In demand

AI governance that lets you keep moving.

The organizations that will struggle with AI are not the ones that adopted it too fast. They are the ones that adopted it without knowing where it was, who owned it, or what it was allowed to decide.

AI arrives from three directions at once

Almost every organization underestimates its own footprint, because it is only counting one of them.

Bought

Vendors switch AI on inside products you already pay for, often without asking.

Built

Your teams ship features with it, at the speed the business is asking for.

Brought

Staff use whatever tool helps, whether or not anyone approved it.

One organization, one set of consequences Your customers, your regulator, and your board will not care which door it came through.

Governance fails when it only covers the middle column. Most of the exposure is in the other two.

The problem, stated plainly

AI governance has an awkward property: the moment you need it is usually the moment it is too late to build it calmly. A customer sends an AI questionnaire before contract renewal. A board member asks what the company's exposure is. A model produces an output that harms someone, and the first question is who approved it.

Each of those is answerable in a week if the groundwork exists, and a quarter of panic if it does not. The work itself is not exotic — it is inventory, classification, clear rules, and named owners. It is simply work that nobody owns until someone is made to own it.

The moment you need AI governance is usually the moment it is too late to build it calmly.

What we will not do

We will not hand you a control framework that halts AI adoption, because your teams will route around it and the engagement will have been wasted. We will not sell you an AI governance platform either, because Innovide does not sell anything. Most organizations at this stage need clarity and decision rights far more than they need a tool.

How the engagement runs

Five phases. Typically six to ten weeks depending on size and how much AI is already in the estate.

  1. Find what is already running

    Almost every organization underestimates its AI footprint. The first phase builds a real inventory: sanctioned tools, models your teams are building with, AI features quietly enabled inside SaaS you already pay for, and the shadow usage nobody has been asked about. This step alone frequently changes the conversation.

  2. Classify by consequence

    Not all AI needs the same scrutiny. A drafting assistant and a system influencing credit, hiring, safety, or clinical decisions belong in different tiers. We set a classification scheme tied to real consequence, so governance effort lands where the exposure actually is instead of spreading evenly and thinly.

  3. Set the rules and the decision rights

    Acceptable-use policy for staff, development standards for builders, and due-diligence criteria for vendors. Just as importantly: who decides, who can say no, and what happens when someone wants an exception. Policy without decision rights is a document, not a control.

  4. Design oversight that survives contact

    Meaningful human review at the points where it changes an outcome, escalation paths for AI-specific failure modes, evaluation and monitoring expectations, and named owners. Oversight that exists only on paper fails exactly when it is examined.

  5. Make it defensible

    Mapping to NIST AI RMF and ISO/IEC 42001, with EU AI Act obligations flagged where they reach you. The output is evidence you can put in front of a customer, a board, an auditor, or a regulator without a scramble.

What you end up with

  • An AI system inventory you can actually maintain
  • A risk classification scheme and a working intake process
  • Acceptable-use policy and AI development standards
  • Vendor and model due-diligence criteria
  • Human oversight, escalation, and AI incident handling
  • Evaluation and monitoring expectations with named owners
  • NIST AI RMF and ISO/IEC 42001 mapping, EU AI Act duties flagged
  • A board-ready summary of position and residual exposure

Good moments to start

  • You are about to ship an AI-supported feature to customers
  • Customers have begun asking AI-specific diligence questions
  • Your board has asked for a position and nobody owns the answer
  • Teams are building with AI faster than anyone is reviewing it
  • You operate in a regulated sector and the guidance is firming up
  • You suspect there is shadow AI use and would rather know

Start with a conversation.

No charge, no obligation, and no pitch deck. Tell us what is putting pressure on you and we will tell you honestly whether we can help.

Get in touch