Risk and Reward: Navigating AI Compliance and Risk Allocation in Advertising | Event Recaps | All MKC Content | ANA

Risk and Reward: Navigating AI Compliance and Risk Allocation in Advertising

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AI is revolutionizing advertising with game-changing creative capabilities and efficiencies, but it also brings a host of new legal risks. With emerging laws like the EU AI Act putting pressure on advertisers, agencies, and AI vendors, it's crucial to understand how to navigate this complex landscape. According to industry data, 87 percent of advertisers have used or experimented with AI tools, while 68 percent of marketers are using AI in their daily work. Organizations must implement comprehensive risk management strategies while maintaining innovation and efficiency in their AI applications.

Key Takeaways

AI adoption in advertising requires careful consideration of multiple risk factors, including intellectual property rights, bias concerns, and regulatory compliance. Recent developments in AI regulation, including new state laws and the EU AI Act, are reshaping how advertisers must approach AI implementation.

Legal compliance remains a critical challenge, with organizations needing to navigate both existing laws and emerging AI-specific regulations. This includes considerations for data privacy, consumer protection, and intellectual property rights.

The platform landscape presents unique challenges, with many AI vendors' terms of service granting broad rights to user-uploaded content. Organizations must carefully review and negotiate vendor agreements to protect their intellectual property and maintain control over their content.

Risk allocation between advertisers, agencies, and vendors requires careful contractual structuring. Key areas include human oversight requirements, bias elimination protocols, regulatory compliance responsibilities, and liability allocation.

Action Steps

  1. Establish clear AI policies and responsible AI practices.
  2. Develop comprehensive vendor vetting procedures.
  3. Implement robust human oversight protocols.
  4. Create bias testing and monitoring procedures.
  5. Review and update contractual frameworks for AI usage.
  6. Establish clear data governance procedures.
  7. Create AI compliance monitoring systems.
  8. Develop incident response protocols.
  9. Build internal AI expertise.
  10. Regular review and update of AI risk management strategies.

CLE Materials

Source

"Risk and Reward: Navigating AI Compliance and Risk Allocation in Advertising." John Monterubio, senior counsel at Loeb & Loeb LLP; Jason Koye, general counsel of North America and worldwide privacy officer at Omnicom Media Group; Monique Forrest, head of North America legal affairs at Beiersdorf Inc. ANA Masters of Advertising Law Conference, 11/11/24.

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