Person
1 episodes · 16 quoted claims
Yoav Naveh says the first wave of enterprise AI adoption began with call centers and customer support, which have many repetitive tasks.
“initial experimentation started at the call center, the customer support, which is there's one nice thing about it's kind of one big call center that has a lot of repetitive tasks”
Yoav Naveh says the second wave of enterprise AI adoption was widespread use of assistants such as ChatGPT, Copilot and Claude, with the employee still responsible for the work.
“I think the second wave came into play with kind of a very high adoption of assistance.”
Yoav Naveh says operational agents face more exceptions and edge cases, but operations account for about 70% of what enterprises do, which makes the opportunity large.
“Exceptions and edge cases become much more frequent. Um, and I think that is uh such a promising opportunity for enterprise, because operation touches, you know, 70% of what they're doing.”
Yoav Naveh refers to widespread talk that 90% of AI proofs of concept fail.
“There's been all this talk about 90% of the P O Cs fail.”
Yoav Naveh says that when he asks most financial organizations what they are doing with AI, they often answer that they gave Copilot to all their employees.
“And in most organizations, still, you're asking what they're doing. Like, oh, we gave copilot to all of our employees.”
Yoav Naveh believes that building AI agents is becoming a commodity, as already seen with coding agents.
“I think building agents is on its way to become a commodity.”
Yoav Naveh says that when an agent fails, it should ask a subject matter expert specific questions rather than stop or hallucinate.
“You want it to actually be able to interact with a subject matter expert, reach out to them, ask them a specific series of questions in order to get themselves out of the hole.”
Yoav Naveh describes Reindeer AI's two-loop system, in which a second loop aggregates conversations and feedback so the agent can update its knowledge.
“You wanna have a second loop that is able to aggregate all those conversations, all those pieces of feedback.”
Yoav Naveh says new versions of an agent should be A/B tested before being rolled out across a business, as with software releases.
“Whenever you have a new version of the agent, you wanna make sure you you a B test it before you roll it out to your entire business.”
Yoav Naveh says human errors are harder to detect than agent errors because human work steps are not documented.
“it's harder to detect them because there's no documentation of the step by step that it that they're doing.”
Yoav Naveh says human mistakes are slower and do not compound, whereas agent mistakes can compound.
“It's a slower mistake. It doesn't compound. I think the question is, how do you make sure agents don't make compounding mistakes?”
Yoav Naveh says he has seen a single company with five departments that each ran a different accounts payable process.
“seen five different departments in the same company that they all have a different account payable process.”
Yoav Naveh recounts a speaker from Anthropic at an event who suggested that everyone will become a product manager and builder.
“this woman from Anthropic spoke. So we're getting into a world where everybody's gonna be a product manager and everyone's gonna build.”
Yoav Naveh says a Reindeer AI client reduced its loan quoting process from days to hours using AI.
“the outcome was that they took a process that would take them days to close and turn that into hours.”
Yoav Naveh says the lender that replies first to a customer comparing quotes is much more likely to win the deal.
“Whoever is replying first is much more likely to win the deal.”
Yoav Naveh predicts that within two years, hours-long loan quoting will be standard and firms that lack it will risk going out of business.
“The reality is that in two years time, that's going to be the standard.”