As founders plan for an increasingly AI-centric future, Gusto co-founder and head of technology Edward Kim said that cutting existing teams and hiring a bunch of specially trained AI engineers is “the wrong way to go.”
Instead, he argued that non-technical team members can “actually have a much deeper understanding than an average engineer on what situations the customer can get themselves into, what they’re confused about,” putting them in a better position to guide the features that should be built into AI tools.
In an interview with TechCrunch, Kim — whose payroll startup generated more than $500 million in annual revenue in the fiscal year that ended in April 2023 — outlined Gusto’s approach to AI, with non-technical members of its customer experience team writing “recipes” that guide the way its AI assistant Gus (announced last month) interacts with customers.
Kim also said that the company is seeing that “people who are not software engineers, but a little technically minded, are able to build really powerful and game-changing AI applications,” such as CoPilot — a customer experience tool that was rolled out to the Gusto CX team in June and is already seeing between 2,000 and 3,000 interactions per day.
“We can actually upskill a lot of our people here at Gusto to help them build AI applications,” Kim said.
This interview has been edited for length and clarity.
Is Gus the first big AI product that you’ve released to your customers?
Gus is the big AI functionality that we launched to our customers, and in many ways ties together a lot of the point functionality that we’ve built. Because what you start to see happen in apps is they get littered with AI buttons that are, like, “Press this button to do something with AI.” Ours was, “Press this button so we can generate a job description for you.”
But Gus allows you to remove all of that, and when we feel Gus can do something that is of value to you, Gus can in an unobtrusive way pop up and say, “Hey, I can help you write a job description?” It’s a much cleaner way to interface with AI.
There are some companies that say they’ve been doing AI for a million years but didn’t get attention until now, and others that say they only realized the opportunity in the last couple years. Does Gusto fall in one camp or the other?
The big change for me is, when you talk about software programming, for most people, it’s not accessible. You have to learn how to code, go to school for many years. Machine learning was even more inaccessible. Because you have to be a very special type of software engineer and have this data science skill set and know how to create artificial neural networks and things like that.
