If you’ve spent any time on LinkedIn recently, you’ll have seen no shortage of posts about AI and Customer Success.
Some predict the end of the Customer Success Manager. Others claim AI will transform everything overnight. Most fall somewhere in between.
The problem is that there’s very little agreement on what’s actually happening.
After dozens of conversations with Customer Success leaders, SaaS executives and founders over the past year, I’ve noticed something interesting.
We’re all talking about AI.
We’re just not talking about the same thing.
Some teams are experimenting with meeting summaries and email drafts.
Others are building AI into customer workflows.
Some are measuring productivity.
Others are trying to rethink their entire post-sales operating model.
These are completely different conversations.
What seems clear is that AI has moved beyond experimentation. It is becoming part of day-to-day Customer Success.
The more interesting questions are no longer whether teams should use AI, but how they should use it and what impact it is really having.
From where I sit, a few themes keep appearing.
- AI is removing repetitive work but increasing expectations.
- It is exposing weak processes rather than fixing them.
- It is making commercial judgement more valuable, not less.
- It is forcing Customer Success leaders to rethink what great performance actually looks like.
I don’t think the biggest story is that AI is replacing Customer Success.
I think it’s changing what good Customer Success looks like.
That’s a much more interesting conversation.
Over the coming months, I’m going to capture the patterns I’m seeing through my advisory work, podcast conversations and discussions with Customer Success leaders.
The goal is simple.
To build a practical picture of how AI is really changing Customer Success, separating the hype from what’s happening in real SaaS organisations.
I’d love to hear what you’re seeing too.
What’s been the biggest change in your Customer Success team since AI became part of everyday work?