This isn’t an anti-AI post. I’m not here to fight the robots.
In fact, AI is a lot like my evening chai, it keeps me sane, focused, and sometimes even makes me look more organized than I actually am. But add too much sugar, and the whole thing becomes… chaos.
That’s what’s happening in many domains including Customer Success today.
AI Is Brilliant… Until We Force It Into Everything
AI is already solving half our CS headaches: drafting QBRs, spotting sentiment shifts, sending renewal nudges, pulling adoption data, and surfacing risks before customers even notice them.
But somewhere along the way, AI turned into corporate Ozempic “adopt it or you’ll be left behind.”
And because of that FOMO, we’ve started forcing AI into places where it simply doesn’t belong.
We don’t need AI to solve 2+2.
We don’t need a summary bot for every document, somethings deserve to be read end-to-end.
We don’t need agents for every micro-workflow.
Not everything needs an agent.
Sometimes simple logic works beautifully. Sometimes the human brain works better.
The Real CS Skill? Building Your Judgment Muscle
Every other day, a podcast or post promises a magical AI agent that “reduces churn automatically.”
But the truth is far simpler: AI gives you signals. Humans decide what to do next.
AI can tell you if the water is hot or cold.
Only you can decide whether to make chai or take a bath.
And here’s the part people skip: You can only make smart decisions when you understand how those signals are generated, the logic, rules, and inputs behind them. Experienced CSMs are actually the best people to define that logic, because they understand the customer reality that algorithms often miss.
Not Everything Needs an Agent
A mature CS org asks three simple questions before building automation:
- Is this something simple logic can handle?
Example: usage drop + no login for 14 days, customer is at-risk.
No agent required. - Will this directly improve the customer’s journey?
If the answer is no, it’s probably noise. - Will this make a CSM’s daily work meaningfully easier?
If it saves 2 minutes a week, skip it.
If it removes 2 hours of repetitive tasks, automate it.
The goal is not to “AI everything.”
The goal is to choose wisely where AI actually moves the needle.
Best Practices for CS Professionals in an AI-Heavy World
To stay effective (and sane), the best CSMs follow a few timeless principles:
- Let AI handle the repetitive work
(notes, summarization, usage extraction, renewal reminders). - Use rules-based logic when the workflow is predictable.
Not every insight needs a model. - Build fewer, smarter agents not a clutter of micro-bots.
- Maintain strong human skills:
empathy, escalation timing, customer narratives, risk interpretation. - Always question: “Do we even need AI for this?”
Because at the end of the day, AI may help you get the signals faster but your judgment muscle is what turns those signals into real outcomes.
AI can accelerate you, but your judgment is what creates real outcomes.
PS:
If AI ever does start doing chai quality checks, I’ll be the first one in line. Until then… let’s use it wisely.
Thanks for reading!
