I just spent four hours in a room with 60 customer success leaders at Planhat North.

The topic was AI (obviously).

And I walked out with a completely different read on where the CS community actually is — not where we say we are.

Here's what I took away.

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First, the thing that surprised me most: you aren't as far behind as you think.

The majority of CS leaders in that room are still trying to assess where they stand. Figuring out what they have, what gaps exist, and what the team is actually capable of.

That's not failure. That's reality.

But here's the thing — the best teams aren't waiting on the perfect assessment. They've moved with speed. They've picked an MVP, shipped a V1, and started learning from it.

The gap isn't capability. It's momentum.

The leaders who are winning aren't necessarily smarter or better resourced. They just stopped assessing and started doing.

Here's a non-exhaustive list of the real, practical plays I heard from the room:

Starting with a team AI assessment. Before you can move, you have to know where you are. What tools does your team use today? Where are the skill gaps? What's your AI fluency baseline? The assessment isn't the finish line — it's the starting line.

CEO and ELT demonstrating AI behaviors. This one matters more than most leaders think. You can't mandate adoption from the top and then not model it yourself. If your leadership team isn't visibly using AI in their daily work, your frontline team is watching — and taking notes.

Blocking time for testing and playing. Not as a one-time training event. As a recurring, protected part of the week. Teams that are figuring this out fastest have intentional space to experiment — not just another item on the to-do list.

Building process maps to help teams understand what's happening under the hood and where automation or AI could make a difference. Making the AI workflow visible so people aren't just using tools — they're understanding the system.

Closing knowledge base gaps automatically — pulling from call transcripts, emails, and tickets to identify where documentation is missing and filling it in before the next rep has to search for the same answer.

Technical CSMs paired with Account Managers. Technical CSMs own the product and technical depth. AMs own the commercial relationship. The ratio and structure is becoming a real conversation as AI changes what a CSM actually does.

One thread that kept coming up: Success Engineer. Is this the future of the CSM?

The idea is that as AI handles more of the reactive and administrative work, the value of a CSM shifts toward technical depth — orchestrating systems, understanding integrations, and serving as the connective tissue between product and customer outcomes.

Account management handles the commercial relationship. The Success Engineer handles everything technical.

Whether that model plays out exactly that way, I don't know. But the underlying tension it surfaces is real: the role is changing, and most teams haven't updated their job architecture to reflect that.

1. Tooling overload is still a blocker.

This one came up over and over. Too many tools. AI is embedded in too many places. Confusion about what to use and when. The irony is that the tools meant to make teams faster are creating decision fatigue. The answer isn't more tools — it's a clear, opinionated stack with intentional rollout.

2. AI curious isn't enough anymore.

Being curious about AI is the floor, not the ceiling. What separates teams now isn't awareness — it's embeddedness. AI has to be in the workflow every time you're doing something, not just when it's convenient. The teams making progress have stopped treating AI as a tool they sometimes use and started treating it as a layer that's always on.

3. Treat CS like a product.

This was the framing I found most useful. Use PRDs. Think about CS as something you're building and iterating on, not just a function you're running. When you imagine CS as a product, you start asking different questions: What's the MVP? Who's the user? What does v2 look like? It forces a precision that "let's improve our CS motion" just doesn't.

The best teams are already taking this further — building and deploying skills directly in Claude that drive alignment, consistency, and best practices across the organization. They're enabling their teams and their agents through markdown files. Which means documentation isn't a back-burner task anymore. It's how you ship.

The conversation in that room wasn't about whether AI matters for CS. Everyone already knows it does.

The conversation was about how fast you are moving, and whether your leadership is actually behaving like this is real.

The gap in Customer Success right now is momentum.

Start moving.

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