What it means to audit an AI system under ISO/IEC 42001 (and why it should matter to your company)
Most conversations about artificial intelligence inside Colombian companies circle around a single question: how do we implement it? That is the wrong question to start with. The right one is: how do we implement it in a way we can explain, sustain, and defend in front of a regulator, a client, or an internal auditor? That, in essence, is the question ISO/IEC 42001 answers.
ISO/IEC 42001 is the first international standard specifically for AI Management Systems. It does not certify that a model is “good”; it certifies that the organization building or operating it has documented, traceable, auditable processes to manage the risks AI introduces: bias, opacity, misuse of data, automated decisions without adequate human oversight, and no plan for when the system fails.
In practice, auditing under this standard means reviewing very concrete things: is there an inventory of the AI systems in use? Is each one’s purpose and known limits documented? Is there an identified human accountable for every decision the system meaningfully influences? Do training and operational data have a traceable lineage? Is there a documented process for retraining or retiring a system once it stops being reliable?
To a company that is just evaluating whether to adopt AI, this can sound like bureaucracy. It is not. It is the same kind of discipline already required in regulated Colombian sectors — think of the rigor of SARLAFT or SARO in financial services — now applied to algorithms instead of manual processes. Companies that already operate under that kind of regulatory demand are not starting from zero; they already have the control culture, they just need to point it at a new domain.
The reason this matters now, not in two years, is that AI regulation is accelerating globally, and the pattern from other domains repeats itself: companies that start documenting and governing before it is mandatory arrive at the regulatory moment with a real advantage, not a race against the clock.
Our team at BIT arrived at AI governance from a different path than most technology vendors: we did not start by building models and think about control later. We started by auditing critical information systems — more than 750 accumulated technical audits over a decade of work on MinTIC’s audit system — and today we apply that same standard, now formalized under ISO/IEC 42001, to the AI systems we design.
If your organization is seriously evaluating AI adoption, the question worth asking is not only which model to use, but whether the provider who will build it alongside you can explain, in verifiable terms, how what you are building together is governed.