AI Is Putting Every Renewal Into Play. The CS Teams That Understand Why Will Keep the Business.

Jason Lemkin posted on July 28 that AI is driving up churn across the board. Products have not gotten worse. Vendors have not started failing their customers. What changed is that customers who used to renew without thinking about it are now looking around.

Three things are pushing them to look: budget earmarked for AI that gives them a reason to shop, corporate mandates to adopt AI and cut costs, and plain curiosity. In Lemkin's words: "A lot more deals now are being put into play simply because customers that aren't deeply unhappy are, for the first time in years, looking to see what AI can bring to the table."

The Konur Consulting take: Inertia was doing a lot of retention work that we were crediting to customer success. AI took it away. What matters now is knowing why a customer is re-evaluating and what they find when they do. A healthy satisfaction score will not tell you either one.

The inertia renewal and why it is over

For most of the 2010s and early 2020s, SaaS renewal rates rested on switching costs that had nothing to do with whether customers liked the product. Moving the data, retraining the team, rebuilding the integrations, absorbing the risk that the whole change goes sideways. Add it up and the mediocre incumbent won by default.

AI is cutting those costs from two directions at once.

The first is build cost. AI-assisted development makes it cheaper to stand up an alternative, and as we covered in the Starbucks post, the internal build option is now credible for workflow problems that used to require a vendor. Most renewal assumptions have not been repriced for how fast that cost is falling.

The second is quality. In narrow categories, AI-native alternatives now beat the incumbent on the dimensions the customer cares about most, often at a lower per-unit cost. Switching still costs something. The prize on the other side just got bigger.

So the customer who used to renew without looking is looking. Some of them are finding reasons to switch that did not exist two years ago.

The boomerang signal that changes the playbook

The part of Lemkin's post that got less attention is what happens after the switch.

Boomerangs are already happening. Customers who churned to AI alternatives six to ten months ago are coming back, because the alternative delivered less than the pitch and the incumbent's institutional knowledge and integration depth only became visible once it was gone. The switch also cost more than they had budgeted.

The standard response to AI-driven churn risk is to fight harder. Accelerate the QBR, bring in an executive sponsor, sharpen the ROI story. That is all correct, and most playbooks stop there. The boomerang data adds a second motion: how you treat the customers who leave decides whether they come back.

Burn a customer on the way out with hostility or punitive contract enforcement and you have closed the door. Handle the exit well and keep the relationship warm, and you are in position to win the account back inside twelve months when the AI alternative underdelivers.

Treat that as a real retention lever rather than a consolation prize. Churn rates in this market are going to run higher than they did in 2022. Some of that churn is temporary, and having a motion to recover it matters as much as the work you do to prevent it.

What is driving the AI evaluation in your accounts

The right intervention depends on why the customer is looking. Three patterns show up.

Innovation budget evaluations start with a CTO or product team that has money set aside for AI tooling and is scanning the whole stack for what can be consolidated or replaced. They tend to be broad, touching several vendors at once, and driven by budget logic rather than dissatisfaction with any one product. Your job is to be the AI layer that advances their agenda rather than a line item they are pricing for replacement.

Cost-reduction evaluations come from a CFO or a board that has mandated a software cost review. These are hunting specifically for per-seat pricing that can be swapped for something cheaper: an AI-native tool, an internal build, a consolidated platform. Here the switching cost argument is the argument. What does it actually cost to migrate, retrain, and rebuild the integrations, and does that exceed the license savings?

Curiosity evaluations are the ones I would worry about, because nothing in your health score will show them to you. A champion read about an AI-native alternative, asked for a demo, and is quietly running an evaluation you will hear about at renewal. The only reliable counter is to ask. Finding out about a 90-day-old evaluation on the day your renewal conversation starts is the worst version of this.

What to do Monday

Add one question to every QBR and executive sponsor conversation this quarter: "Have you looked at any alternatives to [product] in the last six months? What did you find?" It will feel awkward the first few times you ask it. Ask it anyway. The answer tells you whether you are working an active evaluation or a satisfied customer, and those need different renewal motions.

Where an evaluation is already running, build the switching cost case before the customer finishes it. Nobody mid-evaluation has priced the full cost of leaving. Help them price it honestly rather than defensively. If your switching cost is genuinely high, the math works for you. If it is not, better to learn that now than in the renewal call.

Where churn looks likely anyway, spend the effort on offboarding. Make the exit clean, keep the relationship warm, make coming back easy. AI alternatives are still overpromising at scale, so the boomerang is a real recovery path, but only for vendors who earned it on the way out.

FAQ

How do I identify curiosity evaluations before they become renewal risks?

Two signals show up earlier than standard health score inputs. Executive sponsor engagement drops off while day-to-day usage stays flat, which usually means the champion is managing up toward a board conversation you cannot see. Inbound support tickets fall without any matching improvement in health score, which often means the customer is teaching themselves the product ahead of a demo with someone else.

Is the boomerang dynamic specific to certain SaaS categories?

Lemkin sees it across categories, anywhere AI vendors overpromised on timeline or capability. It is heaviest where AI-native entrants cluster: CRM, CS tooling, marketing automation, workflow automation. Those are also the categories where inertia renewal was most common, so the churn wave and the boomerang wave land in the same places.

Does handling churn gracefully mean accepting it passively?

No. You fight for the account until the decision is final, then you shift to a clean offboarding. The two are sequential. The failure mode is letting the retention fight spill into the offboarding and leaving the customer with a bad last impression.

The customers leaving over AI curiosity are not all gone for good. Some are coming back. The teams that earn the boomerang will recover accounts their competitors already wrote off.

Konur Consulting helps SaaS CS organizations build the proactive renewal motion and offboarding playbook needed in a market where AI is putting every renewal into play. Reach out at info@konurconsulting.com.

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Source - AI driving up churn: Jason Lemkin, "AI Is Driving Up Churn Across the Board - Because It Puts Every Renewal Into Play," SaaStr, July 28, 2026. saastr.com/ai-is-driving-up-churn-across-the-board-because-it-puts-every-renewal-into-play

Source - Boomerang observation: Lemkin, same post. "I'm already seeing a number go back a year out or less to their original vendor. Boomerangs are already happening where AI vendors overpromised 6-10 months ago."