of each use case. Measure covers eval sets, accuracy checks and bias reviews. Manage covers human review, monitoring and incident response. For generative AI, NIST published a companion Generative AI Profile, NIST AI 600-1, in July 2024, which we draw on for risks such as fabricated answers and data leakage.

Which US and EU AI laws affect a mid-size company?

The ones most likely to matter are Colorado's new automated decision law and, if you sell into Europe, the EU AI Act. A federal executive order from December 11, 2025 also sought a national AI policy framework and created a DOJ task force to challenge state AI laws, so the state picture may keep shifting.

In Colorado, the original AI Act (SB 24-205) never took effect. It was repealed and replaced by SB 26-189, signed May 14, 2026, a narrower notice-based law covering automated decision-making in consequential decisions about education, employment, lending, healthcare, housing and insurance. It takes effect January 1, 2027 and is enforced by the Colorado Attorney General. Consumers get an explanation of adverse outcomes, human review and the chance to correct their data.

The EU AI Act, as amended by the 2026 Digital Omnibus, applies to US firms that place AI systems on the EU market or whose AI output is used in the EU. Transparency duties under Article 50, such as telling people they are talking to an AI and labeling synthetic media, apply from August 2, 2026. High-risk obligations for Annex III uses like employment and credit moved to December 2, 2027. This is not legal advice; we work alongside your counsel and flag where a use case needs their review.

How do risk tiers and human review work in practice?

Each AI use case is placed in a tier based on what a wrong output could cost, and each tier carries required controls. The tier decides how much review, logging and testing the use case needs before and after launch.

A low-tier example is drafting internal meeting summaries: approved tool, no customer data, spot checks. A medium-tier example is an assistant that answers staff questions from SharePoint policies: retrieval with citations, an eval set of known questions, and logging. A high-tier example is anything that affects a customer's money, a hiring decision or health information: outputs go to a human-review queue, confidence thresholds route uncertain cases to staff, and a rollback plan is written before launch.

How do you check whether an AI vendor is safe to use?

We review the vendor's data terms, retention settings, training use, access controls and contract tier. Consumer accounts and business accounts from the same vendor often have very different terms, which is why the plan your staff signed up for matters as much as the vendor name.

For health information, any AI vendor handling it needs a signed Business Associate Agreement, and the major model vendors sign these only on certain API or enterprise tiers, not consumer plans. We record each vendor's status in the inventory so the approval decision and its reasons are written down.

Will AI governance consulting slow our teams down?

Done well, it speeds them up, because people stop guessing what is allowed. Clear rules let staff use approved tools with confidence and give managers a fast path to approve something new.

We keep the controls proportionate. Low-risk uses get a light approval, and the heavier checks are saved for the few use cases where errors would hurt customers, money or compliance. Our case studies include a compliance management tool for a regulatory consulting firm, with recurring tasks, named owners and due-date reminders, which cut status reporting from 4-5 hours to under 15 minutes. Governance can work the same way: owners, reminders and a dashboard rather than a binder.