Token Series Part 2 | How Much AI is Too Much?

CJ Gustafson (0:00)

We're talking about AI usage. It's supposed to make us all efficient. I have never been busier.

Ali Hussain (0:05)

CJ, I've never felt as busy myself. I actually think finance is the most AI forward after product and engineering.

CJ Gustafson (0:12)

It's a hot take, I like it.

Ali Hussain (0:13)

For lack of a better word, I think of a headless agent as one that does not have a leash on it. You want to at least have an electric fence if you have a nice yard with your dog outside. But ultimately, you need a really good knowledge graph around all of your vendors. I actually put employees in there because it is, if not your biggest, your closest to largest cost center, and then your customers. There's a lot of open questions. Like there's parts of our jobs where AI has made an email or a certain level of insight or maybe the prep for today's call a little bit easier. Now it's just increased the quantum of output we have to put out. And there's a lot of things that still require a lot of human thought.

CJ Gustafson (0:50)

Is this thing on?

Ali Hussain (0:54)

Yesterday's price is not today's price.

CJ Gustafson (1:05)

Me and you were having dinner earlier this week and I was saying, hey, you get texts all the time from CFOs. Are they just asking you like, explain how your product works with usage-based pricing or this and that. And you hit me with a zinger. You said that a lot of them are actually asking about the org design first. That caught me off guard.

Ali Hussain (1:23)

Yeah, and look, I think my team does a better job talking about our product, but I think what's most curious for most CFOs is they're like, hey, Ali, you get to be on like six or seven chats with CFOs every day. What's top of mind for them? And beyond the technology and pricing and costs and all the standard things that have now become inevitable in the market, I think a lot of the financiers I spent a lot of time with have just a lot of experience and what they've been most challenged by now is, what does the new order look like? That is tooling, but a lot of it's just the type of people you hire. I think that is probably the top conversation I have with my deeper relationships I have with the different finance leaders that either are on tabs or who are prospecting with. And I think there's a couple of things driving that. One is just there's a lot of pressure from their boards and their management teams to just rethink the type of people you hire.

And often, finance has to be the most selfless when it comes to being a little bit leaner. The second is, I actually think finance is the most AI forward after product and engineering.

CJ Gustafson (2:26)

It's a hot take, I like it.

Ali Hussain (2:28)

We see it in the data in terms of the adoption of tools like tabs, but also on top of that, when MCP came out in the second half of last year, the way I found out about it was not from talking to my own teams in non-finance or engineering or in the news. Early signals that this was going to be a catalyst in the market was from CFOs controllers who adopted MCP into something like Claude faster than anything I've ever seen in my life. I think they are deeply thinking about org design right now. I think there are some must haves, like I don't think anyone is saying I don't need a controller anymore, or a very thoughtful FPMA or strategic finance lead.

But I think what they're saying is, after that, where can I get just a really AI-pilled team member that can allow us to keep most of the team strategic, but then really forward looking on the latest technology, using LLMs, and just figuring out how the rest of the team does more with less. And so I think that's been the top conversation, is a lot of them know directly the type of person they must have, but it's the added hire that would have otherwise created a bunch of people under these roles. I think it's the biggest question of what that looks like.

CJ Gustafson (3:44)

So I do these finance tech stack reports, and last year I was saying that finance had not had its ChatGPT moment yet, in the same way that call it support had already had with a Dekagon or something like that. And same thing like for engineering, having a cursor or a codex. I think MCP was the equivalent of finance and accounting's ChatGPT moment, because now you could query using language, all these numbers from disparate sources that you couldn't before.