If you work in CX or revops, chances are you've had more than a few conversations about generative AI recently.
Some of those conversations are filled with excitement. Others are loaded with questions. That's understandable. The technology is moving quickly, and everyone wants to know whether it's going to make a real difference or just become another system to manage.
In my own experience leading CX and revenue operations, I've seen both sides: AI tools have created huge opportunities to improve speed, scale, and consistency; but there's a real risk of adopting something too quickly and losing sight of the customer.
That's why my first question is never, "How fast can we implement this?" It's, "How does this help us serve people better?"
Speed is only valuable when it supports context, clarity, and trust. Without those, automation just makes bad experiences happen faster.
Modern expectations demand a new approach
The traditional support model—relying on scripts, long ticket queues, and static knowledge bases—can't keep up with modern expectations. Customers today want quick answers, but they also want to feel understood. Generative AI is powerful because it has the potential to meet both needs, but only when it's applied thoughtfully.
When I started piloting these tools with my teams, I was especially cautious about how we used AI for things like call summaries or email replies. Those tasks seem simple, but they carry weight. One mistake can shift the entire tone of a customer relationship.
I remember a case where AI pulled a hypothetical example from a customer conversation and flagged it as a confirmed action item. The summary stated that a meeting with a major prospect had been scheduled, but in reality the client was just offering an example.
That kind of error could easily have led us down the wrong path if we hadn't reviewed the output carefully.
This is one of the most important things I stress with teams exploring generative AI: Always inspect what the technology delivers.
Fully 66% of employees rely on AI output without verifying its accuracy, according to a KPMG survey. Not verifying AI output can often lead to easily preventable mistakes. We still need human judgment. AI can surface insights and draft messages, but it doesn't understand nuance the way people do. We have to train it, monitor it, and stay involved.
When used well, though, AI can genuinely improve the experience for customers and teams alike.
I've seen AI-generated responses that reference past purchases, tailor product recommendations, and even adjust tone based on sentiment. These tools help deliver more personalized service without overwhelming agents. And that's key, because customers notice when a response feels specific to them instead of a copy-paste job.
AI also supports self-service in ways that couldn't be done before. Knowledge bases can be updated automatically based on frequent issues, which helps customers find answers on their own. That means fewer tickets, faster resolutions, and a more empowered customer experience.
But AI isn't just for customers. It's also a huge asset for frontline teams. When a rep starts working a case, AI can surface recent interactions, relevant documentation, or product details within seconds. That saves time and shortens onboarding for new hires because the context is built right into the workflow. Instead of digging through systems, agents can focus on solving problems.
People still drive the experience
Even with all of the innovation, one thing hasn't changed: Good customer experience still depends on trust. And trust isn't built by saying "yes" to everything. It's built through honesty, consistency, and the willingness to have hard conversations.
In CX, there are times when the right thing to do is push back. Maybe a client wants a quick fix that won't work long-term. Maybe the project isn't a good fit. The easy answer might be to agree and move forward, but that doesn't serve either side.
I've had moments where I've had to say, "This isn't the right direction," or even, "We may not be the right partner for this." Those conversations aren't always comfortable, but they earn trust in the long run.
Being seen as a strategic partner means being willing to protect the client's long-term success, even when it comes at the cost of a short-term opportunity. That mindset turns customers into advocates, even if they're not actively doing business with you at the moment.
A good interaction, one that's honest, supportive, and grounded in mutual respect, can lead to future partnerships, referrals, or new conversations when that client moves to a different company.
That's what I think about when I talk about CX and AI together. The technology is exciting, but it's not a substitute for human connection. It's a tool that can help us be more efficient, more consistent, and more responsive. But the strategy still has to come from people who care about the customer and who are willing to do what's right, even when it's hard.
* * *
AI is here to stay. It will keep evolving, and it will become a bigger part of how we operate.
But the heart of customer experience will always be the same: listening closely, responding thoughtfully, and showing up in a way that builds trust over time.
