The Truth About AI in Contact Centers: What's Real and What's Complete Garbage in 2025

AI in customer experience  has become a buzzword, but let's cut through the noise. From exaggerated claims to outright scams, the truth about AI is often buried under a pile of marketing hype. In this blog, we’ll debunk the myths, call out the nonsense, and provide a practical guide to navigating AI in 2025 for your contact center.

The Problem with Vendor Driven Messages

AI messaging is being driven by CX vendors, not end users. Technology vendors are the ones telling you what you need and what is happening in the industry, and the people like our CEO Tom Laird, and like a lot of contact center professionals, don't have the platform or following or voice to say "Whoa, whoa, whoa that's not what we're seeing."

We are not seeing anything that a lot of these contact center technology providers are providing. And they're making people make really poor decisions when it comes to what they should be buying, what they should be purchasing, how they should be setting things up.

The Real State of AI in 2025

Here's what's actually happening, organizations are making one of two critical mistakes.

They're either panicking and purchasing expensive AI solutions they don't understand, or they're staying stuck with inefficient manual processes because they're overwhelmed by options.

Let me be direct while many AI applications are still maturing, we're seeing real success with practical agent level tools right now. Organizations are getting value from agent assist technology, automated QA, auto summarization, and analytics platforms. These tools work today and deliver immediate ROI as it realtes to AI.

The other unsaid truth, many companies don't actually need AI driven virtual agent techology.

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The Cost Reality Nobody's Talking About

Everyone thinks AI is just snapping your fingers and paying nothing but that's insane.

Let me tell you what's really happening with costs in 2025. Setup fees are crazy expensive. Your minimums for these large third party AI/analytics companies are extremely expensive. And even the per minute usage fees they're doing are crazy.

You're looking at platform fees, setup fees, per minute usage costs, and then ongoing maintenance and development.

Whether you try to build it yourself or hire a third party it's going to be extremely expensive.

If you do it internally you need a whole group of developers for prompt engineering integration and maintenance.

These "mychatbotisamazing.ai" companies are selling you dreams but they aren't telling you about all these hidden costs.

CCAAS Players Have an AI Pricing Advange in 2025

This is where I think the CCaaS guys have the best deal right now. If you're going to look at anything look at your CCaaS provider if you chose a good one. Whether that's Five9 or Genesys or CXone or Zoom their tools are going to be at least the most cost effective and they're already integrated into your platform.

That makes a lot more sense than going out and spending god knows how much money on some generative chatbot that you're still scratching your head about.

What's Real in 2025 A Practical Roadmap

Let me talk today about what I see is real. What is the roadmap or path that people should be taking in 2025 that is realistic? It's not going out and spending god knows how much money on some generative chatbot from "my chatbot is amazing dot AI" company. That stuff is where people are making huge mistakes because they're not ready for it.

The Reality of Self Service

Let me give you an example. We deal with a lot of financial services at Expivia, our BPO parent company. A lot of credit unions. We do core integrations and have been able to build amazing self service models using NICE CXone. Customers can check payments, make loan payments, and do all these things within the IVR, using natural voice. They paid for that. It is working unbelievably well. Customers are happy with it.

So what's the big rush to turn that into some type of AI-ish platform that maybe can give a couple more answers? Not everybody needs this.

The Five Levels of AI Implementation That Actually Work

Let me show you what I've seen working from a roadmap standpoint for AI with our customers. This is what I'm seeing work the best with our customers just in talking to people who are trying to be really methodical with this thing and thinking it through the right way.

Level 1 Infrastructure

The first thing that should be done is to look at your AI infrastructure. If your infrastructure stinks your AI is gonna stink. So looking at your KMS, looking at your procedures for KMS, looking at your system integrations, what API connectivity you have, what security you're willing to go through using LLMs and using large language models. Having all that scoped out is really really important. It's something that really needs to happen before you do anything.

Level 2 Advanced Analytics

We start to look at advanced analytics. Looking at customer intent because if you start to look at customer intent you're gonna start to know what self service you'll be able to utilize in the future. Looking at predictive analytics. Looking at what your customers are actually saying. Can you glean any insights into what's gonna help you from a self service or from even from an agent quality standpoint?

Level 3 Agent Level AI

This is where we see customers getting immediate ROI. Looking at tools like OttoQa, auto summarization, agent assist. These are more basic integrations. These aren't that difficult. If you look at the infrastructure piece that's pretty hard. Nobody wants to talk about that. They just say give me an FAQ and we'll figure it all out for you. The agent tools are straightforward and they work.

Level 4 Self Service Review

Once you get through the first three levels you start to think about self service. You start to think about what do we need to do to make it better. Now that we built out this KMS can we start to implement some of this knowledge into what we already have? Looking at intelligent FAQs and really just more automated flows within our self service. Are we at a point where we think we have everything built out where we can fully automate things?

Level 5 Customer Facing AI

Let me be clear. Maybe 5 to 10% of companies can really find value in customer facing AI compared to what they would have from a regular self service model. If your self service is on point I don't think that there's gonna be that much that you're gonna find from a customer facing AI platform than what you have now.

The Truth About Falling Behind

You're not falling behind because adopting AI isn’t a linear race where you need to grab every new tool as it appears. Instead, you can focus on building a solid foundation now and leap ahead when the right tools become available in six to eight months.

There’s no need to chase every technology trend today. By methodically preparing your systems and processes, you’ll be in a position to catch up quickly, and even surpass others who invested early in tools that turned out to be mediocre.

Bottom Line

AI in CX doesn’t have to be overwhelming or expensive. Start by building a strong foundation, focus on your KMS, advanced analytics, and agent-level tools. The future is coming fast, but you have time to prepare and catch up. And remember: AI is a tool, not a magic wand. Use it wisely