Hive Advisory Group helps mid-market leadership teams find the AI already in use across employees and vendors, measure it against ISO/IEC 42001 and the NIST AI Risk Management Framework, and put ownership, policy and oversight in place. The work starts with what is in use today, and ends with a framework leadership can act on.
For teams comparing AI governance tools or platforms, an independent view of what the business needs to govern tends to make that choice simpler. Hive is an advisory firm, not a software vendor.
A short conversation about where AI governance stands in your business today and whether Hive is a good fit. No preparation needed.
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Most leadership teams arrive with one of these questions. The first conversation is usually about which one matters most right now.
A gap assessment against ISO/IEC 42001 and the NIST AI Risk Management Framework, sized to a mid-market organization. Customers, insurers and regulators are starting to ask for exactly this, and it is far easier to answer before the question arrives.
About the AI Risk & Governance ReviewAn inventory of the AI across teams, including agents and tools that arrived through vendor updates and personal accounts (shadow AI), set against what contracts, client commitments and your own policy already require.
Read: Your AI footprint is bigger than your AI budgetA board-approved AI policy, acceptable-use rules for staff and a vendor AI clause for contracts, drafted and adopted in two weeks. The fastest way to put something defensible in place while the larger review is scoped.
About the AI Policy & Acceptable Use engagementWhere AI lives across the organization in practice, including shadow AI.
How that usage lines up against contractual and client obligations.
Where you stand against ISO/IEC 42001 and the NIST AI RMF, control by control, in plain language.
Exposure prioritized by severity, and a governance plan leadership can act on now.
Both are voluntary, both are becoming the language customers and auditors use, and both were written with large enterprises in mind. Our work is translating them to what a mid-market company actually needs.
The first international management-system standard for AI, published in late 2023. It defines 38 controls across 9 objectives covering policy, roles, impact assessment, data, lifecycle and third parties. Enterprise buyers increasingly prefer suppliers aligned with it, which pulls mid-market vendors into the same requirement. The review tells you how far you are from alignment, and whether certification is worth pursuing at all.
The US reference framework, organized around four functions: Govern, Map, Measure and Manage. It is the framework most US regulators, insurers and large customers point to when they ask what good looks like. The review maps your current practice to each function, so leadership can say which parts are covered and which are not.
Agents act on your behalf, which changes the governance question. Large enterprises are scaling them; most mid-market companies are reading about them and hesitating, and the hesitation is usually right. The Agent Readiness Review answers the four questions that decide whether an agent is safe to deploy, in two to three weeks.
Which processes are safe to hand to an agent, which need a human in the loop, and which should stay out of scope for now.
The approval, logging, rollback and human-review controls each workflow needs, sized to the risk and written so the team can run them.
What an agent may read, write and send, and how that squares with client confidentiality, privacy obligations and your contracts.
How the vendor agreement allocates responsibility when an agent acts wrong, and what to negotiate before signing.
Leadership receives a workflow-by-workflow readiness decision, a control design for the workflows that pass, and contract language for the vendors involved. Often run as a module inside the AI Risk & Governance Review, or on its own for a specific agent decision.
Once a framework and a policy are in place, both ISO/IEC 42001 and the NIST AI RMF expect a periodic review. The Annual AI Audit is an independent look at whether the controls you adopted are still being followed, whether the inventory has changed, and what has arrived since the last review.
It is deliberately lighter than the first review: two weeks, a refreshed inventory, a control-by-control check and a short findings report written for the board. Available to Hive clients after a review, and to companies that built their own framework and want an outside opinion on it.
What AI is in use now versus the last review, including new vendor features and agents.
Whether the policy, approvals, vendor terms and monitoring adopted last time are actually being followed.
Where the business has moved closer to, or further from, ISO/IEC 42001 and the NIST AI RMF.
A short report leadership can hand to the board, an insurer or a customer when asked.
Senior advisors are involved throughout, and scope and pricing are agreed before any work begins.
A short conversation about your situation and whether we are the right fit.
If it makes sense, a senior advisor walks your team through how we would approach it.
A defined engagement with a fixed fee or outcome-based pricing, agreed before any work begins.
Fifteen minutes is usually enough to know whether there is something worth pursuing. Or start with the free brief: ten steps to AI governance, mapped to the NIST AI RMF.