Is AI Making Human Reps Obsolete? The Role and Responsibility of AI in the Modern Call Center

Used well, artificial intelligence (AI) can offer increased efficiency, productivity, and service levels—but they should enhance, rather than replace, human agents

Ever since ChatGPT was unveiled for public use, AI is the talk of the town. AI contact center solutions are a hot topic.

And while AI growth and usage has significantly accelerated over the past two years—and shows no signs of slowing down anytime soon—there’s still a lot that’s misunderstood about how AI fits into the modern call center.

Can AI be transformed into a full-service agent, allowing you to replace all of your human agents with AI?

Should conversational AI be avoided completely in the name of having more relational customer interactions for your audience?

The answer lies somewhere in between. While AI call center solutions can certainly offer increased efficiency, productivity and improved service levels, it can’t replace the empathy and connection human agents offer. That said, ignoring AI altogether will set your call center behind other brands in an increasingly fast-paced and on-demand world.

So how do you use AI effectively to get the most value out of both automated systems and your human team? That’s what we’ll explore in this guide, explaining what you need to know about AI solutions, why AI isn’t replacing your team any time soon, and how to use AI most effectively to maximize rewards and reduce risks.

The Rise of AI & What CX Leaders Should Know

First things first: what do people actually mean when they talk about AI? Artificial Intelligence has many variations, and there’s a wide variety of things that often get lumped under the blanket term of AI.

Here are some important ones that CX leaders should know:


AI that allows machines to learn from large data sets without being specifically programmed


Machine-learning-based networks that use an AI-enabled algorithm to predict the next word given vast amounts of data training sets. ChatGPT is an example of an LLM, and such models can be used to develop general-purpose language generation and understanding


A form of AI that allows machines and programs to understand, analyze and process human language, and in some cases, respond appropriately


A form of AI—often based on a combination of AI tools, such as NLP and ML models—that can simulate human conversations


Similar to NLP, an AI tool that can analyze large or small data sets, conversations, or written messages to identify emotional sentiment and tone

There are many more forms of AI, but these are some of the major ones being used and talked about today. Here’s some of the areas where you might see these being used in a call center:


to assist customers with basic customer service needs or concerns

AI-powered IVR

systems that can analyze a customer’s question and provide the appropriate next steps or answers without need for a human agent

Predictive call routing

that uses AI-technology to match callers with the right live agent based on experience, personality, topic or more

Agent assist using sentiment analysis

to give agents faster insight into customer concerns and needs

AI-powered analytics

to analyze more customer calls faster and provide a deeper level of analysis based on NLP, sentiment analysis and more

Obviously, the ability, predictability and usefulness of AI tools are growing, and AI is becoming more and more capable of human-like interactions. As a result, call centers are increasing adopting AI-based tools into their workflows and processes.

But does all of this mean that human agents will eventually become obsolete? In time, will AI-powered chatbots be able to handle customer concerns just as well as a live agent could? Let’s take a look at the current data.

Is AI Making Human Reps Obsolete?

The data is in, and it might surprise you: despite the rise of AI-powered tools and capability, most customers still want human interaction.

Take a look at the numbers:

say they prefer to talk to a human when they need customer service help

77% say chatbots are frustrating, and only 35% say that a chatbot can help 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

Far from being a replacement of human agents, chatbots still aren’t the magic bullet many call centers hoped for in terms of customer service and the customer journey. Instead, chatbots work best alongside human agents, and many customers still prefer to chat directly with a human agent the first time. AI can empower agents to work more efficiently and serve customer better.

In addition, chatbots and AI tools have other troubling problems—for example, the propensity to deliver inaccurate or biased responses (56% of people surveyed had experienced this) and the risk of “hallucinations” (inventing false answers or straying from programmed scripts) or emotionally inept responses (e.g. Congratulating a user who shares that their dog died).

That said, the role of human agents remains crucial. Not only are human agents necessary for complex customer concerns or unique situations and needs, human agents are the only ones who can respond with appropriate empathy, develop real connections with your customers, and ensure a…well, human touch for your brand.

This human touch remains essential in 2024 and beyond, when customer service continues to play a major role in customer satisfaction and loyalty. Without real connection, empathetic agents, and a feeling of understanding and support from your brand to your customers, customer loyalty will remain elusive.

However, that doesn’t mean that call centers should ignore AI altogether. Instead, the answer lies in implementing the right AI tools that can provide the appropriate support for your human agents—in short, letting AI be good at what it’s good at, and letting humans be good at what they’re good at.

Ready to take the next step?

How AI Can Support Human Reps at Call Centers

But what exactly does that look like? Figuring out how to implement AI effectively into your call center strategy is no easy feat.

Here are six key ways AI can support your human reps at call centers–without losing your customer’s trust.

Improve productivity and engagement

Implementing AI can increase agent productivity by 31%, saving about 12 hours a week in one study. But what kinds of AI tools really improve productivity? We’ve seen things like:

sentiment analysis speeding up workflows

automated voice call transcriptions to speed QA processes and post-call work

AI-powered IVR systems deliver a customer to an agent with more background, reducing the length of time the call needs to take

increased automation of post-call work such as notes and logging

RPA to automate repetitive workflows and recurring administrative tasks

All of these automations also serve to increase agent engagement. When agents spend less time on tedious, repetitive tasks, they can spend more time interacting with customers, providing quality service and building relationships. This leads to higher levels of engagement with their work and less burnout and boredom.

