AI

AI x CRM: A Practical Look at What’s Out There

Jessica Jantzen
April 01, 2025

Let’s be honest, AI is everywhere right now. And in CRM, it’s not just hype. It’s doing the grunt work, helping us get smarter with segmentation, faster with content, and more relevant with every message we send.

I spent time digging into five well-known CRM tools to see what AI features they actually offer. Then I mapped out the real use cases in tables you’ll find below. It’s not claiming to be “complete” (what even is?), but it’s a solid overview of where AI already plugs into our day-to-day work.

You’ll find everything from campaign management to smart customer interactions to prediction models. Real tasks, real outputs.

If something’s missing or you’ve got a better example, tell me. This is built for the community and can only get better with your input.

👇 Here’s what AI is already doing in CRM (not “someday,” but today).

Campaign Management
Segmentation	AI suggests audiences based on your desired outcome.
Sender Reputation Repair	AI improves sender reputation and deliverability by automatically excluding unengaged profiles.
Send Time Optimization	AI picks the best time to send emails to each recipient.
Subject Line & Copy Generation	AI tools like GPT create personalised, high-performing copy (based on brand guidelines).
Image Generation	AI generates images to match campaign content.
Smart Frequency	AI dynamically adjusts how often emails are sent, based on each customer’s interaction history.
Multivariate Testing	AI tests different content, timing, and audience mixes to find the best-performing combination.
Channel Mix Optimization	AI selects the ideal communication channel (email, SMS, push) for each customer.
Journey Assist	AI designs journeys based on your input or prompts.
Journey Orchestration	AI tailors the next message or action based on customer behaviour.
Auto-Monitor	AI tracks campaign performance in real time, spots anomalies, and raises alerts.

Predictions
Churn Prediction	Identifies customers likely to churn and triggers retention actions.
LTV Prediction	Forecasts a customer’s lifetime value to help prioritise high-potential users.
Purchase Propensity	Predicts who’s likely to buy next—and what they’re likely to purchase.

AI-Powered Customer Interaction
Buyer Assistance During Session	Acts as a personalised shopping guide, proactively answering questions and reducing return rates.
Passive Shopper Engagement	Starts contextual conversations to help passive users explore products—driving discovery and conversions.
Product Recommendations	Suggests items based on behaviour, trends, or related purchases—on-site or post-purchase.
Similar Products	Recommends visually similar items based on uploaded images.
Smart Interventions	Prevents cart abandonment by addressing in-session doubts or concerns.
Content Personalization	Dynamically curates content blocks within CRM campaigns.
Contextual personalisation	Picks the best offer or message for each customer, balancing value and business goals.

Before You Go…

This overview isn’t theory. It’s based on what tools are already capable of.

The goal? Make it easier for CRM folks (like you and me) to see what’s possible and what’s worth trying. Whether you’re running campaigns, managing retention, or trying to squeeze more out of your data, AI’s not a “maybe” anymore. It’s quickly becoming part of the process.

So what’s missing? What are you testing that isn’t here yet? Hit me up or drop a comment below. Let’s keep this list useful, together.

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