Key Questions in AI Contracting

People frequently approach AI contracts through a software licensing framework, but this Squire Patton Boggs blog points out that the problem with that approach is that the real value involved in AI systems isn’t the technology itself, but is instead associated with “the underlying data, know-how, business intelligence and outputs that flow into and from AI systems.”

Accordingly, the blog says that there are key areas that need to be addressed in contracts relating to AI systems that aren’t issues in typical licensing arrangements.  The first of these is the question of who owns the outputs? This excerpt explains:

One of the first questions any organisation looking to procure an AI system will ask is: who owns the AI-generated output? It is also one of the most misunderstood.

Many organisations will assume that because they pay for the service and provide the prompts, they automatically own everything the AI produces. In practice though, ownership and usage rights are determined by the underlying contract. Depending on the supplier’s terms, a customer may receive anything from full ownership to a limited right to use the output.

Intellectual property ownership provisions in traditional software and SaaS contracts are not always an easy fit in this context as those usually reflect a binary approach that the supplier owns their software, which is then used by a customer under license. As such they fail to address the nuances of AI system use, which often involve multiple strands (input, output, prompts, training etc.) each of which require separate contractual consideration as to ownership and usage rights.

Even where ownership sits with the customer, it is important to understand whether the supplier retains any rights that could restrict commercial exploitation. This becomes particularly important where AI-generated content forms part of a product, service or wider intellectual property strategy. It is also worth looking beyond the initial output. Rights relating to modifications, derivative works and future developments can ultimately become more valuable than the original AI-generated material.

Other key questions include responsibility for ensuring the accuracy of AI outputs, protection of customer inputs, the need to assure that customers have the right to input particular data into the AI tool, training rights, and the need for bespoke terms addressing confidentiality and data protection.