Extract from Jared McKiernan’s article “Generative AI in eDiscovery: What to Watch”
Naturally, generative AI tools have piqued the curiosity of many legal and eDiscovery professionals, eager to learn all of the ways they might be able to help streamline their workflows and save them time and money.
It’s not hard to see why — generative AI tools have numerous potential applications in modern eDiscovery.
For instance, they can be leveraged by an API to drive the instruction set for document review, minus the upfront searching, tagging, organization, and filtering steps.
However, there are a number of challenges to consider. Here’s what to watch with generative AI in eDiscovery:
Slow Adoption
While some legal technology companies may rush to incorporate generative AI into a product to leverage the market buzz, actual adoption of this type of technology has a good chance of being slow. That’s because new technology, in general, typically sees a slower adoption trail in the legal industry due to the industry being risk-averse. This risk aversion is not surprising when you consider lawyers themselves are trained and expected to mitigate risk for their clients. The technology itself is still in its early days and requires considerable effort for it to be safely introduced to the legal profession.
