This year’s promising outlook for initial public offerings is worth celebrating. Successful transactions have potential to jumpstart an IPO market that has seen limited activity the past two years.
But for companies whose growth trajectory is tied to artificial intelligence, how well they navigate a rapidly changing regulatory and legal landscape will directly impact their ultimate success.
Given the ambition of IPO-ready companies to lead in the AI space, their legal teams will need to continue navigating a complex legal and regulatory environment in the quest to go public and generate profits. Many state and federal regulations of generative AI software and tools are still evolving and subject to change and interpretation.
New York Times Co. sued OpenAI and Microsoft Corp. in December 2023 for copyright infringement over alleged unauthorized use of published work to train AI technologies.
Regulations are also evolving in the international sphere. France’s competition authority fined Alphabet Inc. for 250 million euros (about $269 million) in March due to alleged use of copyrighted content in training Google’s AI service, Gemini.
Courts haven’t yet interpreted terms of open-source licenses. This poses numerous legal risks to companies whose AI business depends on a company’s ability to enforce open-source licensing agreements with customers, as well as companies that develop and commercialize open-source software for customers.
These licenses could be construed to impose unanticipated conditions or use restrictions. Licensees may also face claims demanding the release of proprietary source code developed based on the open-source license.
Newly public companies can also expect increased scrutiny from regulators and competitors—relating to AI or otherwise. The Federal Trade Commission launched an inquiry in March focused on Reddit Inc.’s sharing of user-generated content with third parties to train AI models. Reddit has also faced patent infringement claims, though it’s unclear whether they have a basis.
A particularly risky hurdle is the development of stricter data privacy laws and potential impact of such laws on AI-centric companies, including those that use personal information data to train AI products.
For example, the California Consumer Privacy Act and the Virginia Consumer Data Protection Act impose restrictions on disclosure of data collected from residents in those states that have the right to opt out of certain sales or transfers of personal information. Connecticut, Utah, and Colorado enacted similar legislation that took effect last year. As a result, the risk of legal claims in the event of a security breach is increasing and regulators are watching.
Companies that use artificial intelligence markup language face additional risks. The legal and regulatory environments around AIML are changing quickly. Companies must ensure the content their AIML solutions assist in producing doesn’t infringe on or misappropriate intellectual property rights of others or violate applicable laws or regulations.
IPO-ready, AI-centric companies have faced a challenging legal and regulatory environment for years. Now that these companies are going public, we will witness the next stage of their evolution and see how their legal advisers guide their clients. Their success as public companies may hinge on how well they adapt to a rapidly shifting legal landscape.
This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.
Author Information
Ari Edelman is partner in Olshan Frome Wolosky’s corporate group and represents companies in going-public transactions.
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