I was recently at Customer Contact Week (CCW) in Las Vegas, and—unsurprisingly—references to agentic AI were everywhere. Vendor booths, breakout sessions, and conversations around the expo hall all drove home AI’s potential to transform contact center operations.
But at the same time, I heard from many contact center leaders—at this event and others I’ve attended recently—that they feel like they don’t know where to start with AI. Or they’ve started an AI initiative but have gotten bogged down in the implementation, or they aren’t seeing the return they expected.
When implemented strategically, AI-powered technology can dramatically increase contact center efficiency, augment human agent skills, and improve service delivery. “Strategically” is the key word here. Simply jumping on the latest AI solution because that’s what everyone else is doing isn’t the answer.
I’ve been speaking a lot lately about how contact center leaders can navigate the AI hype to identify the technologies and use cases with the best ROI for their organizations. Below, I’ve summarized the trends and best practices that I keep coming back to.
Self-service AI is maturing, but the agent experience is suffering
Let’s start with one of the most prominent AI use cases for contact centers: self-service. Over the past few years, contact centers have done an incredible job implementing or optimizing AI-powered self-service capabilities (think chatbots, virtual voice agents, mobile apps). These AI solutions are great at handling routine requests or queries. Remember when customers used to call their bank just to check their balance? Now they simply open an app.
At the same time, AI self-service has its limits, and many organizations are already walking back their plans for an “agent-less” ( or near agent-less) future. Gartner recently surveyed customer service leaders and is now predicting that 50% of organizations that planned to significantly reduce their customer service workforce will abandon those plans by 2027.
Customers still want a human to help them with their most complicated or emotionally charged service issues.
Almost three-quarters (74%) of consumers still rank speaking to a live agent over the phone as their first choice when they have an urgent or sensitive issue, according to a Five9 study. Creovai’s own research with ContactBabel found that live phone calls make up around 65% of all inbound contact center interactions, and that percentage has remained relatively steady over the last several years, even as AI self-service technology has improved.
What has been changing is the pressure on human agents. Ten years ago, an agent might handle one complex call, then get a mental break with five or ten straightforward ones. Today, with self-service siphoning off the straightforward interactions, most calls coming through to human agents are complex or high stakes.
Think about it: if customers can't solve their problem through self-service, it's because their issue is genuinely complicated or urgent. Your agents are now dealing with complex call after complex call, with no reprieve. Without the right tools and support from your contact center, that’s a recipe for burnout.
Contact center leaders can’t afford to ignore agent burnout
The high-stress nature of the agent role is driving up attrition rates at an alarming pace, with average agent turnover currently in the range of 30-45%. Agents are struggling because they’re jumping between systems to try to solve customer issues, dealing with outdated knowledge bases, or just not getting the training they need to successfully handle difficult interactions.
Here's the kicker: when agents struggle, your customers feel it immediately. An overwhelmed agent can't deliver the experience your customers expect, especially when they're already frustrated enough to pick up the phone instead of using self-service.
It's a vicious cycle. Struggling agents either leave (driving up your recruitment and training costs) or they stay but can't perform at their best (driving down customer satisfaction). Neither scenario is sustainable.
If your contact center has been focusing all its AI efforts on self-service, you need to start looking at how you can implement AI to support your human agents. While self-service continues to be important, the need for human agents isn’t going away any time soon, and equipping your agents to handle complex interactions is critical.
Start with quick wins: AI to reduce after-call work
So where should you implement AI to support your agents? My recommendation is to start with the one or two areas that will give you the quickest return on investment, then layer on additional capabilities over time.
In my experience, one of the easiest wins is in after-call work. Consider an insurance agent handling a First Notice of Loss claim—they might spend 10 or 15 minutes on the call gathering details, then another 5-10 minutes documenting everything in their CRM system. Using generative AI, software like Creovai Agent Assist can listen to that call in real-time, automatically summarize the conversation, extract key tasks, and populate the CRM system. We often see a 50-80% reduction in after-call work with this single capability. Not only does that reduce operational costs for your contact center, but it also enables agents to spend less time on administrative work and more time helping customers.
Layer on intelligent guidance: AI to improve call outcomes
Of course, reducing after-call work doesn’t directly solve the challenge of agents struggling with complex customer interactions. This is why I recommend layering on what our team at Creovai calls intelligent guidance.
The concept is straightforward but powerful: instead of leaving agents to navigate complex interactions alone, we use AI (a copilot widget on their desktop) to guide them toward the most successful outcomes based on your organization's interaction data.
Here's how it works. First, Creovai analyzes all your historical interactions using conversation analytics. Creovai Conversation Intelligence can help you identify what successful agent journeys look like, understand the top reasons customers are calling, pinpoint the most effective responses, recognize common objections along with the best rebuttals, and more. Essentially, it surfaces interaction insights that you’d never be able to uncover from manual reviews alone.
Then, you can add prompts to our real-time agent assistance software based on your best historical interactions. As agents are speaking with customers, our Agent Assist software listens and understands the conversation in real-time using AI. It automatically guides agents with the information they need—including relevant prompts based on what has worked well in similar situations.
For example, in an outbound sales contact center, you might use Conversation Intelligence to identify which rebuttals are most effective for different customer objections. You could then build the most successful rebuttals into Agent Assist so that whenever the software detects a specific objection in a live conversation, it can prompt the agent to use the most effective rebuttal.
Intelligent guidance gives all agents access to the experience and knowledge of your top performers. It’s based on proven success from your organization, scaled across your entire team. It helps your agents navigate towards that “ideal interaction” every time, reducing stress and enabling them to efficiently resolve complex issues.
Your next steps
AI can do a lot, but it can’t be your strategy. Success requires focusing on the technology that can start delivering tangible value quickly rather than making scattered investments. Start by identifying your biggest pain points—whether that’s wrap-up time, complex voice interactions, sales conversions, or anything else. Implement AI solutions that address these specific challenges, measure the results, and then expand your capabilities.
Most importantly, remember that AI should augment your human agents, not replace them. The goal is to automate straightforward, repetitive tasks while giving your team the tools they need to handle increasingly complex interactions with confidence. The immediate benefit is better service delivery and issue resolution, but enabling your agents with AI can have a number of knock-on effects. Agents who have the tools to be successful are likely to stay with your contact center longer, giving you more experienced agents and reducing your hiring and onboarding costs. And when your customers consistently receive support from confident agents who resolve their issue on the first contact, they are more likely to continue doing business with you.
The question isn't whether AI will transform contact centers—it already has. The question is whether you'll harness it strategically to support your agents and deliver excellent customer service, or get mired down in complex implementations and a scattershot approach.
The choice is yours.
