AI Risks & Sanctions: What Companies Really Face in 2026

Since August 2026, the AI Act is fully applicable. Companies that have not yet brought their AI systems into compliance face massive financial penalties, but also operational consequences that are often more devastating than the fines themselves. A complete overview.

1. The Financial Sanctions Regime (Article 99)

The AI Act introduces a three-tier administrative fine system, calculated on global turnover — the higher amount between the fixed cap and the percentage applies:

SME and startup protection: For small structures, the fine is capped at the lower of the two amounts (fixed or percentage), to prevent economic destruction. The CNIL (French data protection authority) can also impose daily fines of up to €100,000 for persistent non-compliance.

2. Operational Consequences — Often Worse Than the Fines

Market Withdrawal

Competent authorities can order the immediate disabling, recall or withdrawal of a non-compliant AI system from the European market. For a company whose product relies on AI, this could mean a total business interruption.

Exclusion from Public and Private Tenders

AI Act compliance has become an eliminatory criterion in public procurement and in B2B contracts with large groups (banks, healthcare sector, insurance). A non-certified company is simply removed from the selection process.

Reputational Damage and "Naming and Shaming"

Regulators (CNIL, Arcom, sectoral authorities) can publicly name sanctioned companies. This "naming and shaming" leads to a breakdown of trust with investors and clients, often far more costly than the fine itself.

Aggravated Civil Litigation

Non-compliance is considered an aggravating factor in civil proceedings. A victim of algorithmic discrimination (credit refusal, automated dismissal) can obtain substantial damages if the company is in violation of the AI Act. Insufficient documentation — 200 to 300 hours of work per high-risk system — becomes evidence against the company.

3. Internal Technical Risks to Anticipate

Algorithmic Risks and Biases

AI reproduces and amplifies human biases present in training data:

• Documented real case: An AI recruitment tool systematically eliminated female candidates for technical positions — having learned from 10 years of historically biased decisions
• Credit scoring: A model using postal code as a proxy can reproduce indirect racial discrimination, exposing the bank to proceedings under both GDPR and the AI Act simultaneously

Cybersecurity Risks: Data Poisoning

AI systems are vulnerable to data poisoning attacks: malicious actors alter training data to bias the model's decisions or cause critical failures. This risk is particularly high for fraud detection systems, network security and medical diagnostics.

Data Risks: The Adoption Barrier

Approximately 1/3 of French SMEs do not yet have a structured data strategy — this is the primary obstacle to compliant AI. Incomplete, siloed or non-digitised data makes it impossible to verify the dataset quality required for high-risk systems.

4. Specific Sanctions in France (SREN Act)

Beyond the AI Act, France has adopted its own legislation targeting malicious AI uses:

5. Action Plan: 5 Steps to Protect Yourself

1. Inventory all your AI systems and classify them according to the 4 risk levels
2. Document high-risk systems: algorithms, data sources, oversight procedures (200–300h per system)
3. Train your staff on AI literacy (Article 4, mandatory since February 2025)
4. Audit for biases and implement continuous monitoring of automated decisions
5. Apply to Bpifrance: the AI Booster France 2030 programme subsidises 50% of the DATA/AI diagnostic (€13,000 excl. VAT) and up to €60,000 excl. VAT for compliant deployment