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How To Use AI In Customer Success Without Killing Trust
- Laurence Leong
- Mar 10
- 4 min read
Updated: Mar 27
AI is quickly changing CS. Teams are using AI to automate onboarding, analyze customer data, and help CSMs work faster. But there is a challenge. CS is built on trust. When companies introduce AI without being clear about how it works, customers can lose confidence. This blog includes actionable insights on how to maintain trust from a panel I joined with Anika Zubair (CEO & Founder at the Customer Success Pro) and Chad Horenfeldt (Head of CS at Avoca), hosted by Gemma Cipriani-Espineira (Founder at CS Angel) and featuring Tori Jeffcoat (Director, Product Marketing at Gainsight).
The AI Opportunity (and a Reality Check)
Recent Gainsight survey data shows that while 59% of CS teams report steady or increasing investment in the area, AI adoption itself only saw an 8% year-over-year increase, with only 14% of teams currently using AI agents. The primary hurdles aren't a lack of vision but challenges in operationalization.
Panelists highlighted key barriers:
Data Integrity: The "garbage in, garbage out" principle reigns supreme. AI is only as good as the data it's fed, and poor data leads to unreliable outputs and erodes trust.
The Expertise Gap: Many teams lack the internal training and change management processes to effectively implement and adapt to AI tools.
A Shift in Strategy: As Tori put it, "AI and digital are a strategy, not a segment." It’s not about replacing humans but augmenting them, allowing teams to reach every customer with the right resource—be it human, digital, or AI—at the right time.
Gainsight Surveyed +400 CS Professionals To Identify AI Trends
Interestingly, while a poll of the session's audience revealed that over 70% were using customer-facing AI, 9% admitted their organizations were not being transparent about it—a risky approach in a relationship-driven field.
Practical AI Applications from the Trenches
The most compelling part of the discussion was the real-world application of AI in day-to-day CS operations:
Personalized, Scalable Insights: At Okta, AI is used to create "Value Snapshots"—think a “Spotify Wrapped” for product usage—that deliver personalized summaries and benchmarking to thousands of customers at scale. It's also used to recommend the next best actions for CSMs.
The CSM's Co-Pilot: Anika Zubair championed the "co-pilot" approach, where AI acts as a dedicated teammate. By analyzing everything from call recordings to product usage data, AI can advise CSMs on risk signals, identify growth opportunities, and suggest the next best action for an account.
The AI Support Agent: Chad Horenfeldt shared how his team uses AI as a support agent, efficiently handling inquiries while freeing up human agents to tackle more complex issues.
Preserving Trust in the Age of Automation
For all its power, the panelists agreed that AI must be wielded with care. Trust is fragile, and past experiences with poorly managed chatbots have left customers wary. The key takeaways for leaders were unanimous:
Start Internally: Before deploying customer-facing AI, use it to refine models, prove value, and build confidence within your own team. Avoid making mistakes in front of your customers.
Be Transparent: The panel debated whether to give an AI a human name, but all agreed on the need for transparency. Be clear with customers when they are interacting with an AI and always provide a simple "off-ramp" to a human.
Avoid Over-Automation: Don't let efficiency lead to a spammy, impersonal customer experience. The goal is to augment the human relationship, not create a frustrating, automated wall.
Be a Gardener: AI is not a "set and forget" tool. It requires constant pruning, updating, and guidance to ensure it delivers an optimal and trustworthy experience.
Bringing Your Team on the AI Journey
CS leaders must own the AI narrative within their organizations. It is their responsibility to educate their teams, inspire a culture of experimentation, and provide the psychological safety needed to navigate this change. This requires a robust change management strategy and a clear one-year plan that shows how humans, digital channels, and AI will work together as part of a unified customer success strategy.
At the end of the day, it’s not an either/or between Human CSMs, AI Agents, or Digital. The future of Customer Success is an intertwined ecosystem where AI and Digital are used for maximum scale and to handle the administrative and data-processing load, freeing up humans to do what they do best: build relationships, think strategically, and deliver outcomes; and doing this in a way that delivers more value, and therefore trust, to customers.
Further Education & Resources
Continue your learning journey by exploring more resources recommended by the panel:
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