Minimization and retention
Send only what is necessary and document how long it is kept.
PrivacyRisk, data and external effects must be defined before adding autonomy.
Protection depends on the context of use.
Send only what is necessary and document how long it is kept.
PrivacyLimits tools and requires approval for sensitive effects.
AgentsReview and evidence increase as the impact of the error grows.
RiskThe legal classification depends on the territory and the specific use.
Provider, version, data, purpose, managers and users.
GovernanceIdentify affected people and foreseeable consequences.
AssessmentA new model or tool can alter obligations and controls.
Follow-upArticle 4 of the EU AI Act requires providers and deployers to take measures to ensure that their staff and other people operating or using AI systems on their behalf have a sufficient level of AI literacy. This guide explains how to turn that obligation into role-specific training and keep a record of the measures taken, without mistaking documentation for automatic proof of compliance.
14 Oct 2026 ↗ ANALISISArticle 16 of the AI Regulation assigns specific compliance, documentation, monitoring, and communication duties to providers. This guide distinguishes these tasks from those of the deployer and proposes verifiable controls, with caution regarding dates and sanctions.
13 Oct 2026 ↗ ANALISISAn agent that uses tools and changes data does not thereby acquire its own legal category or automatically become high-risk. The analysis depends on its purpose, configuration and use, and on the role each organisation plays throughout its lifecycle.
13 Oct 2026 ↗ GUIAA practical guide to connecting an AI system’s risks with the measures taken and the evidence that they work, without confusing an internal log with legally required documentation.
13 Oct 2026 ↗ GUIAA practical guide to linking each risk in a high-risk AI system to a measure, a test and documented evidence, while distinguishing legal requirements from operational recommendations.
08 Oct 2026 ↗ GUIAA practical guide to building AI literacy around specific tasks and risks. It distinguishes what institutional sources say from operational measures organisations may choose to adopt.
01 Oct 2026 ↗Safety cannot be inferred from a model sheet. It depends on the data, permissions, affected people, connected tools, and ability to stop or reverse actions.
Define owners, purpose, inventory, acceptance criteria, and incident channels before deployment.
Describe users, data, third parties, foreseeable impacts, and out-of-scope uses.
Test quality, bias, privacy, instruction injection, and failure recovery with recorded evidence.
Limit privileges, require confirmation for sensitive actions, monitor changes, and maintain a rollback path.
Stop sensitive actions before producing external effects.
Every claim must retain the official page consulted and the verification date.
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