In February 2026, the Technology and Services Industry Association published its annual customer success report. The findings are direct and, for many CS professionals, probably uncomfortable.
The core argument is this: CS teams are no longer being judged on customer sentiment. They’re being judged on financial indicators. The report builds this case around a framework called AI Economics, which examines how AI is disrupting traditional SaaS pricing models and forcing customer success teams to rethink how they operate, what they measure, and how they justify their existence.
The Economics of the Full Report: Customer Success Has Fundamentally Changed
The math behind customer growth has shifted. Acquiring new customers costs more than ever, which means retention is not simply a CS team metric. It’s a primary lever for business profitability.
That shift puts pressure on a pricing model that wasn’t built for this moment. Traditional SaaS revenue was built around seat expansion—more users meant more revenue. As AI reduces the need for headcount, those seat-based models start generating less revenue by design. The irony is built in.
CS teams now sit directly at the center of that transition. Their job is to ensure that AI-backed products deliver outcomes measurable enough to justify new pricing models. When that ROI story can’t be clearly told, the consequences are predictable: CS budgets are questioned, teams are downsized, and the function is demoted back to a support layer.
The Data Problem Nobody Wants to Talk About
Most CS conversations about AI focus on the wrong obstacle. The report emphasizes that messy data isn’t the main obstacle to effective AI in 2026. Modern AI tools can work with imperfect information reasonably well. The real problem is siloed data.
In most organizations, sales owns the CRM, support owns the ticketing system, CS owns success plans, and product owns usage data. Those systems aren’t talking to each other in any meaningful way. Then, when an AI tool tries to generate a prediction or flag a churn risk, it’s not working with the full picture.
This results in inaccurate predictions, undetected risks, and engagement that feels generic. Personalization requires context that the system simply doesn’t have. According to the report, the ability to unify customer data is now one of the strongest predictors of renewal performance going into the back half of 2026.
What the Numbers Actually Show
The data in this report is worth sitting with for a moment.
80% of CS teams cannot quantify the savings generated by their own CS technology. 57% of CS professionals don’t measure ROI for generative AI tools they’re already using and paying for. Those two numbers alone explain much of why CS budgets are under pressure.
On the other side of that gap, the performance difference is significant. Organizations with formal value realization capabilities achieve a 7-point higher NRR than those without. Best-in-class firms using guided digital customer journeys report a 30% increase in NRR. Variable CSM compensation is increasingly tied to NRR and lead generation, now ranging between 20-30% of total pay.
For Jarrod Haneline, these numbers reflect something he sees playing out in real time. The gap between CS teams that track and communicate measurable outputs and those that don’t isn’t closing. It’s widening.
Three Things CS Teams Must Do Now
The report doesn’t frame its recommendations as suggestions. It identifies three imperatives.
The first is fixing the data foundation. Data quality and system integration issues need to be resolved for AI to deliver the accurate predictions and customized engagement that CS teams are being asked to produce. There’s no workaround for this one.
The second is reskilling for strategy. CSMs need real investment in data literacy, strategic advisory capabilities, and complex problem-solving. Building strong client connections still matters, but relationship-building alone no longer meets the bar.
The third is challenging per-user pricing. As AI reduces headcount and seat-based revenue declines, outcome- and value-based monetization models become necessary. CS teams are positioned to drive that conversation because they’re closest to the data on what clients actually achieve.
The Role Is Changing. The Question Is Whether Teams Are Ready.
The report’s conclusion leaves little room for interpretation. The CSM role is shifting from relationship manager to value manager, and that shift is happening now, not on some future timeline.
Jarrod Haneline’s work at Pest Share reflects that transition exactly. Coordinating client outcomes, tracking measurable results, and operating within a platform built on automation and transparency—that’s the day-to-day reality the TSIA report describes. It’s not theoretical.
The CS teams that will struggle in 2026 are the ones still measuring success by activity: calls made, emails sent, check-ins completed. The ones that pull ahead are making the harder investments in data infrastructure, skills development, and the pricing conversations the TSIA report identifies as no longer optional.
The profession isn’t shrinking. It’s being held to a higher standard. That’s a different thing entirely.
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