AI GOVERNANCE

The cost of shadow AI: what you never see on the AI invoice

Nobody approves a shadow AI budget. It pays for itself: a subscription on an employee's card, an Azure environment nobody turns off, a process that depends on an application with no owner, and IT hours spent firefighting work that was never planned.

Why the real cost is not where you look for it

When someone asks how much a company spends on artificial intelligence, the answer is usually the sum of the corporate accounts. Shadow AI is not there: it is on personal cards that get reimbursed without context, on duplicate licences for the same tool, and on cloud environments someone spun up to test and nobody turned off.

The second cost is time. A team that solves its own processes with applications built on the side gains speed today and loses it later: when the person who built it leaves, when a field has to change and there is no repository, when audit asks who approves what and there is no answer.

The third cost is risk, and it is the only one you cannot budget. Customer data in tools without a data processing agreement, code with licences nobody reviewed and decisions made by a model without traceability are exposures you pay for in a fine or in a lost customer.

That is why shadow AI is not fixed with a ban or an expense audit. It is fixed by knowing what is used, who pays for it and what data it touches, and then deciding what stays, what moves to a governed lane and what gets switched off.

THE CHALLENGE

The real cost is not on the AI invoice

Adding up corporate accounts does not tell you what the company spends on artificial intelligence: shadow AI is paid on other lines.

  • Invisible subscriptions

    Individual accounts reimbursed without control, tools duplicated per department and plans nobody reviews when the team changes.

  • Forgotten infrastructure

    Environments and applications built for a test that are still running, consuming and with no identified owner.

  • Rebuild hours

    When the application without a repository fails, it is rebuilt from scratch. That time appears in no cost report.

APPROACH

How it is actually measured

We measure per application and per environment, not with a single AI line nobody can break down.

  1. Inventory with owner

    A list of tools, accounts, applications and environments with who pays and what data they handle: no owner means shut down or migrate.

  2. Cost per unit

    Each application and environment with its associated consumption, to see what really weighs and what is kept out of inertia.

  3. Quantified risk

    We translate regulatory exposure and single-person dependency into estimable impact, not adjectives.

  4. Decision with numbers

    Each use gets a decision: stays, migrates to the governed lane or shuts down, with its saving and its exit cost.

DELIVERABLES

A spend picture that adds up

What leadership needs to decide without relying on corridor estimates.

  • Cost map

    Cost per application, environment and provider, including what does not appear in today's technology budget.

  • Duplicates found

    Overlapping tools, unused licences and orphan environments, with the specific figure for each one.

  • Economic risk

    Estimated exposure from people dependency, missing repositories and data without a processing agreement.

  • Savings plan

    Actions ordered by saving and effort, with date and owner, without promising cuts that break the operation.

TRUST

Optimise without breaking what works

We have managed platforms and cloud cost in companies since 2008, with offices in Barcelona and Madrid and remote collaboration across Spain, Europe, LATAM and the US. Minimum-cost criteria with the operation as the limit.

  • An inventory of real AI usage and unregistered applications, with estimated cost and risk by criticality.
  • Migration of whatever is worth keeping into a governed lane, instead of shutting it down and losing the solution.
  • Every new application starts with a repository, separate environments, an owner and a record of approvals.
  • A management report covering what is spent, what is at risk and what is decided, without technical jargon.

FAQ

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