AI in Post-Sales: Are we getting it all wrong?

I want to tell you about a conversation I had with a Chief Revenue Officer a few weeks ago.

He's smart. His team is experienced. The company had just rolled out an AI tool that promised to "transform" the way they managed accounts. It had been three months. Nothing had changed. If anything, the team was more frustrated than before — because now they had one more dashboard to check, one more thing to update, one more system that didn't talk to the others.

"It's not that the tool is bad," he told me. "It's that I don't even know what the key problem is that I'm solving."

I've been hearing versions of that conversation a lot lately. And I think it tells us something important about why AI in Customer Success isn't moving the needle the way it should.

We keep buying tools before we've asked the fundamental question.

There's a headline doing the rounds right now. Study after study shows that AI adoption in B2B SaaS post-sales functions isn't delivering. Teams are overwhelmed. Leaders are confused. Budgets are being spent and nothing is fundamentally different. The promises were big. The reality is underwhelming.

I don't think that's because AI isn't powerful enough. I think it's because we're implementing it back to front.

We go tool-first. We hear about something that can summarise call notes or generate renewal emails, and we buy it. We layer it on top of a team that's already stretched and a process that was already broken. And then we wonder why it doesn't stick.

The question we should be asking isn't "which AI tool should we buy?" It's a much more human question first: what are your CSMs actually doing every week — and which of those things genuinely requires a human being to do it?

Because if you sit down and really audit that, what you find is uncomfortable. A significant portion of a typical CSM's week — I'd say more than half — is consumed by tasks that have absolutely nothing to do with why you hired them. Preparing for calls by piecing together information from four different systems. Writing up what was said after the call. Updating CRM fields that should update themselves. Drafting follow-up emails that look almost identical to the one from last week. Trying to remember, before a renewal conversation, what was actually agreed three months ago.

These are tasks we can outsource to AI.

Here's what I believe, and what I'm going to start putting into practice more intentionally with my clients: AI doesn't replace the CSM. It protects the one thing the CSM is irreplaceable for — the human moment.

Think about the highest-value thing a great CSM does. It's not filling in a health score. It's sitting with a customer — on a call, in a QBR, in a difficult renewal conversation — and being so genuinely present that the customer feels understood. They read the room. They sense the shift in tone when the champion's engagement drops. They know instinctively when to push and when to listen. They make the customer feel seen before they try to solve anything.

That moment is where trust is built. That moment is what drives GRR and NRR. And that moment requires a human.

The problem is that too many CSMs arrive at that moment exhausted, under-prepared, and already carrying the weight of everything they haven't done yet. The Value Gap isn't just about what we deliver to customers — it's about what we take away from the people responsible for delivering it.

AI doesn't remove the human moment. It clears the runway so the human moment can actually land.

So here's how I'm starting to think about it. Not as a strategy. More as a working hypothesis I'm testing.

I think about it in terms of two points in time: before the conversation and after the conversation. Everything in between — the actual call, the relationship, the commercial movement — belongs to the human. Everything outside of it is fair game for automation and intelligence.

Before the conversation, the idea is simple. The CSM shouldn't have to scramble to prepare. A few hours before a meeting, imagine if an AI agent had already done the work — scanned the previous transcripts, looked at the usage data, checked any open tickets, glanced at the customer's LinkedIn and recent company news, pulled anything relevant about the stage they're at commercially. And then distilled all of that into something useful. Not a report. Not a forty-slide deck. A brief. Structured around the SPICED or MEDDPPICC methodology, so you understand the situation, the pain, where this conversation could lead, and what the call to action is. The CSM walks in genuinely prepared — not performing preparation, actually prepared.

After the conversation, the transcript does the work. The CRM updates itself. A follow-up email is drafted and surfaced for a quick review — not sent blindly, but ready to personalise and approve in two minutes rather than fifteen. Next steps are captured. The health score refreshes based on what was actually said and committed to — not based on whether someone remembered to update a field before the end of the day.

And here's what I think gets missed in most of these conversations: all of that feeds upward. Every post-call automation becomes an input to a dashboard that gives managers and C-suite a near real-time picture of where GRR and NRR actually stand. Not a quarterly forecast built from gut feel and spreadsheets. An actual signal, updated after every customer conversation. That's what changes the board conversation from "we think churn is around X" to "here's where we are right now, and here's what we're going to do about it."

I want to be clear about something: this isn't a blueprint I'm selling. I'm not standing here telling you I've built this perfectly and it works flawlessly. I'm telling you this is the direction I believe is worth moving in — and the lens I'm using to think about it with my own clients.

The companies I see getting this wrong are the ones treating AI as a headcount play. If AI does the admin, we need fewer CSMs. That's short-term thinking dressed as efficiency, and it will cost them.

The companies getting it right — or at least moving in the right direction — are the ones asking how they can use AI to increase the quality of human attention without increasing cost. Same team. Dramatically more capacity for the conversations that drive retention and expansion. The CSMs aren't less important in this model. They're more important — because the only thing they're left doing is the thing that matters most.

I'm going to keep building on this thinking. It won't be perfect. Some of it will need to be adapted depending on the size of the team, the maturity of the function, the tools already in place. But the starting point is always the same: audit the tasks, protect the human moment, and let everything else run itself.

That's the shift. And I think it's worth trying.

If you want to understand where your CS function stands before you make any decisions about tooling or AI, take the CS Maturity Scorecard at 2026ready.scoreapp.com. Ten minutes, and you'll know exactly where your biggest gaps and opportunities are.