Customer Experience Expert Warns Leaders to Limit AI’s Interaction with Customers
Dan Gingiss explains how AI can improve customer experience by handling repetitive work while preserving the human interactions customers value most.
Dan Gingiss
Customer Experience Expert, Speaker, and Consultant
Human First: AI can scale customer experience, but emotionally complex interactions still require seamless human support.
Smarter Scaling: Use AI for repetitive backend work so employees can respond faster, more intelligently, and empathetically.
Chatbot Risks: AI chatbots often create friction when companies prioritize cost reduction over resolving customer problems quickly.
Feedback Signals: AI customer-feedback analysis turns overwhelming comments into prioritized actions and reveals opportunities for proactive service.
Customer Focus: Successful AI programs start with customer needs, measuring whether technology improves convenience, relevance, trust, and consistency.
Dan Gingiss is a customer experience expert, speaker, and consultant who helps organizations connect with customers on a human level and create experiences that they can't wait to tell others about.
We sat down with him to discuss how to scale CX efforts without removing the human interactions that customers crave. Here's what he told us.
Social media is the gateway to CX
I am a customer experience expert, speaker, and consultant. I help mid- to large-sized organizations develop simple, practical, and inexpensive ways to make CX a competitive advantage.
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Being a solopreneur means I'm a CEO, CXO, CMO, COO, and everything in between. And having led social media teams at McDonald's, Discover, and Humana, I understand social media's impact on customer experience. That's why I teach companies how to be shareable — creating moments customers can't help but capture on their phones.
I also wrote one of the first-ever books on customer service in social media. I learned early on that while any company could broadcast on social, enlightened companies realized social media was a gateway to listening more effectively to customers.
How AI should and shouldn't be used in CX
I use AI to generate ideas, optimize workflows, identify gaps, analyze mountains of data, bat around strategy ideas, and develop products.
It's also good at quickly analyzing and taking action on customer feedback — both of which were extremely manual processes with qualitative feedback prior to AI.
But the more I lean into AI, the more I realize that it cannot replace human interaction.
Post-pandemic, consumers are still craving human interaction, so customer experiences must preserve that regardless of how AI is used.
That means you can't just hand the work to AI and be done with it. You need real customers to test it before you launch it into the wild.
Similarly, it is less useful for communicating with customers, especially as the general public has become more aware of content obviously written by AI.
Why AI should elevate your team instead of replacing them
The mistake companies make is using AI to replace humans instead of elevating them. The best experiences use AI to make humans better — giving agents context, surfacing insights, removing busywork — so when a human steps in, they’re faster, smarter, and more empathetic.
That's the biggest risk I see with AI in CX: that AI will take over too much of the customer journey.
The reality is that customers aren't ready for it. They don't want it.
For now, I recommend using AI on as much of the backend as possible, freeing up your humans to engage with customers 1:1.
So, AI should handle the things customers don’t want to spend time on — speed, convenience, simple answers, repetitive tasks. That’s where scale wins.
But the moment an interaction becomes emotional, complex, or high-stakes, customers want a human. And not as a last resort; as a seamless next step.
The mistake companies make is using AI to replace humans instead of elevating them. The best experiences use AI to make humans better — giving agents context, surfacing insights, removing busywork — so when a human steps in, they’re faster, smarter, and more empathetic.
AI should complement your team, not replace them.
Why some companies do AI CX right while others fail
One of the most compelling examples of AI driving results in customer experience is Netflix.
Their recommendation engine doesn’t just power the “Because you watched…” row — it personalizes every aspect of the interface, including dynamically changing the thumbnail artwork you see for the same show based on your preferences. The impact is massive: Netflix's recommendation system drives roughly 80% of the content watched, and that personalization saves the company an estimated $1 billion annually through improved retention.
That’s the upside of AI in CX at its best — more relevant experiences, higher engagement, and measurable business results tied directly to customer behavior.
