AI Governance
AI governance consulting sets the rules, owners and checks that keep AI systems safe, accountable and within the limits you choose as they move into production. HEU.AI is a firm that also builds AI, so the governance we recommend is written to be put into practice.
What does an AI governance engagement include?
We start with an AI readiness assessment of your data, technology and ways of working. From it we build a governance framework for managing risk as AI initiatives move into production. We also flag any governance question that is still open, because it can block a use case if it waits until later.
Related: AI strategy consulting.
How do you keep autonomous AI under control?
Every agent has a stated remit and written limits on what it must never do without a person. Autonomy is graded: draft only, act on one-click approval, or act unattended within agreed limits. When an agent is not confident it escalates instead of guessing, and every action is logged. A named person approves anything with legal, financial, safety or reputational consequence.
Related: agentic AI development and the autonomous agents case study.
How is your data kept secure?
Data is kept separate between tenants and functions. Access is permissioned tool by tool. We deploy on AWS, Azure or your own infrastructure, with self-hosted models where data cannot leave your environment.
Related: RAG development.
How do you check that governance is working?
Model output quality is measured in production, so a regression shows up as data and not as a user complaint. You can see this on a recruitment platform we built.
Who should own AI governance in your organization?
Each control needs an owner on your side: who approves a use case, who watches the output, and who decides when something is switched off. We write these owners into the framework, so nothing depends on one person remembering.
Related: data engineering.
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FAQ
What is AI governance?
The set of decisions about what AI is allowed to do in your organization, who approves it, and how its output is checked. Governance consulting helps you write those decisions down and put them into practice.
What is an AI governance framework?
A written set of roles, policies, risk checks and approval steps for how AI is built and used in your organization.
Does AI governance slow AI projects down?
It should not. Rules set early decide what AI may do and who approves it, so projects run inside clear limits instead of stopping to ask each time. The first step is a written assessment, whether or not you go ahead.
How is AI governance different from data governance and AI security?
Data governance covers how data is owned, kept clean and accessed. AI security protects AI systems from misuse. AI governance sits above them: it decides what AI is allowed to do, who approves it and how its output is checked, and it depends on good data governance and security.
Do we need AI governance before we use generative AI?
It is easier to set up first, because the rules shape what you build. If AI is already in use, start by finding where it runs today and what it can reach.
How do I choose an AI governance consultant?
Ask whether the firm has run AI in production, who owns each control after the engagement, and whether the framework can be put into practice.
Set the Rules Before AI Reaches Production
Book a free consultation and we will look at where AI runs in your organization today, what it can reach, and who should own each control.