In 2024’s Customer Success Leadership Study, 87% of participants said their teams use or have immediate plans to adopt AI. However, only 21% said they have purpose-built AI products in their CS tech stacks.
Optimistically, we can infer a healthy picture of experimentation and pilot projects with AI point products. It makes sense to try point solutions, especially if your CS team is still figuring out other things like your renewal process and plays, or your adoption methodology.
The issue over time is that AI point solutions, just like other point solutions, lead to different people doing different things. Your CSMs’ AI prompts on how to engage a customer, or their descriptions of healthy versus unhealthy, are different. One day, you wake up and everything and everyone is a bit out of sync.
At this point, it’s time to integrate your processes (whether AI or non-AI) to achieve standardization and repeatability. It’s time to think about a customer platform to centralize AI.
To unlock the real value of AI, everything needs to work together.
Arguably, point products can achieve each point task better because they specialize in that exact thing. Yet, with AI, making things work together is where the real value is.
An analogy: building a car. You can shop for the best components individually—the tires, the headlights, the speakers, the seats. But can you put them together effectively? Will they actually perform that well together? Chances are, despite the parts, you won’t get the most effective vehicle.
Point products aren’t designed to get a whole enterprise on the same game plan. If one point is overly important to you and you need to specialize, keep it. But when you’re buying AI for automation, summarization, health scoring, predictive analysis, and more, it’s hard to pull together many point solutions without a full-time ops or engineering team.
You tell your AI point product to write a renewal email, and it writes a great “Hey, it’s renewal time” draft. But it doesn’t know that this is a healthy customer whom you intend to upsell next quarter. Without those data insights to layer your prompt onto, your AI can’t be truly effective, and you end up with fragmented workflows and missed opportunities.
Why AI matters for customer teams: Could you deliver a 30-50% productivity increase?.
When should you centralize your customer team’s AI tools, and how?
If you know people are using AI but don’t know how they’re using it, it’s time to centralize your customer team’s AI through a CSP like ChurnZero. If you have an uneven distribution of AI use, where your tinkerers are doing interesting, effective things for themselves and others, but nothing is standardized and scalable, that’s a sign.
If adoption levels are more uniform, but half are using ChatGPT, one-third are using Gemini and the others are using Meta, or Claude, you should be a little worried, because that’s where you also run into compliance issues with customer data.
Compliance isn’t just an issue for large companies. Even if you’re small, customers will require you to be super-careful with their data.
When you centralize your AI, you can get a clear answer from a single platform vendor about how they do it—for example, ChurnZero requires that our AI vendors do not use customer data to train their models. And, assuming your CSP’s AI is effective, the likelihood of your team members using their own AI solutions decreases from there.
Get more actionable advice on building and scaling AI use cases in ChurnZero’s new AI guide for customer teams.
How do you choose the right AI-powered customer platform?
You still have to do the work to uncover whether a CSP has actually invested in AI or is just marketing it. Integrations with different AI tools are certainly important. But soon, every software will have AI, so look at how advanced the CSP’s AI capabilities are.
“Helper” features where you ask questions are entry-level. The CSP should be doing things for you: writing emails, summarizing account histories—things that are actionable. Soon, AI will become a background feature in playbooks, adding layers of personalization based on data in the CSP.
So, as a buyer, you need to look past the marketing checks and examine what AI features they’ve shipped, how integrated they are, and whether they’re in the right places.
You Mon Tsang is the CEO and co-founder of ChurnZero. Learn more from You Mon about AI for customer teams.
