Artificial intelligence (AI) has revolutionized the way businesses operate, and call centers are no exception. The integration of AI technologies in call centers is transforming customer service, enhancing operational efficiency, and improving overall user experiences.

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In this article, we’ll explore AI automation in the call center, including key trends to watch in 2025 and beyond.

In this article:

• What is AI automation in the call center?
• Advancements in AI call center automation
• Growing use cases for AI call center automation
• The impact of AI call center automation on companies & the human workforce
• Potential issues & concerns in AI call center automation
• Transform your call center with AI automation in 2025
• Frequently asked questions

What is AI automation in the call center?

AI automation in call centers refers to the use of technologies, such as chatbots and virtual assistants, to handle routine tasks like answering inquiries, resolving issues, and managing workflows without human intervention. By integrating AI solutions, call centers can increase efficiency, reduce operational costs, and provide personalized services to customers.

Key components of AI call center automation include:

• Chatbots: Chatbots are AI-based conversational agents that can handle customer inquiries through text or voice. They can provide instant responses to frequently asked questions, guide users through processes, and even carry out transactions, all without human intervention.
• Voice recognition: Voice recognition technology allows AI systems to understand and process spoken language. This enables automated systems to identify customer intents and provide appropriate responses or escalate issues to human agents when necessary.
• Natural Language Processing (NLP): NLP enables machines to comprehend, interpret, and respond to human language in a meaningful way. This capability is crucial for understanding customer queries, sentiment analysis, and providing relevant solutions.
• Predictive Analytics: AI can analyze historical data to predict future customer behavior. This allows call centers to anticipate needs, optimize staffing levels, and create targeted marketing strategies based on customer trends.
• Automated Call Distribution (ACD): AI-driven ACD systems can efficiently route incoming calls to the most suitable agents based on various parameters such as skills, availability, and customer needs, enhancing overall service quality.

Let’s discuss some of the key trends in AI call center automation to keep your eye on in 2025 and beyond.

The 2024 CallMiner CX Landscape Report is here! One key takeaway? #AI continues to transform the contact center and #CX.

Findings reveal 👇
💡87% of CX leaders say genAI is key for their teams
💡91% agree AI will help optimize #CX strategies
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— CallMiner, Inc. (@CallMiner) September 10, 2024

Advancements in AI call center automation

1. Starting with the basics produces the most success with AI. “Shiny object syndrome with early-stage AI applications can prove distracting for enterprises looking for ROI from AI. In 2024, organizations will take a “back to basics” approach, looking at some of the areas in their business where automation and AI can help them produce the most effective gains.

For example, in the contact center, quality assurance (QA) is an often-overlooked area of investment for AI. Typical QA analysts can often only listen to 3 to 5 random calls per agent, per month — less than 1% of overall interactions. Instead of repetitive tasks like call listening, AI systems can analyze 100% of customer interactions across all channels — dramatically increasing the scale of the QA function and driving more accurate results. Further, the automation of time-consuming, mundane tasks will free up human employees to spend time doing more meaningful work. While these applications may not be the most ‘shiny’, they will generate the most value for enterprises in the shortest period of time.” - Five 2024 AI trends for the contact center and beyond, CallMiner; X: @CallMiner

2. AI-powered hyper-personalization becomes prevalent. “Some 71% of consumers now expect companies to deliver personalized interactions, and 76% get frustrated when this doesn’t happen. However, using basic segmentation to generate a customer’s first name with a meta tag (e.g., %FIRSTNAME%) is no longer impressive—customers expect it.

“At its core, hyper-personalization harnesses the power of AI to make the most of data to improve customer experience.

“Hyper-personalization in contact centers can take many forms. In one example, bots can track real-time conversations with customers and feed your agents prompts based on the customer’s unique experience or emotional needs.” - Charles Kergaravat, 5 AI-Powered Contact Center Automation Trends for 2024, Apizee; X: @apizee

3. Natural language processing continues to advance. “NLP is a machine learning technology that allows computers to interpret, manipulate, and comprehend human language. Through applications like chatbots, voice assistants, sentiment analysis, and automated transcription, NLP helps improve efficiency, customer satisfaction, and operational insights. Despite challenges in accuracy and contextual understanding, the advancements in NLP continue to be a significant driver for innovation and better service in contact centers.” - Laura Fitzgerald, 5 AI Trends for Contact Center Automation in 2025, Pindrop; X: @pindrop

4. Companies can now add empathy to interactions with AI. “When businesses use manual processes, customers can get frustrated due to slow workflows and an increase in errors. Automation can improve this productivity and reduce error risks.

“‘When you talk to a human, that human will have more information to personalize the experience for you, because the AI can look at previous interactions, start to see patterns, start to predict what somebody might be reaching out about, and equip that agent to deliver a better experience,’ Dhingra says.

“AI tools now listen in to voice or digital interactions, observe what is being typed and provide suggestions to agents on next steps, Martin says.

“Although customers get frustrated with bots at times and request a live agent, they are getting more efficient at helping with tasks that burn out agents. To improve CX using a bot, organizations must hand off a call to a human quickly after spending several minutes with a bot, Martin says.

“With the emergence of generative AI, contact center solutions can now add empathy to an interaction, according to Martin. For instance, once a gen AI tool for a bicycle brand learned that a customer was in a bike accident, it would say to the customer, ‘We’re sorry to hear you were in a crash, are you OK?’ Martin says.

