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Writer's pictureILLIA PROKOPIEV

Data Ownership in AI-Related Agreements

Artificial Intelligence (AI) is revolutionizing sectors, boosting efficiency, and enhancing the decision-making process. However, as AI systems intensify their dependence on data, the quandary of data ownership emerges as a central concern in framing AI-centric contracts.

Types of AI-Related Agreements:

  • Development and Consulting Agreements

  • Partnership and Collaboration Agreements

  • Software Licence Agreements

  • Service Level Agreements

  • Non-Disclosure Agreements

  • End-User Licence Agreements

The Heart of the Matter: Data Ownership


AI and Data Dependency: AI leans on data for training, testing, operation, and continuous enhancement. The data, often a source of competitive advantage, becomes a contentious point in negotiations.


The Ownership Misconception:

  • A frequent stumbling block is an emphasis on "ownership." In jurisdictions like the EU, data, as information, isn't property and can't be "owned" like tangible assets.

  • Though some ownership rights might apply to data encompassed within an IP object (e.g., copyrighted work), individual, especially machine-generated data, often fall outside IP protection.

  • There are instances where data may be shielded as a trade secret, providing safeguards against unsanctioned acquisition, use, or disclosure.

Strategic Approach to AI Contract Drafting:

  • Reflective Terminology: Employ terms mirroring applicable law to minimize potential misunderstandings.

  • Focus on Exploitation Rights: Instead of pure ownership, zone in on rights of exploitation and confidentiality clauses. Such a shift aligns better with trade secret protections.

  • Avoid Negotiation Stalemates: Realizing an agreement can become easier when understanding each party's commercial interests and focusing on rights of use, confidentiality durations, and exploitation fields.

  • License Over Exclusivity: Even when one party owns most IP rights, granting a license can be a win-win. By discerning each party's core concerns, you can draft terms catering to both interests.

  • Anticipate Data Evolution: Given the dynamic nature of data and AI, anticipate what data will be collected, used, and generated. As AI systems evolve, data integration grows, amplifying the challenge of rights allocation in agreements.

Conclusion: Crafting a clear, transparent AI-related agreement necessitates collaboration from the onset. A proactive approach, combined with legal expertise in IP law, trade secrets, and data regulation, can pave the way for robust, dispute-free contracts. Embrace the AI age, but with a legally clear and strategic vision.


Note: The information provided is not legal, tax, investment, or accounting advice and should not be used as such. It is for discussion purposes only. Seek guidance from your own legal counsel and advisors on any matters. The views presented are those of the author and not any other individual or organization. Some parts of the text may be automatically generated. The author of this material makes no guarantees or warranties about the accuracy or completeness of the information.

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