Generative artificial intelligence (AI) could make commercial contract negotiations “worse”, the founder of contracting specialists Radiant Law has argued.
Alex Hamilton said that although it could make contract review “far faster”, he was not sure how much time was spent on this, and the AI’s impact on contract drafting would be “marginal” at the most.
Mr Hamilton, chief executive of the London law firm, described GPT-4 as “amazing”, but making contract templates “short, clear, reasonable, and relevant” remained “the closest we have to a silver bullet” in contracting.
“AI might help you do this, but it still requires human judgement calls and the very human ability to navigate corporate decision-making – it’s always about relationships.”
In the paper GenAI and commercial contracting: what’s the point? published on LinkedIn, Mr Hamilton went on: “Ever since seeing GPT in action, I’ve worried about its potential for weaponising negotiations.
“I suspect that we are going to see more random points raised that add little to no value as GenAI is asked to review contracts. Negotiations are so often random and awful now that I’m not sure whether GenAI is going to help or make things worse. I fear worse.”
However, he said generative AI could help in a “few areas”, for example “a thoughtful person, faced with a novel contracting situation, may find GPT useful to stimulate thinking about what might be the points that matter”.
Since negotiations could be “as much about psychology as substance, a bit of AI magic applied to the tone of comments, emails and changes may help make things more palatable”.
Mr Hamilton said he expected tools that “connect clause classification with rules to spot issues in contracts (basically whether a clause you want is missing, or a clause you don’t want is included)” to improve, but they would only be helpful where the right points were raised.
This required either someone “actually thinking about the deal in front of them”, or a “thoughtful playbook being created in advance, customised for the deal type and your organisational needs” that controlled the changes being applied.
Mr Hamilton said Radiant Law would experiment with generative AI in this area but he expected the impact to be “pretty marginal”, partly because the firm was “already operating at 90% half-day turnarounds on contracts”.
On drafting, he said Ai could help with creating contract templates, but he had found only “one use case” where the problem could not be solved by document automation.
Generative AI could make contract review “far faster”, but he was “not sure that much time” was spent “reviewing and interpreting deals (other than relatively rare review projects), because reviews are so painful right now that everyone is used to just ignoring what was written down.
“So there isn’t much time to reduce in the area where GenAI will probably have the biggest impact.”
Although he had mentioned only limited use cases where the AI would help with contracting, Mr Hamilton said it “may still add lots for you as a tool” but the “only way to find out is experimenting.”
In any case, he described both in-house and private practice lawyers as “pretty bad” at adopting helpful technology.
“This is partly explained by the incentives that apply to private practice, but I’m still astounded by how little document automation (which actually works) is used by in-house teams.
“Even though AI is going to find its way into all the tools we use day-to-day, most features already in Word, Outlook etc… are ignored. I’m not convinced that five years is long enough to make an impact, even where GenAI offers a clear advantage.”
Even if generative AI was “useful and adopted”, reducing the time and cost of contracting “may increase the demand so even more time is spent” on it.
“I suspect we are going to have a lot more questions in the future about what’s in our contracts. Whether that translates into better contract management is moot.”