Here’s a stat that stops you in your tracks: 72% of CS leaders say AI will be critical to their success by 2026 yet only 32% are running even a single live AI use case. It’s not just a tech gap. It’s a confidence gap. Teams believe in the promise of AI. They see the potential for personalization at scale. But day to day, most are stuck in pilot mode, wrestling with siloed data, manual workflows, and playbooks that don’t quite stretch far enough. That’s exactly why we created the 2025 Digital Customer Success Benchmark: to go beyond the hype and dig into what’s actually happening in the field. What’s working. What’s stalling. And how leading CS teams are starting to close the gap between vision and execution. Who’s Shaping Digital CS Today? We heard from CS leaders across the spectrum - especially those responsible for scaling strategies. With CS Ops leaders and VPs making up over half the group, it’s clear that both strategic and operational minds are driving the future of digital customer success.
AI in CS: Big Hopes, Slow Progress
The numbers tell a fascinating story about AI adoption in Customer Success. While nearly three-quarters of teams see AI as mission-critical for their future, the present reality is more sobering:
- Only 32% run even a single live AI use case
- Just 3% describe their AI deployment as "extensive"
- 27% cite data quality as their top barrier—outranking budget and skills combined
- Nearly half the market remains stuck in "exploring" or "piloting" mode
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Through the use of AI, we have reduced time to build and deliver quarterly renewals and churn reporting by 30+ hours, giving our renewals team more time to strategically engage, retain, and grow our customers | Jeremy Donaldson, a customer success leader at LifeLoop.
The leaders who break through aren't chasing chatbots, they're embedding AI into everyday workflows: auto-generating QBR summaries (19%), creating next-best actions (17%), and surfacing predictive churn flags (14%). But they only succeed after solving the fundamental data quality problem that trips up most AI initiatives.
If I could add one capability for 2025, I'd choose AI-driven journey orchestration, so every customer path feels handcrafted, not hardcoded. It's time our tools moved at the speed of customer change.
Reflects Alexandra Sagaydak, Chief Customer Officer at PeopleForce.
But AI Isn't the Only Confidence Gap
The AI adoption challenge is just one symptom of a broader execution problem plaguing Customer Success. While teams chase future AI capabilities, they're struggling with more fundamental challenges happening right now. Consider personalization: CS teams rate their capabilities 6.3 out of 10 on average, yet only 33% of companies deliver tailored journeys to more than half their customer base. Half the industry is confident they're nailing personalization, but only a third of customers ever feel it. This isn't about lazy teams or misaligned priorities. It's about the fundamental tension between what CS teams know they should deliver and what they can actually execute at scale.
The VIP Treatment Problem
Here's how the confidence gap actually plays out: Leaders optimize the top tier, white-glove onboarding, bespoke QBR decks, custom success plans, while the long tail survives on canned emails and hope. The math is unforgiving. Just 16% of teams believe their current personalization approach will work when their customer base doubles. We've built customer experience strategies that break under the weight of our own success.
If I could add one capability for 2025, I'd choose a unified personalization layer across all touchpoints, one that leverages AI to auto-adapt based on lifecycle stage, intent signals, and tech stack maturity | Zara Palevani, Director at Merkle.
Mid-market organizations feel this pinch most acutely. Fast growth meets thin headcount. Books of business too large for heroics, too small for full automation. The result? Teams excel at white-glove experiences for their top tier while the majority of customers get a fundamentally different experience.
Where the Hours Actually Disappear
Behind every ambitious AI plan and personalization goal sits a calendar stuffed with manual tasks. We found that 36% of teams cite CSM bandwidth as their biggest scaling blocker, outranking data silos (22%) and tooling gaps (18%).
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But where do those hours actually go? Three activities consume a third of the work week: onboarding check-ins (27%), follow-up emails (24%), and progress reporting (21%). We're not talking about high-value coaching conversations or expansion planning, we're talking about administrative overhead that keeps teams reactive.
