Are CEOs Delusional About AI?, Using AI for Revenue Planning, Vibe Coding a CRM?
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What is the main topic discussed in this episode?
Hi everyone, Charlie and Chrissy here with the Cookin' Up Go to Market podcast. So we have a very special guest today, Alison from our team who leads our Power Solutions Architecture and Analytics practice. I think every time we've had Alison Allison on, it's been one of our best performing podcasts, right? With a lot of good stuff around analytics. I probably the one person that knows the most about attribution, sales force, so many different things. Um And we're gonna have a big part of the topic today talking about revenue planning and AI and how we've been using AI to prepare for revenue planning, get the most out of revenue planning and help our clients plan. Um, but before we get into that, we've got a few other topics.
So the first one we're gonna start with. So Claire is gonna throw this up on the screen when when we get there.
Are CEOs really delusional about AI or just missing the implementation details?
Um But this is a this is a a tweet by Aaron Levy from from Box. I'm gonna read it out for anyone that isn't um watching and then I wanna get the team's reaction here. So CEOs are uniquely prone to AI psychosis because they're sufficiently distant from the last mile of work that still has to happen to generate most value with AI. So when they Play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents. Look, I've made this awesome product prototype, yes, but you didn't have to review the code before it went into production and fix a bunch of issues. Look, I generated a contract, yes, but you didn't verify all the terms before it goes out to the counterparty and didn't have to wire up all the past contracts to work with.
The best thing you can do as a CEO is to use AI a ton to figure out the real implications for agents of the enterprise and come out the other side with an appreciation for both the upside and the real work that goes into them. So my question for Alison. Do Chrissy
and I suffer from AI psychosis? Tell us the truth. But you can you can avoid that comment
uh that question if you want. And what do you think? Do you agree with this? Where where do you see value in this statement? And and do you agree? What do you think?
Do, but I feel like Um my opinion on on that is similar to opinions I've had in the past, as especially when it comes to operations in general, that often leadership doesn't kinda understand all the work that goes into what we do in operations. Um Especially when it comes to like as we'll get into later, like things like revenue planning where your data has to be in such a good place to really be able to effectively build a model, um, but also um your data has to be in such a good place in order for AI to work well with it. So I think there's like a probably a misconception in a lot in a lot of leaders' eyes that their data is clean enough to to be able to leverage AI the way they want it to and that there's not a lot of work that's still gonna have to go into that
first. That's a good point actually. I hadn't even thought about how it it is a continuation of a an old an old problem that we've always had to deal with and off. Do you Do you agree, Chrissy? 'Cause it's kind of sounds like Is it just like an expectations gone up problem, but actually the reality on the ground floor has always been difficult, or is it both Reality is even harder to achieve good results now with AI makes it even more complicated and expectations have gone up. Like, what do you think? has changed the most or if anything in this dynamic.
People like now leaders are are using the technology and they're getting this kind of false perception on like what's possible. It's like I talked about it multiple times on this podcast. I've said it multiple times. It's like a little bit of information is a dangerous thing. And I think like that's what they have in their purview. It's like on operations now. It's It's a little bit like before they didn't actually know anything about operations. They just knew it was hard and they knew it was important Yeah, they
weren't logging into the marketing automation platform and and building stuff were they?
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Chapters
6 chapters
1
What is the main topic discussed in this episode?
0:00–0:50
2
Are CEOs really delusional about AI or just missing the implementation details?
0:50–22:04
3
How can AI be used to build and accelerate revenue‑planning models?
22:04–32:24
4
What data‑quality and cleaning steps are required before AI can help with forecasting?
32:24–41:19
5
How does Claude/Claude Code automate spreadsheet creation and formula generation?
41:19–50:00
6
What is a “slippage rate” and why does it matter for long sales cycles?
50:00–57:17