3 things to fix in your CRM to leverage AI more effectively

Good Morning {{first_name}}!

It’s Monday - and that means it’s time for your CRM Dispatch - an issue where we talk about CRM issues that often cause frustration, anger, and blame.

So, let’s start this Monday morning by blaming AI. Everyone is blaming the AI.

The sequences, the tools, the automations - none of it is working the way the demos promised. But why would that be? Hmm…well, it’s your data.

Let’s dive in.

Bad data costs U.S. businesses an average of $12.9 to $15 million per year in wasted marketing spend, lost opportunities, and operational drag. And in 2026, AI does not fix that problem. In fact, it probably makes it worse.

Sit with that for a second. People fully trust AI because ChatGPT once gave them a good enough answer, so they think implementing AI into a CRM will give them a “good enough answer” to make business decisions.

Gulp.

When something doesn’t work, marketers always tend to lean toward rewriting the copy, tweaking landing pages, reworking segments, and A/B testing. But in this instance, SMB teams are troubleshooting the wrong thing.

The real issue is usually upstream. Lifecycle stages that are inconsistently defined, contact records that have never been cleaned, and event data that does not actually match what the customer did. Despite the “hype” around AI, CRM features do not fix broken data ownership. The foundation of how the data is handled is the core issue.

The problem usually spans across three areas.

First, lifecycle stage definitions: if your team is assigning lifecycle stages without a shared definition of what each one means, your segmentation is meaningless.

Second, event taxonomy: if the events firing in your CRM do not consistently reflect what contacts are actually doing, your behavioural triggers are firing on noise. Look at integrations, email activity, website views, meetings booked, etc.

Third, CRM sync: if your marketing tool and your CRM are out of sync, your automations are running on a stale snapshot of your customer. This includes third-party integration syncs where data is passed back and forth.

You don't have to scroll every AI thread, track every new tool, or watch every demo. 

The Rundown AI breaks it all down for you — the latest AI news, tools, and tutorials in one free 5-minute email every morning. 

Trusted by 2M+ professionals at Apple, Google, and NASA.

Sign up to start learning.

This week, I want you to pick one of the three above and go on an investigation journey.

Pick one: lifecycle stages, event data, or CRM sync.

Open your CRM and ask a simple question: Does this data reflect what actually happened with this contact? Is that person a lead or a customer? Do the event data actually reflect the communications or activities the person has had with the company? And is all third-party data syncing over?

If the answer is "I am not sure," that is your answer. Start there. You do not need to overhaul everything. You need to know which layer is lying to you first.

This week, the Lifecycle Audit Checklist went into production. That should hit this newsletter in a few weeks!

Stay tuned.

TL;DR

If your AI is failing you, it’s probably not AI. And it’s probably not that the sequence is broken or that the message is wrong. It’s most likely the foundation from which the AI is pulling. Every retention and re-engagement play you run is only as strong as the data it runs on. Fix the layer underneath before you change the one everyone can see.