"Since we implemented EverAfter, the feedback from customers has been amazing. They love having one place to access everything, and it's made communication so much easier. We've seen a real shift—customers are sending messages, commenting, and engaging more. We're definitely driving the behavior we want to see," shares Sara Arecco, Head of Customer Success at Antavo.
Early stage CSMs juggle 28 manual touches per week alongside just four automated ones. In mature organizations, those lines cross—manual touches drop to 12 while automation climbs to 18. This transformation doesn't happen by accident.
The Automation Evolution
Most CS teams have already tackled the "easy" wins—health scores, a handful of onboarding workflows, quarterly usage emails. It works, but only to a point. Our data reveals three signals that the next wave of automation is now within reach:
- Manual still carries the load. Even after years of tooling investment, 68% of organizations say day-to-day outreach is still driven from a CRM list or spreadsheet. That's not a failure; it's proof the first wave created demand for something better.
- Dynamic segmentation is the tipping point. Only 27% route customers into persona or lifecycle-specific playbooks today. Yet scaling teams use twice as many automated workflows precisely because segmentation fires the right task set, every time.I
- ntegration turns workflows into momentum. Half the respondents juggle 3-5 CS tools daily. The leaders aren't adding more apps—they're unifying into a single workspace, cutting manual tasks per CSM from 28 to 12 each week.
Recently we're investing in tools such as EverAfter… We're embedding them in our customer interface and driving customer traffic there first and foremost | Joshua K. Pritchett, Director of Scaled Customer Success at Okta.
Where the Smart Money Goes
We asked CS leaders one simple question: "If you had to place your next big chip, where would it land?" Their answers clustered around four investments that read like a playbook for digital-first customer success:
- Predictive insights - Teams want intelligence that whispers what's coming, not dashboards that report what happened
- Unified customer data - The foundation that makes AI and personalization possible
- Workflow automation - Optimizing existing playbooks, not replacing them
- Self-service success hubs - Customers need a home for goals, metrics, and resources
The pattern reveals important nuances when mapped against organizational maturity:
- Foundational teams prioritize easy content and templates—they're still building the basics
- Defined organizations make workflow automation their #1 pick (58%)—they have playbooks but need bandwidth
- Scaling teams push hard on self-service engagement (50%)—the long tail now outnumbers the CSM roster ten to one
"The personalization tactic that moved the needle most for us was account intelligence combined with personalized touchpoints to each customer's goals, resulting in reduced churn by 30%," shares Aviel Sivan, Head of Global Customer Success at Windward.
The Path Forward
The confidence crisis in Customer Success, whether it's about AI adoption, personalization delivery, or operational scaling - isn't about lack of vision or effort. It's about the fundamental challenge of translating ambitious goals into consistent execution.
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The teams breaking through aren't waiting for perfect AI solutions or unlimited resources. They're taking five specific actions:
- Unify data sources before chasing AI implementations—data quality is the foundation for everything else
- Publish success hub templates for each customer segment to enable self-service
- Set trigger rules on usage and lifecycle events to automate the right intervention at the right moment
- Embed predictive intelligence for renewal risk and expansion signals
- Auto-generate QBR content to reclaim preparation time for strategic conversations
EverAfter customers testing this model report a 40% drop in manual follow-ups within three months, proving that personal doesn't have to mean expensive—and that the right foundation makes AI adoption much more achievable.
The next wave of Customer Success isn't about choosing between AI and human touch, or between high-touch and tech-touch. It's about creating experiences where intelligence, automation, and human expertise combine to deliver personalization that actually scales.
Because in 2025, good intentions aren't enough. Whether it's AI implementation or personalization delivery, customers can feel the difference between true capability and capability theater. The question isn't whether your team believes in the future of Customer Success - it's whether you can bridge the gap between confidence and execution.
Ready to see how your team compares? Our complete 2025 Digital Customer Success Benchmark includes detailed frameworks and actionable guidance for bridging the gap between AI ambitions and current reality, plus proven strategies for scaling personalization and operations.
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