How Contact Centers are Using AI: A Look Behind the Scenes

As AI advances, how are contact centers responding? A balance of AI and human support speeds workflows, optimizes efficiency and improves customer satisfaction.

AI has long been the subject of many thriller films, with a common plot: AI comes to take over the world.

If you’re outsourcing your customer service to a contact center, you’re probably a little less concerned about AI taking over the world and a little more concerned about how your contact center might be using AI.

  • Are you paying for your contact center to outsource all of your customer service to a robot?
  • Is your contact center using AI in ways that are irritating to your customers or damaging to your customer service?
  • Should your contact center be using AI, and if so, how?

Far from AI taking over the world and making call center agents (and many other jobs) obsolete, what we’ve seen is a helpful symbiosis of sorts emerging as call centers begin to integrate AI into their processes and work. As they do, it’s not only optimizing productivity and enhancing efficiency but also improving the overall customer experience by freeing up more time and energy for human agents to focus on human-centered tasks and experiences.

So how exactly are contact centers using AI to improve the customer experience—or how should they be? Here’s a behind-the-scenes look at how our contact centers at ROI CX Solutions are using AI for positive improvements and what to look for and consider in your own call center or outsourcing partnership as you look to leverage AI.

The rise of AI in customer service and CX

There are so many different forms of AI available today, and that’s true in the CX world as well. If you’re not familiar with some of the AI options and capabilities out there, here are some common ones you’ll likely see call centers using or experimenting with:


Chat-based bots that use machine learning (ML) and natural language processing (NLP) to answer basic questions or service needs from customers in a real-time dialogue as virtual agents.


IVR systems that use NLP to analyze customers’ questions and provide the appropriate next steps and input without the need for a human agent.


Uses AI technology to match callers with the right human agent based on experience, personality, question topic or more.


Uses sentiment analysis to give agents faster insight into customer concerns and needs and suggest relevant solutions.


Uses various forms of AI to analyze customer calls faster and provide deeper levels of analysis on large quantities of data.

That’s not to say that every call center is—or needs to be—using every form of AI available. However, the options, availability and capability of AI are growing, and call centers should be determining which AI tools will be most useful for them and the customers they serve.

As you consider the rise of AI throughout customer service and the CX world, it pays to keep two important questions top-of-mind:


AI tools might be helpful to either your agents, or to your customers, or ideally both. Even if customers aren’t aware of AI being used to power a workflow or increase personalization, they can benefit from it.


Too often, companies try to solve a non-problem with a new piece of technology, only to create problems that weren’t there before. For example, many IVR systems, improperly implemented, cause extreme frustration to callers. A whopping 98% of callers have tried to skip through IVR systems to reach a human agent—which doesn’t mean that IVR systems aren’t helpful, but rather that they are often set up in unhelpful ways. You don’t want to use AI in a way that “breaks” something good you already have going. Instead, use it to enhance your processes that currently work well.

But before we dive into tactics on how to do that, perhaps a more pressing question needs to be addressed:
should AI replace human agents, or can it?

Ready to take the next step?

Is AI replacing human reps in call centers—or should it be?

The short answer is: Even conversational AI can’t replace human representatives in call centers (or at least not yet). But perhaps more importantly, it shouldn’t be, even if it could. The data is clear—the majority of customers often prefer to speak to a real person when they have a concern:

prefer to speak with a human agent when they reach out to customer service.

ay chatbots are frustrating, and only 35% say that chatbots solve their problems most of the time.

are more willing to use a chatbot if they know they can easily transfer to a human agent for more help.

This isn’t to say that AI doesn’t have a place in contact centers—but it certainly won’t be replacing human agents anytime soon.

Ideally, there should be a balance at contact centers between AI tools and human agents, and both should be used for what they’re best at. That is, AI tools should be used for large-scale data analysis, rote and repetitive tasks, data organization and manual entry, scaling operations and so on. Humans are, of course, better at emotional reasoning, empathy, building relationships and managing 1-on-1 conversations and complex situations.

For a contact center, both of these functions are essential, which is why using AI and human agents together effectively can significantly improve and optimize workflows. The bottom line: customers want to talk to other humans when they have larger problems or concerns, so keep a human-centered approach. But don’t be afraid to use AI in the background to speed up workflows and help live agents deliver a more personalized experience.

