More than the rules
We ask for more than the Regulation requires.
79pointsverified across eight dimensions and three pillars: literacy, reskilling and governance
45of 79are EstratégicaMente’s own criteria; thirty-two derive from the Regulation and two are mixed
The Regulation does not go this far. Its Article 4, in the wording in force since 27 July 2026, requires supporting the promotion of AI literacy, without imposing any documentary format or evidence. CriterIA© deliberately goes further: of the seventy-nine points in the rubric, forty-five are EstratégicaMente’s own criteria, thirty-two derive from the Regulation and two are mixed; all eight points of the reskilling pillar are our own. We ask for more because an organisation that does not know how to use AI neither optimises it nor creates value with it, however thick its file.
Own data · source: CriterIA© rubric, 79 points
What CriterIA© is — and what it is not.
What it is
CriterIA© assesses AI literacy (Art. 4 of Regulation (EU) 2024/1689), reskilling and organisational governance for the responsible use of artificial intelligence. It is a private, voluntary methodological seal, aligned with the spirit of the codes of conduct in Art. 95 of the Regulation. What it does verify: that the organisation has method, training and a culture of criterion in its use of AI — verifiably, with every issuance anchored on blockchain.
What it is not
It does not constitute the EU declaration of conformity or the CE marking provided for in the Regulation, nor does it replace any applicable conformity assessment procedure (Arts. 43-44), and it is not a certification issued by an accredited body.
Pillar · Governance
Governing AI is not about knowing how much technology an organisation uses. It is about knowing where it is used, what for, who is accountable, which risks are accepted and what evidence shows they remain under control.
Our thesis: literacy, reskilling and governance
Without literacy, governance and reskilling, AI is not an advantage: it is a risk. Artificial intelligence does not fail because of the technology: it fails when it enters an organisation that does not know how to use it, has not redesigned its processes to receive it and has no way of deciding who answers for what it produces. In that scenario it saves no work: it multiplies the error, makes it faster and spreads it further.
Literacy. That people know what the tool does, where it fails and when to distrust it. It is not teaching prompt writing: it is teaching people not to believe the answer.
Reskilling. That roles are redesigned around what the person contributes once the machine does the rest. Without this, AI frees no time: it creates confusion and resistance.
Governance. Inventory, risk classification, human oversight with a real ability to intervene, and a record of what was decided and why. Without this there is nothing to show when someone asks.
A law firm tells you whether you comply. We train your team, redesign how you work and then issue our private verification seal. Those are three different things. We applied it at home before any client: we have our consultant network trained with an auditable record, and verification is separated from drafting.
Technological transparency: we apply our own method to ourselves
Our clients' data is stored in the European Union (Ireland). Calls to AI models involve a transfer to the United States under standard contractual clauses. Full detail in our AI Policy.
If you use generative AI, four rules: always take a commercial plan with a DPA, never consumer accounts. Check how your provider transfers data.