Why AI Agents Can Beat the Incumbents

Vladimir Keil (0:00)

If you want to build an aircraft, you need to procure thousands of suppliers. Someone sends a confirmation of like, hey, sorry, like this part is going to arrive two weeks later. And if they missed this email, hundreds of millions of them.

Elena Burger (0:10)

Procurement historically may have been more in a box, and now it's like, okay, it's touching legal, it's touching finance, it's touching a bunch of different software systems and people. The opportunity for the AI native startup is to say, we're going to own that entire end-to-end arc.

Vladimir Keil (0:24)

No company and no enterprise starts with fully autonomous negotiation agents from day one. Why? Because they don't trust us and they don't trust the technology from day one. By having this you-in-the-loop approach, we are feeding our agent with all the feedback and all the learnings, and then they suddenly trust us for like 10K negotiation, 20K negotiations, 100K negotiations.

Elena Burger (0:43)

When you think about what a durable vertical AI company looks like, what are the qualities that you look for? It's really, really hard to forecast your mode going forward. When you look back at all the best businesses, at the early stages, they were...

SPEAKER_3 (0:57)

If the incumbent already owns the customer, the data and the system of record, where does an AI native startup have an advantage? In this episode, Elena Burger sits down with a16z partner Seema Amble and Lio co-founder and CEO Vlad Keil to answer that question through one of the most complex parts of the enterprise, procurement.

They get into why so much of the actual work happens outside the system of record, across emails, spreadsheets, contracts, engineering data and conversations with suppliers. And Vlad explains how Lio is building agents that can coordinate that context and increasingly take on the job end to end. They also discuss how you earn enough trust to let an agent negotiate on your behalf, why building an internal AI tool can be deceptively easy until you hit the exceptions, and what changes when agents eventually sit on both sides of a transaction.

Elena Burger (1:51)

Welcome back to the a16z podcast. I'm Elena Burger. And today I'm joined by Seema Amble, a partner at a16z and Vlad Keil, co-founder and CEO of Lio, which builds AI agents for enterprise procurement. Seema, you recently wrote a piece called The Incumbents Are Coming, and it asks a question facing almost every AI application company. If an established software vendor already has the customer and the data, and the model can work across its tools, where does a startup have an advantage? And we have Vlad here, and Vlad can really help us understand where a startup has an advantage. So I think a good place to start is the cases for and against the incumbents. So if a company can connect a capable AI agent to the software it already uses, where does another application actually have a use case and an advantage there? Yeah, let me back up and frame it up a little bit. So historically, we thought about there is the incumbent, and then there's the startup, and it's a fight between distribution and innovation, which should take my partner Alex Rampel's phrase. However, now there's like this third piece which you're pointing at, which is the incumbent can layer on one of the models on top, and then there is a much more formidable competitor in the market.

So why do you need an AI native startup if you've got CloudForce, which is taking Cloud plus Salesforce and putting the two together, and then you've already got all your data and your employees are all used to using the product. So why another product? I absolutely still think there's obviously still a case for the AI native startup and it really centers around the fact that the legacy incumbent is limited to their system of record and that record they have, and they're not completing the end-to-end job. So let me put that more concretely in an example. So say you're a customer and a customer calls and says they got charged after they got canceled.

Resolving that cancellation history isn't just the customer going into the chat and saying, hey, I got overcharged. The response there, it has to hit billing, it has to look at all the chat history, it has to look at the contract. That's not one system of record, that's the knowledge around that customer and everything it touch. That's something that one system of record wouldn't touch. However, the opportunity for the AI native startup is to say, we're going to own that entire end-to-end arc.

That could be illegal, so owning everything from brief all the way through trial. Vlad can talk more about procurement, but it's really the concept of owning the end-to-end work. Yeah. Vlad, do you want to talk about where that does show up in procurement? Like where existing incumbent plus a model just is insufficient, and what have you seen just with the companies that you work with?