How exactly do you do that? That’s what we’ll walk through in the next section.

How contact centers are using AI: 6 tactics to implement

At ROI CX Solutions, we’re always looking to innovate and try new solutions that can improve customer interactions while also making processes and workflows more efficient for our agents. Increased productivity and improved customer service is always a win for us.

With that said, here are six ways contact centers—including our teams—are using AI.

Stronger QA processes and monitoring

AI contact center tools are great for large-scale data analysis and insights, so it shouldn’t come as a surprise that AI can be a major aid in the QA process.

Previously, QA processes were very manual and involved a lot of time and resources. Dedicated QA agents would have to listen to or monitor phone calls manually and so could only listen to a very small number of phone calls for each agent every week. The agent would have to listen carefully to the entire phone call and then identify areas to improve.

Since only a small number of calls were listened to on a weekly basis, it was difficult to find all issues in a timely manner, and a representative sample wasn’t always possible.

Since introducing AI to the process, it’s become much more efficient and effective, as well as wider in scope. AI tools can listen to 100% of recorded phone calls now instead of just a small percentage. Some AI tools can even use NLP and sentiment analysis to flag specific areas of concern for further evaluation. With this process in place, every call gets analyzed, and QA teams can simply listen to the exact parts of the call flagged for concern.


There are so many benefits here, namely:

  • QA is scalable and more accurate since all calls are being monitored and analyzed.
  • QA agents need to spend less time listening to calls and looking for issues and can spend more time evaluating areas of concern and coaching agents.
  • Issues flagged by QA processes are able to be fixed more quickly, causing fewer problems in the long run.
  • Since all calls are being monitored, fewer QA problems are slipping through the cracks, and agents receive better coaching.
  • CSAT scores are improving as agents get better quality feedback more often and are able to improve their service delivery.

Identifying and fixing call avoidance

Call avoidance has long been a problem throughout call centers, but monitoring it and fixing it was a largely manual and ad-hoc process. Far from being just an employee morale issue, call avoidance also creates large inefficiencies and overworked staff, leading to lower quality service and more dissatisfied customers.

This is another instance of large-scale data analysis that AI can help with pretty significantly. AI tools help here by identifying patterns of long hold times or long times of silence during the call and passing that data to QA. The QA team in place can then help correct this behavior and help agents become more efficient so they can handle calls more effectively and quickly.


Your operations run more smoothly, your agents are able to handle more calls in less time (meaning more cost-effective operations for you), and customers are able to be helped more quickly (meaning stronger customer satisfaction scores).

Supporting agents via AI Agent Assist

AI isn’t just for analyzing large swaths of data in the background—it’s also a great real-time assistant when data is needed as well. And when it comes to working with large numbers of customers, all of whom expect customized personal service, data is always helpful.

Agent Assist is one of the most helpful AI functions we’ve found to improve operations, support agents and deliver better customer service. With Agent Assist, AI listens to live calls in real-time and uses NLP and Sentiment Analysis to provide the agent with additional insight into the caller (i.e. if they’re at risk for canceling their subscription, based on common phrases used in other calls). Agent Assist can also provide several options for solutions agents can use to help resolve customer concerns.

From here, human agents can use relational skills and insights to choose the best solution and respond most appropriately. Agent Assist doesn’t replace the agent—you still need that human touch and understanding. What it does is cut down on the amount of time an agent takes to find the solution the caller is searching for.

  • Increase in First Call Resolution rate, which is correlated with higher customer satisfaction.
  • Faster and more effective service and call resolution, meaning better service for customers and more efficient service for you.
  • More personalized customer experiences, leading to higher satisfaction.
  • Agents can focus more on relational connection and complex tasks, rather than mundane requests or knowledge base searches which are high causes of agent burnout.

Optimizing efficiency throughout the call center

There are many ways that AI can be used to optimize efficiency and speed up workflows throughout your call center. We’ve mentioned some specific ones above (i.e. QA processing), but there’s many more that can be implemented. For example, a contact center might use AI to:

  • more quickly and efficiently evaluate candidate applications to hire agents for better-fit positions and reduce agent turnover
  • evaluate common mistakes and quality issues and flag them for ongoing coaching for QA teams
  • analyze workforce capacity and data to better forecast workforce needs and improve workforce management and predictions
  • create self-service tools so that customers can search your knowledge base or find solutions faster on their own, leading to reduced call volume, less-stressed agents and happier customers
  • manage small, everyday interactions such as taking payments or giving account information through chatbots or other self-serve solutions
  • support agents with after-call work such as tracking and logging many details automatically after listening to calls to improve efficiency

All of these solutions, among others, can increase efficiency and processes so that agents are more productive and customers get quicker, more effective results.

