Garante ruling on AI profiling: what businesses need to know
The Italian Data Protection Authority (Il Garante) has clarified how the GDPR applies to automated profiling and AI-driven decisions. The ruling tightens expectations around transparency, lawful bases and impact assessments, and shifts responsibility from abstract principles to concrete, operational duties. Below is a practical guide to what the decision means — and what organisations should do now.
Key points of the decision
– Profiling and automated decisions that significantly affect people must rest on a clear legal basis and be transparent. Generic privacy statements won’t cut it.
– Where consequences are substantial, meaningful human oversight must be available; superficial review processes are insufficient.
– Data protection impact assessments (DPIAs) are required when profiling poses high risks to rights and freedoms.
– Controllers must document testing, fairness checks and mitigation measures so they can show regulators how they manage risks.
What the ruling requires — in practice
The Authority focuses on outcomes rather than technical labels. If an algorithm can change someone’s access to services, influence credit terms, affect employment prospects or otherwise alter legal or practical status, enhanced safeguards kick in. Practical obligations include:
– Clear, accessible explanations for data subjects about how the profiling works, its significance and likely effects.
– DPIAs that identify probable harms and set out concrete mitigation plans.
– Substantive human intervention able to review and, where necessary, change automated outcomes.
– Detailed records of processing activities, model tests, validation results and remediation steps.
How to interpret the implications for your organisation
The ruling narrows the room for “we can’t explain it” defences. Complexity or commercial secrecy won’t absolve controllers from proving that risks were assessed and mitigated. Expect regulators to demand evidence — not promises: dated DPIAs, versioned model registries, logs of tests and decisions, and documented governance processes.
Top actions for compliance
Start with a systematic sweep of your AI uses:
1. Map profiling uses and rank them by impact. Prioritise DPIAs for anything that can materially affect individuals.
2. Document lawful bases for each processing activity and keep that rationale under review.
3. Design human oversight that can meaningfully challenge automated outputs — include escalation routes and decision logs.
4. Rewrite user-facing notices into plain language that explains the logic and the consequences of profiling.
5. Build technical safeguards: model versioning, provenance records for training data, robust logging, access controls and explainability tools.
6. Update contracts with vendors and cloud providers to require audit support and remediation obligations.
7. Train product, legal and compliance teams and create an incident-response playbook for algorithmic harms.
Risks and likely enforcement
Il Garante has new teeth. Enforcement may include corrective orders, temporary bans on specific processing activities and fines — up to €20 million or 4% of global turnover, whichever is higher. Besides regulatory penalties, companies face litigation, reputational harm and business disruption. Regulators are especially vigilant in sectors where profiling has immediate consequences: employment, insurance, credit and public services.
Best-practice checklist
– Adopt a “privacy by design” approach across the AI lifecycle and insist vendors provide documented safeguards.
– Use standardized DPIA templates and retain dated evidence of risk assessments and mitigations.
– Deploy monitoring and explainability tools that produce human-readable justifications for outcomes.
– Maintain multidisciplinary governance (legal, compliance, data science, product) to review high-risk projects before launch.
– Keep audit-ready trails: model benchmarks, validation reports, change logs and remediation records.
Concrete next steps
– Assign clear ownership for algorithmic risk and embed RegTech to generate auditable evidence.
– Perform or refresh DPIAs focused on datasets, features, thresholds and decision flows.
– Create accessible communications for affected users and a reliable channel for human review.
– Ensure procurement and contracts require providers to support audits, provide provenance for training data and participate in remediation.
Final takeaway
The Garante’s decision moves the needle from theoretical guidance to operational obligations. Regulators now expect demonstrable, auditable proof that profiling risks are assessed, mitigated and governed. Organisations that translate policy into concrete controls — and can show how those controls work in practice — will reduce regulatory exposure and protect trust with customers and partners.