“AI has a place and it drives value in certain areas, but in certain areas, you don't need AI,” says Rishi Khosla, co-founder and CEO of OakNorth. Rules-based approaches, he adds, are sometimes sufficient.
But Khosla says that while generative AI is on his radar, the company has no immediate plans to integrate the technology into its core product. “Some technology is great from the get-go, some is exciting but wobbly,” he says. Because of problems with accuracy and reliability, he says today’s generative AI models are not ready for prime time in a credit intelligence business that faces compliance and regulatory requirements. That said, his engineering team keeps testing the waters through experiments, like a recent AI hackathon focused on how generative AI could be used to enhance the predictive industry forecasting model.
Outside of the core product, however, OakNorth is going all in on generative AI. The company is finding a wide range of generative AI use cases in marketing, sales, finance, and operations that can increase productivity and find efficiencies. In marketing, generative AI helps the company to create content such as press releases, corporate blog posts, and other company information. The technology’s application to content has turned out a surprising dividend. As inaccuracies come up in text generated by AI, it helps OakNorth identify misinformation about the company or its people on the internet. It can then track it down to make sure it’s updated.
“If you ask the generative AI to write a bio of an executive, you might get 90% or 95% of correct information,” says Khosla. “But maybe some of the information is incorrect and that's because somewhere, perhaps on page 27 of Google, there's something that's incorrect. And so it can actually be helpful in terms of discovering if there is some information out there that is not correct, and then you can go and find that and have it corrected.”
But one of the biggest impacts generative AI has had on OakNorth is through the changes it has sparked in the talent market. “Getting data analysts has always been hard,” Khosla says. “The interest in generative AI has made that harder.”