By Rafael Luque Ocaña

The AI inventory in a spreadsheet: why it stops working, and it's not about the number of rows

A spreadsheet works for making the list. The problem isn't making it: it's keeping it up to date. And the way it fails gives no warning — an outdated row looks exactly like a correct one.

If your organisation started its AI systems inventory in a spreadsheet, it made the right call: it's quick, it costs nothing, and it forces the one thing that actually matters at the start — sitting down and asking what's out there.

This article isn't about that decision being wrong. It's about when it stops holding up and why — which isn't what's usually said.

What isn't the problem

It isn't the number of rows. A spreadsheet copes perfectly well with hundreds of lines, and if someone tells you it stops working past a certain figure, they're inventing the threshold. There isn't one, simply because it depends on things that aren't the count.

Nor is it making the list. Going through the departments, asking what tools are used and writing them down is work, but it's work with an end point.

The problem shows up afterwards, and it's of a different nature.

What it actually is: the list isn't the work, keeping it up to date is

An AI systems inventory isn't a census. Each entry has a status, and that status changes without anyone reporting it:

  • A vendor adds an AI feature to a product you'd been using for years without it.
  • Someone switches on a module that was licensed but switched off.
  • An integration's permissions get widened to solve a one-off problem.
  • The person responsible for a system changes role or leaves the company.
  • Actual use shifts: a tool that used to inform a decision starts making it.
  • And a system's classification can change without the system itself changing, because the rule changed or its use changed.

None of these six events originates in the spreadsheet. They all arrive from outside, and the spreadsheet has no way of finding out.

The failure mode, which is what makes this different

Here's the point, and it deserves spelling out slowly.

When a spreadsheet falls out of date, it doesn't fail: it keeps working. It returns a list, tidy, looking fine. A row describing a system that no longer exists looks exactly like a correct one. One that omits a module switched on four months ago leaves no visible gap.

The error in a manual inventory is silent by construction. Nothing breaks, there's no warning, no cell turns red. And that's why it isn't discovered by reviewing the spreadsheet — which is what you'd naturally do — but by colliding with reality: someone asks about a system that isn't there, or one that was retired gets documented.

It's the same pattern that makes the inventory the precondition for almost everything else: obligations are framed around specific systems, and an incomplete list produces compliance that only looks complete.

What actually grows

Not the number of systems. What grows is the product of three things: how many systems there are, how many attributes of each one can change, and how often they change.

A company with a few very stable systems can keep a spreadsheet going for years without trouble. Another with the same systems but with integrations tweaked every month, permissions granted on demand, and vendors shipping new features every quarter is doing maintenance work that doesn't resemble making the list at all, and that nobody budgeted for.

The signal, and it isn't a number

If there's a moment when a spreadsheet stops working, it isn't recognised by counting rows. It's recognised when you can no longer answer this question about any given row:

When was this last checked to still be true, and who checked it?

As long as the answer exists for every line, the tool doesn't matter. Once it stops existing — and it usually stops existing quietly, without anyone deciding to abandon it — what's left is no longer an inventory. It's a list that was made once.

What can be done without changing tools

Three things, and none of them require buying anything.

Add two columns: who and when. Date of the last check, and the person who did it. It turns silence into something visible: a row without a recent date stands out.

Set a trigger, not a calendar. Reviewing "every six months" gets missed without anyone noticing. Reviewing when a new tool is procured, when someone changes role, or when a vendor announces new AI features ties the review to something that actually happens.

And decide who owns the list. Not who fills it in: who's accountable for it being up to date. Without that person, the two columns above stay empty just the same.

With that, a spreadsheet holds up for far longer than is usually said. And the day it stops holding up, it'll be for the right reason — because nobody can say when each line was last checked — not because someone put a number where there isn't one.

This article is for informational purposes only and does not constitute legal advice.

Frequently asked questions

Does the AI Act require an inventory of AI systems?

Not under that name: the word inventory does not appear in the Regulation. But a deployer's obligations relate to specific systems, such as those in Article 26 for high-risk systems, and they cannot be met for systems nobody knows about.

Can a system's classification change without the system changing?

Yes. If its use shifts to the point of changing its intended purpose and a system that was not high-risk becomes high-risk, whoever makes the change is considered the provider of a high-risk system (Article 25(1), point (c)). And a legislative change, such as Regulation (EU) 2026/1744, can change the dates or the scope of what is required.

How often should the inventory be reviewed?

The Regulation sets no frequency. As a governance practice, it is worth reviewing it when a new tool is procured, when someone changes role or when a vendor announces AI features, and recording on each row the date of the last check and who made it.

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