When I tried to grow our sales team, it didn’t go well at first. But after we started using AI CRMs the right way, our pipeline tripled without hiring more people. Here’s exactly what we did.
The Framework That Actually Works
Here is a simple framework for evaluating AI CRMs. It's not complicated, but it requires discipline.
Step 1: the best solutions are often the simplest ones
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the data tells a different story than your gut
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get AI CRMs right treat it as an ongoing process, not a one-time project.
The Reality Nobody Talks About
A lot of the advice on AI CRMs rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that you should focus on one thing and do it exceptionally well. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that the data tells a different story than your gut. Once they make the switch, everything changes.
Real Talk: What Actually Matters
Here is what actually matters in AI CRMs.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on AI CRMs. Many fail because they moved too slowly.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. It sounds obvious, but many founders make decisions about AI CRMs in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around revenue intelligence, AI CRM, deal scoring AI, AI sales tools that I've been thinking about a lot lately.
The Bottom Line
None of this is rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at AI CRMs aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
Companies that take AI CRMs seriously tend to pull ahead of the ones that don't.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
Q:How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.