And since more engaged agents deliver better customer engagement, this is also a win for your customers—correlating with increased customer satisfaction, brand affinity and loyalty.

Lower operational costs

According to recent research, implementing AI tools for your team can lower operational costs by as much as 59%. And no, this doesn’t mean you should immediately go fire your human agents.

Instead, AI can lower operational costs—even with the same team on board—by making your team much more effective and delivering critical business insights sooner. For example: teams who implemented real-time voice transcription found costs reduced by 13.6%. Not only were agents more efficient, as after-call work was reduced due to AI transcriptions and note-taking, but there was also clearer follow-up after each call, leading to increased customer satisfaction, better data analysis and stronger QA processes.

This is just one example of how AI tools can help lower operational costs. Aside from improving agent performance, AI tools can also:

reduce the amount of manual labor needed for tasks like data entry, data analysis, QA processes and so on

improve the amount and quality of data analysis from your call center, leading to better business insights and stronger business decisions

reduces turnover by creating agents who are more engaged and satisfied with their work, thus resulting in lower hiring, staffing and training costs

improves loyalty and customer retention rate with higher service levels and faster, more effective service

Reduce human error

Human agents are great at empathy, emotional intelligence, connecting with customers, problem-solving (especially complex problems) and creativity—all things that AI isn’t that great at (at least, not yet).

But what about what humans aren’t so great at? Things like:

  • Tedious, repetitive tasks
  • High levels of detail, especially over large quantities of work or data
  • Quickly managing large data sets for processing or analysis

These are all areas where AI shines, and bringing AI into your workflow for these types of tasks can not only improve efficiency and lower operational costs (see above points), but they can also help your team greatly reduce human error and create more repeatable, consistent processes and data handling.

For example, take the process of data entry and processing—even with the best human agents on the case, the work is likely to be slow and tedious, which means that human agents will become more liable to errors and mistakes along the way. On the other hand, a machine can process data endlessly, with no tiredness and much lower potential for errors.

Improve speed of answer and service metrics

It makes sense that as agent efficiency and engagement improves, you can also improve service metrics such as speed of answer and average handle time.

But these aren’t only indirectly impacted by AI tools—there are also ways to implement AI tools intentionally to improve service levels. Consider:

  • AI-powered interactive voice response (IVR) can help get common questions answered resulting in faster response times
  • AI customer analysis can provide detailed insight into customer behavior and preferences, assisting agents with providing more personalized service
  • AI-powered knowledge bases can assist agents with providing accurate answers more quickly, allowing for faster handle times and less call transfers
  • AI chatbots and self-service tools can provide faster service for simple questions and route calls, providing 24/7, on-demand service for higher customer satisfaction and lower wait times

In addition, increasing self-service tools not only lowers wait times for the customers who make use of them, but, since it frees up agents to focus on more complex tasks and questions, it also lowers wait times for customers who really need to speak to a human agent.

Support agent understanding with sentiment analysis

Sentiment analysis has the potential to be one of the biggest AI supports for human agents. When employed properly, sentiment analysis can:

  • quickly give agents an overview of tone and emotion of incoming callers, allowing them to respond appropriately in less time
  • analyze large volumes of call transcripts or customer communications to understand high-level sentiment among your customer base
  • alert managers or supervisors when an agent might need support dealing with an angry customer
  • provide real-time assistance for responses and solutions based on customer emotions and previously-successful responses
  • and more

In short, sentiment analysis is like an emotional coach for your agents—monitoring every call and interaction in real time for word choice, tone, complexity, caller history and more, so that your agents can provide the best support every time.

While human agents may still be the best at actually providing that emotional, empathetic response, AI tools can make quick analysis of what the emotion or sentiment is, on both a micro and macro level. Having these insights not only provides support for your agents, but it also provides your team with better analysis of your customer’s feelings, thoughts and perceptions toward your brand.

Improve QA & agent training

Another major area where AI can shine in your call center is through improved QA and agent training.

In the past, QA has been a largely manual operation, with QA supervisors or managers reviewing calls or call transcripts one-by-one, grading them against a scorecard, and then compiling data for further analysis, agent training or review. Due to the amount of time and effort this requires, most call centers only reviewed a random sample of calls or conversations, and agent reviews typically took place days or weeks after a given conversation.

AI is changing the game for QA processes, in terms of both speed and scale. For example, augmented quality monitoring (AQM) software allows call centers to automatically record every call and uses AI tools to transcribe calls, review them, score them against a given scorecard and provide feedback and customer data, all using NLP, sentiment analysis and more. Not only does this provide a much deeper look at quality, but it also improves efficiency, reduces manual work for agents and supervisors, and drives cost-savings as a result.

Is Your Call Center Implementing AI Effectively?

At ROI CX Solutions, we’re already implementing AI-powered supports and tools for our teams, with great success for both clients and customers. Our best-in-class technology, powered by experienced and empathetic agents, drives results like:



(from an average 40-minute wait to a 7-second wait)



by providing more efficient service, our client saw more appointments scheduled and fewer no-shows

Tripled Quality Output

and appointments set for a client while maintaining high quality standards



achieved a 70% inbound sales conversion rate through data-driven intelligence into customer behavior and sales trends

What could results like these achieve for your business?

Improve customer satisfaction, strengthen trust and understanding between your brand and your customers, and improve operational efficiency while lowering overhead costs by implementing the right AI tools into your call center. Connect with an expert from ROI CX Solutions today.

Read more about the results we’ve gotten for our clients

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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