Retention before and after the AI revolution

AI is changing the game in many industries, but is it really the answer to all of our problems in Customer Success?
Customer Success and Account Management has gotten SO much harder the last few years. There’s been a lot of market pressure, an increase in competition and a slow-down in net-new sales meaning everyone is looking to post-sales and customer growth teams to increase revenue. Meanwhile budgets get tighter, teams are getting smaller and there’s a huge drive for efficiency and profitability. 

All of this has created a boiling pot for Customer Success - everyone’s focused on higher outputs and more revenue from existing customers, with bigger books of business than ever before per CSM. 

And then - AI enters the market.

Suddenly we can see insight from our masses of data, we can automate repetitive CS tasks and we can generate pretty much anything with a click of a button. It's powerful, and it’s an exciting next step in our industry.

But here’s the thing: AI alone isn’t the answer.

It’s only useful if it’s pointed at the right problems, with the right context.

It’s not enough to just “use AI” to be more efficient. We STILL have to ensure that what we’re doing with AI is relevant and has good customer context. Otherwise we’re being “more efficient” in the wrong places.

This ability to generate anything at the click of a button has AI creating emails for customers for us, automatically creating playbooks we can execute on for our customers. 

But does it really have all the context it needs?  

The last thing we want is our CS teams generating an AI playbook that’s not specific to what is actually going to help that customer, or what’s been proven to help customers before. 

It’s great that it’s quick and efficient, but what’s the point in efficiency if it’s not effective? 

And in this market, we just can’t afford to get this wrong. 

So what AI needs is context. And for me, you’re not going to get better context than ML, or Machine Learning. Also AI - but not in the way that most people think of AI when they hear it today. 

Machine learning is what gives your data its superpower:

context. Unlike traditional AI that generates content or automates tasks, machine learning is focused on developing algorithms that can learn from data and generalise to new, unseen scenarios. It’s what allows systems to detect patterns, predict outcomes, and surface what’s likely to work, based on what’s worked before.

In the world of Customer Success, ML is the brain behind the scenes telling the LLMs: “Here’s what actually matters for this customer.” It transforms AI from a content engine into a decision-making companion.

So yes, I do think AI is going to be insanely powerful for CS, but really it’s at it’s most powerful when you’re including the data and the ML.