HRMS does for people what no one does for your agents

When you hire someone, you put them in a system. You have a role, scope, competencies, manager, status. You know what they can do, who they report to, when they need a review.
When you deploy an AI agent, you have none of that.

You have a tool. It may work. It may not. Someone configured it six months ago. That person no longer works here.

Organizations are building fleets of agents with no governance at all. One team buys Copilot. Another builds its own GPT-4o pipeline. A third uses Make.com to automate email. No one knows what duplicates what, what is live, or what runs without any oversight.

This is not a technical problem. It is an organizational problem that does not have a name yet.

There is no word for what your organization is missing

We have been talking to chief operating officers for years. We ask the same question: what AI resources does your organization have?

Most go quiet. Not because they have nothing — but because they do not know how to answer.

They know Copilot runs somewhere. That sales is “trying something with ChatGPT”. That IT stood up a document pipeline. But no one can say what that system can do, under which conditions it runs, who owns it, or whether it duplicates what the next department built.

There is no inventory. No vocabulary. No place where a COO could ask: what AI resources do we have for this process?

We started looking for a name for that gap.

We called it

AIRS — AI Repository of Skills.

A system that records not tools, but competencies. Not “we have a chatbot”, but “we have an agent that can: read invoices in format X, escalate to department Y when condition Z applies, in the context of our Comarch ERP”.

Every agent has six attributes:

• Agent — who: name, model, business-side owner.
• Skills — what it can do: concrete tasks, not vague categories.
• Context — where it operates: ERP, CRM, WMS, external APIs.
• Constraints — what it must not do; when it escalates to a human.
• Owner — who is accountable operationally, not just technically.
• Status — active, in pilot, retired.

That is closer to an operational resource catalogue than an IT asset register. And that is why it is not a standard yet — IT thinks of agents as infrastructure; operations lack language to name them. AIRS provides that language.

Why this matters now

Organizations are in a phase comparable to the early years of ERP. Deployments run fast, without governance, without structure. In three years the same companies will try to understand what they have, how it works, and why half of it never delivered value.

An agent inventory built today costs a fraction of an audit done after the fact.

If your organization is rolling out AI and no one can answer what AI resources we have for this process — this is exactly what you are missing.

Start with one question: how many AI agents run in your company today, and who is operationally accountable for each? If the answer is hard — let’s talk.