A Concrete Deadline, Not an Abstraction
2 August 2026 is not a symbolic date. It is the moment when the AI Act begins to produce real consequences for anyone who develops, deploys, or uses generative AI systems in Europe.
From that date, the regulation will require:
- clear labelling for deepfakes and for texts generated or manipulated by AI on matters of public interest;
- disclosure to users when they interact with an AI interactive system, such as a chatbot.
These are not abstract technical requirements. They are about transparency towards people — the ability to recognise when content has been created or altered by a machine, reducing the risk of deception and manipulation in public information.
The Code of Practice: A Voluntary Tool with Regulatory Weight
To support the adoption of these obligations, the European Commission published the Code of Practice on marking and labelling of AI-generated content, developed by six independent experts with input from over 180 stakeholders.
The code is voluntary, but not neutral: providers and deployers of generative AI systems that sign up can demonstrate compliance with the AI Act’s obligations. It is a pragmatic tool for those who want to stay ahead of enforcement and build trust with users, clients, and regulators.
In a subsequent phase, the Commission will supplement the code to further clarify the scope of legal obligations.
Compliance Is Not Just an Obligation: It Is a Competitive Advantage
Organisations that prepare today — mapping their AI systems against transparency requirements, adopting risk assessment frameworks, and verifying algorithmic robustness and bias — are not simply avoiding penalties. They are building AI systems that people can trust.
This is precisely the space where IT4LIA AI Factory’s AI Trust services operate.
How IT4LIA Supports AI Act Compliance
IT4LIA AI Factory has developed an AI Trust service portfolio designed to guide companies, startups, public bodies, and research centres through every dimension of regulatory compliance and technical reliability.
AI Legal Compliance
Comprehensive analysis of the requirements applicable to AI systems under the AI Act and related regulations (GDPR, NIS2, Cyber Resilience Act). The service supports organisations throughout the entire product lifecycle — from development to market placement — producing structured deliverables for compliance verification.
AI Risk Assessment
Identification and classification of regulatory, technical, and operational risks, aligned with the NIST AI Risk Management Framework. The service goes beyond simple compliance checks, supporting a conscious and robust management of the specific risks of each application context.
Technical Reliability Assessment and Sandbox
Systematic testing of safety, robustness, reliability, and algorithmic bias in dedicated sandbox environments, supported by HPC infrastructure. Includes stress testing of protection mechanisms (guardrails) and analysis of model transparency and controllability.
AI Reliability Assessment in Critical Systems
For mission-critical systems, technical evaluation focused on uncertainty, robustness, and operational risk — including verification of safe learning requirements and application-specific operational constraints.
The Time to Act Is Now
Book a meeting now with our AI experts to analyze your use case, identify gaps with respect to regulatory requirements, and define a tailored roadmap.
Ludovica Coletta, Andrea Margheri, Emilio Tucci (ACN -National Cybersecurity Agency)
Other related materials:
- Policy page with the Code: Code of Practice on marking and labelling of AI-generated content: https://digital-strategy.ec.europa.eu/en/policies/code-practice-ai-generated-content.
- EU Icons for labelling AI-generated content: https://digital-strategy.ec.europa.eu/en/policies/eu-icons-labelling-ai-generated-content.
- FAQ: Code of Practice on Transparency of AI-Generated Content: https://digital-strategy.ec.europa.eu/en/faqs/code-practice-transparency-ai-generated-content.
- FAQ: Signing the Code of Practice on Transparency of AI-Generated Content: https://digital-strategy.ec.europa.eu/en/faqs/signing-code-practice-transparency-ai-generated-content.
- How to sign the Code of Practice on Transparency of AI-Generated Content: https://digital-strategy.ec.europa.eu/en/library/how-sign-code-practice-transparency-ai-generated-content.
- Press release : Commission publishes Code of Practice on marking and labelling AI-generated content : https://ec.europa.eu/commission/presscorner/detail/en/ip_26_1328.
