It would be an understatement to say that generative AI is taking the business world by storm. Companies are racing to find ways to integrate AI into their daily processes, and software companies are no exception. Generative AI has demonstrated a high level of compatibility with day to day software development tasks, especially those processes that are more routine. CEOs of some of the biggest tech companies in the world have even expressed that junior level developers may have their roles entirely replaced or transformed when generative AI can handle low level coding entirely by itself. However, generative AI is no magic bullet for software problems, especially in view of some of the IP implications inherent in using such tools. If you are looking to leverage generative AI in your company’s day to day software development, make sure it is part of a comprehensive view of how software ownership is handled in your business strategy.

Terms and Conditions

Before you can assess anything in regards to the general ownership of any AI generated code, it is important to evaluate the terms and conditions that may be implicated by use of generative AI tools themselves. Many companies are turning to enterprise AI offerings that can be integrated into their routine business processes, but avoiding in-house solutions means that use of AI tools will be subject to the terms and conditions set out by the provider. You should expect enterprise AI solutions to seek licenses on the outputs created by their tools, so that the creators can leverage your data to better improve their own offerings. Any code output may be retained and stored by the provider, which may create barriers to seeking certain types of IP like trade secret protection. At a minimum, always make sure any agreements with AI providers obligate them to maintain the confidentiality of your company’s information, and prevent them from having too much access to your internal code.

Copyright Protection

Similar to with patents, the Copyright Office and US Courts have offered guidance that works created solely by AI cannot be granted copyright protection. However, if the code that was generated under the guidance and control of a human, such that the code is not considered to have been created by the AI (rather the AI was used as a tool), then it may still be eligible. Similar to the points made above for patents, record keeping and proper policies will be key here, in order to make sure that any software developed is done so in such a way that requisite human involvement can be demonstrated in the future.

Patent Protection

While patent protection is not commonly used for code itself, (it is rather used for systems and methods which might be implementations of the actual executable code) – it is still important to note that the USPTO has issued recent guidance on when AI outputs may qualify for patent protection. Processes that are output wholesale from an AI tool may struggle to be eligible for patent protection, so policies should be put in place to make sure there is a requisite level of human involvement if patents are on your mind. Keeping records of the human aspect when inventing and developing new ideas is also imperative.

Trade Secret Protection

As mentioned above, the use of enterprise AI solutions may impede your ability to protect your software under a trade secret framework. To claim protection over material as a trade secret requires reasonable measures of security/confidentiality to be put in place around the relevant material. Giving a third party ownership interest, licenses to, or unfettered access to your proprietary code may create roadblocks to this requirement. However, this risk can be mitigated by closely examining the relevant agreements, and making sure that any enterprise AI providers must adhere to stringent confidentiality obligations and may only access the software locations you need them to. Note that this may be a hard ask in some cases, as training data based on your use of an AI tool is incredibly valuable to the AI developer.


Cynthia is an Intellectual Property Partner in Baker McKenzie's Palo Alto office. She advises clients across a wide range of industries including Technology, Media & Telecoms, Energy, Mining & Infrastructure, Healthcare & Life Sciences, and Industrials, Manufacturing & Transportation. Cynthia has deep experience in complex cross-border, IP, data-driven and digital transactions, creating bespoke agreements in novel technology fields.


Bryce joined Baker McKenzie's IP Practice Group following his graduation from the University of Georgia School of Law in 2020. With an electrical engineering degree, practical work experience for various electrical contractors, and studies in circuitry design and electromagnetics, he is able to leverage his experience across the patent prosecution, IP litigation, and technology transactions areas.