5 AI legal challenges every business must address

AI’s legal landscape: As artificial intelligence continues to revolutionize industries, companies face a growing array of legal challenges and considerations when implementing AI strategies.

• The Copyright Alliance reports over two dozen AI-related lawsuits in the US alone, highlighting the legal complexities surrounding AI adoption.
• In September, the Federal Trade Commission took enforcement action against companies for making deceptive claims and promising false business results using AI hype and technology.

Key legal factors for AI implementation: Business leaders and owners must carefully consider five critical legal aspects before rolling out broad AI strategies across their organizations.

1. Technology evaluation: Assessing compatibility and integration: Companies need to evaluate their existing IT infrastructure’s compatibility with current and future AI systems.

• This involves examining infrastructures, workflows, data handling procedures, and customer interactions that AI might affect.
• Businesses must ensure that AI solutions can seamlessly integrate into their current software ecosystems and maintain service quality without violating privacy agreements.
• Scalability of AI solutions should also be considered during the evaluation process.

2. Regulatory compliance: Navigating a complex and evolving landscape: Companies must stay informed about federal, state, and international regulations governing AI use.

• Europe’s GDPR and the European Union’s AI Act have specific stipulations concerning automated decision-making procedures, which apply to most AI systems.
• Several US states are developing their own AI regulations, adding to the complexity of compliance.
• Businesses should design robust compliance frameworks that can adapt to evolving regulations, potentially requiring periodic audits and specialized compliance officers.

3. Data and security protections: Safeguarding sensitive information: Companies must prioritize data security when adopting AI technologies.

• A clear understanding of data storage locations, encryption methods, and access controls is essential.
• Jake Heller, a lawyer and AI product manager at Thomson Reuters, emphasizes the need for stringent data privacy and security measures, comparable to those in legal practices.
• Companies should inquire about data breach protocols and confirm that AI providers’ security practices meet industry standards.
• Implementing clear data governance policies, including data classification, access controls, and periodic security audits, is crucial.

4. Data training risks: Managing AI’s learning capabilities: The self-learning abilities of AI systems present potential liabilities that business leaders must address.

• Companies need to understand precisely how their data are used by AI systems, especially in sensitive domains like healthcare and finance.
• Negotiating terms of data usage with AI providers is essential, including whether providers retain rights to use the data for improving their own AI models.
• Exploring technical options like differential privacy can help protect individual data while allowing meaningful analysis.

5. Intellectual property issues: Navigating ownership and copyright concerns: Content created through AI raises complex questions about intellectual property rights.

• Ownership of AI-generated works remains a contentious issue, with potential claims from various parties involved in the AI creation process.
• Companies should apply existing intellectual property protection policies to their AI platforms and clearly specify ownership of AI-generated works in contracts with providers.
• Businesses must be aware of potential copyright infringement issues if AI systems are trained on copyrighted material.

The evolving regulatory landscape: Despite the growing need for AI regulations, progress in establishing legal guardrails has been slow.

• California Governor Gavin Newsom recently vetoed the first major piece of legislation aimed at establishing legal guardrails for AI usage of certain copyright materials and the creation of deepfakes.
• As AI capabilities continue to advance rapidly, business leaders must cautiously navigate the implementation of AI within their organizations, balancing innovation with legal compliance and risk management.