The AI Contact Center Revolution Is Here But, Most Companies Are Getting It Wrong

A recap of my conversation on the CX Pod with Liz Glagowski of the Customer Strategist Journal at the TTEC SKO

I've spent years working on a problem that's been unsolved for decades: how do you deliver genuinely great customer experiences while controlling costs and scaling intelligently? For most of that time, the tools just weren't good enough. The promise was always bigger than the delivery.

That's no longer true.

I sat down with Liz Glagowski on the CX Pod at the TTEC SKO recently to talk about where we are in this AI moment: the real trends, the hard truths, and what separates the companies that will win from the ones that will spend a lot of money and get very little back. Here's what I wish every CX leader would take away from that conversation.

1. The problems haven't changed. The tools finally have.

The core challenges in CX (improve quality, control costs, raise CSAT, increase sales conversion) have been on every ops leader's list for decades. What's different now isn't the problem statement. It's that large language model-native technology has finally given us the tools to actually deliver against that promise, not just promise it.

The companies winning right now aren't the ones chasing the newest shiny thing. They're the ones who got educated on what real AI looks like versus bolt-on solutions, and made deliberate choices about where to deploy it.

2. Voice of the customer is the most underused strategic asset in the enterprise

Every Fortune 100 CEO says they want to be customer-centric. But most organizations are still treating their contact center data as a cost center problem rather than a strategic intelligence engine.

Every conversation your customers have is a signal: about your product, your pricing, your competitive gaps, your compliance risks. When you surface those insights and route them to the product team, the marketing team, the compliance team, you've transformed customer service from a reactive function into a proactive business driver.

This is one of the three big areas where I see the highest-impact AI deployments: deep, continuous voice of the customer that reaches every part of the organization.

3. As AI agents take more conversations, quality assurance becomes more critical, not less

Here's the thing most people don't talk about: as AI agents handle more and more customer interactions, who's checking those AI agents?

The customer doesn't care whether they talked to an AI or a human. They care about whether their problem got solved and whether the experience was good. That means quality has to cover the entire journey, AI agent interactions and human agent interactions, as one connected thing and not two separate programs.

We recently had a Level AI voice agent handle a 15-minute complex troubleshooting call, walking a customer through a 20-step solution end-to-end. That's the level of capability we're at. But capability without quality oversight is just a faster way to disappoint customers at scale.

4. "Show me the money" is the new table stakes for AI vendors

In 2024, a lot of organizations signed up for AI pilots on faith. In 2025 and 2026, the question has changed: Where's the ROI?

My advice to any CX leader evaluating AI right now: work backwards from outcomes. Don't try to solve every problem at once. Find the one or two highest-impact automation opportunities in your specific business. For an e-commerce company, that might be "where is my order." Build the IT environment for that, prove the return, then expand.

The bigger the organization, the more tech debt you're working around. Phased, ROI-driven deployment beats a grand unified AI strategy that takes 18 months and never ships.

5. Four different AIs for one customer journey is a problem, not a portfolio

This is the one I feel most strongly about. Right now, it's common for a single customer journey to touch a voice agent from one vendor, a copilot solution from another, a QA tool from a third, and a VoC platform from a fourth. Four different AIs. Four different data silos. Zero connected intelligence.

That's not a tech stack; that's a patchwork. And customers, and the CX leaders who serve them, are starting to figure that out.

The trend I'm most excited about for the next few years is organizations consolidating toward one integrated, end-to-end system with one connected AI across the full journey. Not because it's cleaner architecturally (though it is), but because that's the only way to truly understand and improve the customer experience holistically.

What I think we'll be talking about a year from now

When Liz and I reconnect next year, I expect the conversation to shift from "what's possible" to "what actually worked." The projects getting underway now will have delivered real, measurable ROI, and the brands that moved deliberately will have a meaningful competitive advantage in how they serve customers.

The most differentiating thing a brand can do right now isn't have the most AI. It's have the right AI, connected across the full customer journey, with quality and intelligence built in from the start.

Want the full conversation? Listen to the complete episode on the CX Pod to hear more on how AI is reshaping contact center operations, what separates high-ROI deployments from expensive experiments, and where the industry is headed next. Listen to the full episode here!