Key Considerations & Best Practices: Minimizing Liability in AI Software Licensing

Published Date: 12/07/2024

With the increasing use of artificial intelligence (AI) in software products, companies must navigate a complex web of legal risks and contractual considerations. This article highlights key issues to address when negotiating software license agreements that involve AI, including third-party AI services and custom-built AI solutions.

"As software products and services increasingly leverage artificial intelligence (AI), software developers and licensees must navigate evolving legal risks and contractual considerations. Failure to negotiate clear software license agreements that account for unique aspects of AI-powered software may result in unexpected liability or costly litigation.

Software developers and licensees encounter two common types of AI-powered software products implicated in licensing agreements  (1) software products that leverage third-party AI services hosted offsite; and (2) software products that leverage custom-built AI, deployed either in the cloud or within on-premises infrastructure. Each type of AI integration raises important strategic considerations and risks, including intellectual property rights, data privacy, security and breach concerns, gatekeeper responsibilities, service performance guarantees, and evolving legal and regulatory landscapes.

Software Products That Leverage Third-Party AI Services

Software companies rely on powerful AI services from tech giants like Microsoft, Google, and Amazon to enhance their products with capabilities such as natural language processing (NLP) and predictive analytics. While incorporating third-party AI services can provide compelling features, professionals managing licensing must carefully consider potential risks.

Key considerations for software license agreements involving third-party AI services include allocation of liability relating to software functionality, responsibility for data privacy and security, and IP rights. Parties must also address errors or damages caused by third-party AI, data privacy and security risks, and IP considerations.

Software Products That Leverage Custom-Built AI

Software products that rely on proprietary AI solutions deployed on-premises or in the cloud can provide greater flexibility and control over features, as well as greater control over access to confidential data. However, parties responsible for providing and maintaining the underlying infrastructure face heightened risks relating to data governance, system integration, and product/service quality.

Key considerations for software license agreements involving custom-built AI include the gatekeeper role and service level agreements (SLAs) and performance guarantees. Parties must establish concrete metrics for reasonable AI performance and address issues related to data governance and system integration.

Lessons Learned from Litigation—Best Practices

Software that leverages AI functionality often handles personal information, financial data, intellectual property, and other sensitive information, raising important liability considerations. Best practices for parties seeking to proactively manage risks when writing and negotiating software license agreements include 

Carefully scrutinize broad “as is” clauses for third-party components.

Rigorously test any AI service before integration—and document these efforts.

Negotiate stronger indemnification terms with third-party AI service providers.

Identify and provide notice of functions that rely on external AI services.

Clearly articulate IP ownership rights associated with AI-generated content.

Regularly audit third-party AI performance, and provide customers with direct links to performance metrics and incident reports.

Ensure that any marketing materials accurately describe AI-related capabilities and limitations.

Memorialize procedures for secure data storage, retention periods, and deletion processes.

Ensure the AI system’s data practices adhere to data privacy laws.

By understanding and carefully considering the risks associated with licensing AI software, software vendors and licensees can proactively manage risks and negotiate favorable contract terms."

FAQs:

"Q: What are the key risks associated with licensing AI-powered software?

A: Key risks include intellectual property rights, data privacy, security and breach concerns, gatekeeper responsibilities, service performance guarantees, and evolving legal and regulatory landscapes.

Q: What are the benefits of custom-built AI solutions?

A: Custom-built AI solutions can provide greater flexibility and control over features, as well as greater control over access to confidential data.

Q: What are the key considerations for software license agreements involving third-party AI services?

A: Key considerations include allocation of liability relating to software functionality, responsibility for data privacy and security, and IP rights.

Q: What are the best practices for parties seeking to proactively manage risks when writing and negotiating software license agreements?

A: Best practices include carefully scrutinizing broad “as is” clauses, rigorously testing AI services, negotiating stronger indemnification terms, and regularly auditing third-party AI performance.

Q: Why is it important to establish concrete metrics for reasonable AI performance?

A: Establishing concrete metrics for reasonable AI performance is important to address issues related to data governance and system integration, and to ensure that AI systems meet the parties’ expectations."

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