That said, real downsides exist when AI is poorly implemented. Many consumers still report frustration with generic or “faux” personalization — like being addressed by the wrong name or receiving irrelevant recommendations — which can erode trust.
And in customer service, chatbot experiences have trained customers to expect friction instead of help.
Qualitatively, the biggest risk isn’t the technology itself — it’s losing the human touch. Organizations seeing the best results use AI to enhance empathy, not replace it, keeping the experience feeling personal, even as it becomes more automated.
Why AI chatbots are double-edged swords
One thing that is still underdelivering is AI chatbots. They're still largely useless.
We were promised faster, smarter, more human-like interactions, but many customers got clunky chatbots that act like digital gatekeepers, not unlike IVRs on the phone. They’re designed to deflect contact instead of resolve issues. Instead of improving the experience, they add friction, forcing customers to repeat themselves, hunt for a human, or abandon the interaction.
That’s not a technology problem; it’s a strategy problem. AI tends to disappoint when companies use it to optimize processes and budgets instead of elevating experiences.
When companies start with “How can we save money?” instead of “How can we make this easier, faster, or more enjoyable for the customer?” — that’s when AI misses the mark.
How CX leaders can benefit from AI customer-feedback analysis
Companies should use AI to analyze the mountains of data that previously required an analytics team.
I remember receiving daily reports in Corporate America of all comments left on the website — hundreds each day. I couldn't make heads or tails of it unless something was on fire and everyone was complaining about the same thing.
I'd review one day's report, then forget the next day, then run out of time the next day. By Friday, I'd have four reports on my desk with only time to scan one. Today, AI instantly analyzes these, resulting in specific action items based on customer feedback.
How AI makes proactive servicing possible
Proactive servicing is a huge opportunity. Too often, we ignore customers until something goes wrong, but AI can anticipate issues based on other customers' experiences and get out in front of them.
Here's how it works.
First, companies aggregate signals — customer behavior, transaction data, support tickets, even sentiment from past interactions. This combines what I call VOC (voice of customer) and AOC (actions of customer).
Then, AI models look for patterns that historically led to a problem. “Customers who did X often end up calling about Y.”
From there, you trigger proactive outreach. That could be as simple as a well-timed email or push notification, or as advanced as dynamically changing the experience in real time. For example, Amazon will reach out to customers proactively if they notice a slow download speed for a streamed movie, anticipating a suboptimal experience.
The key tools behind this include CRMs, predictive analytics models, and journey orchestration tools that automate the “next-best action.”
But the real magic isn’t the tech — it’s the mindset. You’re not waiting for the customer to raise their hand. You’re saying, “We see what’s likely to happen next, and we’re going to make it easier before it becomes a problem.”
Why Claude is the go-to CX tool
Claude has risen above the rest for its ease of use, outstanding writing skills, and ability to connect to other parts of the business.
But honestly, all of the major LLMs are incredible. Everyone has access to these tools for $20/month — tools that are only limited by our imaginations. I just wish I had a better imagination!
I am still learning new things and capabilities every day, and my first reaction often is, "Why didn't I think to ask AI that?"
Why CX leaders must focus on the customer, not the tech
AI has already caused organizations to become lazy. Not every email needs to be written by AI. Customers still want human interaction. Sure, we may eventually reach a stage where our world feels like Ready Player One, but we are decades away from that right now.
So, here's advice: Keep your eye on the ball, which is the customer.
No matter what technology comes our way, we should always ask: Is this better for our customer?
If so, proceed. If not, stop and find another way. Chasing shiny objects is rarely good for our customers, who want stability and consistency.
AI has already caused organizations to become lazy. So, here’s advice: Keep your eye on the ball, which is the customer. Chasing shiny objects is rarely good for our customers, who want stability and consistency.
Follow along
You can follow Dan Gingiss on LinkedIn, Instagram, and YouTube. And check out his personal website.
More expert interviews to come on The CX Lead!
