Litigation, Fines, and New Laws: The Legal Challenge of Implementing Artificial Intelligence Without Exposing Oneself
The accelerated expansion of artificial intelligence (AI) has forced governments, courts, and regulators into new and complex territory: defining how automated systems should be used, audited, and controlled as they increasingly impact the economy, healthcare, education, and public safety.
According to the report AI Risk Disclosures in the S&P 500: Reputation, Cybersecurity, and Regulation, published by The Conference Board and ESGAUGE, 13% of S&P 500 companies in 2023 reported legal risks related to AI, but that number grew to 63 companies (more than 25%) by 2025. These firms acknowledge that adopting AI may lead to fines, litigation, regulatory sanctions, and loss of investor trust if not implemented carefully and within clear regulatory frameworks.
What Legal Risks Do Companies Using AI Face?
The report identifies three major areas of legal exposure: changing regulation, compliance and penalties, and emerging litigation involving liability and intellectual property. Each of these areas presents different implications, but they all share one reality: rules are still under construction, and legal uncertainty has become a new operational risk factor.
1. Changing and Fragmented Regulation
The EU’s AI Act, passed in 2024, has become the most frequently cited regulatory framework by S&P 500 companies. This law sets strict requirements for “high-risk” systems (e.g., those impacting fundamental rights or making financial or medical decisions), mandating impact assessments, technical audits, and penalties of up to 7% of global annual revenue for violations.
According to the report, 41 companies explicitly mention the challenges of operating in a world where regulations vary by country and are sometimes contradictory. While the EU promotes a preventive, ethics-based approach, the U.S. is moving forward with more sector-based, transparency-oriented regulation—still lacking a unified federal framework.
2. Compliance and Sanctions
A total of 12 S&P 500 companies warn of the cost burdens related to regulatory compliance. Implementing AI now requires new oversight processes, external audits, decision logs, and technical documentation proving how algorithms arrive at outcomes.
Companies fear sanctions from bodies such as the Federal Trade Commission (FTC), which has already launched investigations into the misuse of personal data in training models, or the SEC, which monitors how AI-related risks are disclosed to investors. Additionally, several U.S. states—including California, Texas, and Colorado—have begun drafting their own algorithmic transparency and data protection laws.
3. Emerging Litigation
The report highlights that courts have yet to fully define how existing laws apply to AI, but a surge in litigation is expected around intellectual property, privacy, and civil liability.
The most frequent concerns include:
- Intellectual Property: 24 companies cite the risk of being sued for using copyrighted data or content to train models. Artists, publishers, and authors have already filed lawsuits against generative AI developers for unauthorized use of creative materials.
- Privacy and Personal Data Use: 13 firms report the challenge of simultaneously complying with GDPR in Europe, HIPAA in the U.S. (for health data), and California’s CCPA/CPRA, complicating international data management.
- Liability for Automated Decisions: Some companies acknowledge the possibility of lawsuits if an AI system makes errors that harm consumers, employees, or patients—ranging from wrongful terminations to medical misdiagnoses.
How Does Legal Uncertainty Affect Innovation?
The lack of a unified legal framework is slowing or delaying AI investment in critical industries. Sectors like healthcare, finance, and manufacturing face the dilemma of needing to innovate quickly to stay competitive—while avoiding fines or lawsuits that could cost millions.
The report notes that most corporate leaders already view regulatory compliance as a core element of tech development. In practice, this means that before launching any AI-powered product, companies must conduct ethics reviews, bias testing, legal impact analysis, and fully document their algorithmic decision-making.
Unlike traditional innovations, AI errors can have immediate legal and media consequences. A malfunction in a health app or a faulty credit recommendation can not only damage consumer trust—but also lead to class actions or regulatory fines.
What Role Do Corporate Boards Play in Managing AI Legal Risks?
The report emphasizes that corporate boards must play an active role in overseeing legal and ethical risks associated with AI, just as they do with financial or cybersecurity issues.
Key recommendations include:
- Incorporate AI into corporate governance frameworks, with internal policies on responsible use, privacy, copyright, and fairness.
- Establish digital ethics officers or committees capable of assessing risk before deploying automated systems.
- Update financial and regulatory disclosures to include the potential legal impact of AI on operations.
- Train executives and employees on emerging laws, especially those concerning data use, algorithmic transparency, and bias.
Analysts warn that investors are increasingly demanding transparency about how companies manage AI risks—and that AI governance will soon become a key factor for attracting capital and retaining market confidence.
What Legal Scenarios Could Dominate the Near Future?
The study projects that AI’s legal landscape will evolve rapidly over the next three years. Key trends companies should anticipate include:
- International Regulatory Harmonization: The EU and U.S. are beginning talks to align on core principles such as transparency, auditability, and human rights in AI systems.
- Specific Liability Laws for Algorithmic Decisions: Autonomous systems may soon be held to standards similar to those for self-driving cars or medical devices.
- Stronger Intellectual Property Protections: New rules may require explicit licensing for using copyrighted materials in generative model training.
- Algorithmic Traceability Requirements: Regulators will demand companies document how models reach decisions, with third-party verification capabilities.
- Expansion of the “Material Risk” Concept: Annual company reports will increasingly detail AI’s potential legal and financial impact.
These developments will force organizations to invest more in compliance, legal counsel, and technical audits to reduce their exposure.
What Can Companies Do to Reduce Litigation and Regulatory Risk?
The report concludes with actionable steps corporations can take immediately:
- Conduct legal and ethical audits of AI systems before commercial deployment.
- Ensure data traceability for model training, including verified sources and licenses.
- Adopt “human-in-the-loop” policies to ensure human oversight in sensitive decisions.
- Update contracts with technology providers to include shared liability clauses for potential AI errors.
- Strengthen internal compliance culture by training all relevant teams—from tech to marketing—on applicable regulations.
The challenge for business leaders is to integrate AI into governance with the same rigor they apply to finance and operations, while communicating clearly to maintain stakeholder trust.
A New Chapter in the Relationship Between Law and Technology
The rise of artificial intelligence marks the beginning of an era where technological innovation and legal compliance must go hand in hand. Companies that adopt a proactive approach—centered on ethics, transparency, and traceability—will be best positioned to reap the benefits of automation while avoiding the cost of irresponsibility.
Legal and regulatory risks are no longer a marginal issue; they are now a strategic pillar for the world’s largest companies. In the AI era, compliance is not just an obligation—it’s a competitive advantage that could define the difference between leadership and loss of trust.