Improving customer experiences

Of course, all of this efficiency isn’t just helpful for you and your agents—it also trickles down into the customer experience.

Even when AI isn’t customer-facing, it lends a big hand toward improving customer experiences. For example, at ROI CX Solutions, our AI solutions have enabled us to remove many mundane, rote and repetitive tasks from agents’ plates, freeing up our staff to spend more time focusing on personalizing customer experiences and giving them more time and energy to devote to each customer.

As a result, the entire experience becomes more customer-centric, and our agents are able to meet and exceed customer expectations. Whatever gains in efficiency we get from AI can be directly routed back to serving the customer more effectively, resulting in stronger customer satisfaction, increased customer loyalty and retention and better brand perception for our clients.

Improving agent performance and outcomes

Finally, AI can be a great tool to improve agent performance and outcomes.

As mentioned above, AI can support QA processes, which can certainly provide valuable data into agent performance and provide detailed insights for more effective coaching. However, that’s not the only way you can use AI to improve agent performance. Other effective methods include:

  • Using an AI assist tool to provide real-time feedback and support to new agents so they can internalize their training faster.
  • Take QA data that AI provides and make actionable improvements as a result.
  • Use AI-provided data to incentivize agents to improve their biggest challenges and reward desired outcomes. Since AI can provide these insights at scale, you can personalize these efforts by agent so everyone is working on their own biggest challenges rather than generic feedback.
  • Allow agents to self-evaluate their own performances with AI support and use AI-powered knowledge bases or coaching support to give them the tools they need to improve.
  • Use AI to create personalized dashboards for each agent, allowing them to keep track of their own outcomes and KPIs and work toward improving them.

One of the biggest advantages of AI in this area is scalability. With hundreds of agents, it’s difficult to provide personalized feedback, coaching and training to each agent in a way that delivers quick and effective improvements. However, with AI, this feedback can be personalized and scaled no matter how many agents you’re working with.

With quick and effective feedback available, agents are more motivated to improve and improve faster, leading to more invested and highly-trained agents who provide better support to your customers.

Our take: AI at ROI CX Solutions

The bottom line is that AI is here to stay—and for that, we should be grateful. Instead of avoiding AI or assuming it can replace your human agents, it’s crucial to find the right ways to use it so that your AI tools complement your human agents’ skills and provide increased efficiency and productivity.

Consider, too, that customer expectations are constantly growing—whatever work you replace with AI will quickly be backfilled with increased customer needs, whether a growing need for personalization, increased call volume as you grow, or more genuine customer relationships. Customer service is always growing, and AI can help you become more efficient so you can keep up with—and even exceed—your customer’s expectations.

At ROI CX Solutions, we’re using AI in dozens of different ways, including many of the ways outlined above, and seeing incredible results. In our teams, AI is supporting our human agents and helping us:

  • improve service levels by providing more efficient service for our clients’ customers
  • optimize processes and workflows to provide more cost-effective service for our clients
  • improve agent performance through increased QA monitoring and coaching
  • strengthen customer satisfaction and brand perception through better, more personalized service
  • support agents by reducing mundane and monotonous tasks, allowing them to work on meaningful and complex challenges and improving job satisfaction (which in turn improves service provided to customers!)

Curious how an AI-supported contact center can help grow your business, improve your service levels, and strengthen customer satisfaction, all while making your operations more efficient? Contact an expert at ROI CX Solutions today—we’ll show you how our innovative and tech-powered solutions can help transform your business.

About ROI CX Solutions

ROI CX Solutions drives customer satisfaction and business success through outsourced customer service and global sourcing management. With decades of experience across our expert team, ROI CX Solutions has innovated results-driven performance and improved customer experiences for brands across a variety of industries. With flexible, customizable solutions, state-of-the-art technology, and world-class customer service representatives, we deliver results for your business—and your customers.

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