Even so, as gen AI emerges to elevate CX, don’t expect it to replace humans altogether, Martin adds: ‘There's always going to be a place for a human in the system, but how efficient we can make that human, how productive, how happy we can make that customer, those are the questions to answer.’” - Brian T. Horowitz, Three Areas of Focus to Elevate the Customer Experience for All, BizTech Magazine; X: @BizTechMagazine

5. Agentic AI is a transformative approach to call center automation. “Whilst Gen AI has dominated headlines with its ability to create content and assist with tasks, a more sophisticated form of AI - known as agentic AI - is quietly transforming how businesses operate across sectors worldwide.

“In a report titled ‘Automation 2.0: The Rise of Intelligent AI Agents,’ research firm GlobalData has found compelling evidence that agentic AI is now becoming the cornerstone of enterprise automation strategies.

“This development marks an evolution from traditional automation approaches, offering organisations capabilities to navigate and optimise their operations in increasingly complex technological environments.

“Research like this proves important for businesses across the world as they grapple with mounting pressures to improve efficiency, reduce costs and enhance customer experiences in an increasingly competitive marketplace.

“What sets agentic AI apart from its predecessors, is its departure from conventional automation tools, equipped with advanced reasoning capabilities and the ability to act autonomously within defined parameters - characteristics that are proving invaluable across industries ranging from healthcare to financial services.” - Kitty Wheeler, How Agentic AI is Impacting Global Enterprise Automation, Technology Magazine; X: @TechnologyMagBC

6. AI enhances robotic process automation. “The AI-induced evolution of RPA from a tool for automating routine tasks to an intelligent system capable of handling complex operations marks a significant shift in business process management.

“‘This has led to smarter, end-to-end automation, reducing manual intervention and increased accuracy,’ Michael continues.

“The financial sector has been quick to adopt AI-augmented RPA, leveraging its capabilities to enhance accuracy, ensure compliance and improve speed in critical areas such as fraud detection and claims processing.

“Similarly, the healthcare industry has embraced this technology to manage patient records, streamline billing processes and automate diagnostic procedures, thereby improving efficiency and reducing errors.

“Beyond these back-of-house process automations, the synergy of RPA and AI has meant that RPA can now have a customer-facing role.” - Kristian McCann, RPA Meets AI: A Synergy Revolutionising Business Automation, AI Magazine; X: @AIMagazine_BC

7. Vertical AI agents offer specialized automation capabilities. “As the AI ecosystem evolves, a significant shift is occurring toward vertical AI agents — highly specialized AI systems designed for specific industries or use cases. As Microsoft founder Bill Gates said in a recent blog post: ‘Agents are smarter. They’re proactive — capable of making suggestions before you ask for them. They accomplish tasks across applications. They improve over time because they remember your activities and recognize intent and patterns in your behavior.’

“Unlike traditional software-as-a-service (SaaS) models, vertical AI agents do more than optimize existing workflows; they reimagine them entirely, bringing new possibilities to life.” - Rohan Sharma, We’ve come a long way from RPA: How AI agents are revolutionizing automation, VentureBeat; X: @VentureBeat

8. Innovative AI tools give companies flexibility and choice. “In addition to delivering a new look and feel to the existing CallMiner help bot, CallMiner AI Assist is built on an extensible orchestration framework that connects AI components and tools across the platform. This framework uses generative AI to improve user experience, including simplifying complex tasks, increasing efficiency, enhancing productivity and surfacing previously unknown business intelligence through conversational assistance. By providing the option for AI delegation, CallMiner AI Assist helps users get more value from the platform with less effort, while still delivering necessary oversight and control.

“Further, today’s organizations want choice when it comes to the underlying models that are used to provide insights. CallMiner has always focused on platform flexibility, and CallMiner AI Assist can be powered by different AI models based on the use case, ensuring the right model is used based on business needs.

“‘As an AI leader in the contact center and customer experience industries, CallMiner remains focused on delivering responsible, secure AI capabilities that drive tangible value and give our customers a competitive advantage,’ said Bruce McMahon, Chief Product Officer, CallMiner. ‘CallMiner AI Assist is now so much more than a help bot. It’s an intelligent, scalable solution that enhances platform ease-of-use, increases operational efficiency, and ensures organizations are getting even deeper insights from their customer interactions. By delivering an agentic AI framework that takes action and tracks value on behalf of users, CallMiner continues to set the bar for how AI is leveraged within conversation intelligence platforms.’” - CallMiner Introduces CallMiner AI Assist to Intelligently and Automatically Support In-Platform Actions, CallMiner; X: @CallMiner

Growing use cases for AI call center automation

9. Call centers explore various use cases for generative AI. “Generative AI is a technology that contact centers use to create content and converse with customers and agents using natural language.

Generative AI can be used to automate a number of common call center tasks, such as drafting follow up texts, creating promotional content, and responding to customer emails.

“Leveraging generative AI not only frees up agents to handle more complex matters, but it reduces human error and ensures that customer interactions are consistent, on brand, and in compliance with all company standards.

“Example: An online retail company could use generative AI to automatically create a personalized follow up email for every customer after a purchase is made. The AI can analyze the customer’s purchase history, identify tracking numbers and shipping information for the current order, and send a friendly, customized, and helpful message for the customer, just seconds after the purchase was made. This not only relieves stress on agents, but makes every customer feel valued.” - Rebecca Drew, Contact Center Automation Trends Shaping 2025, GetVoIP; X: @getvoipreviews

10. More call centers leverage generative AI for agent assistance. “Perhaps the most impactful automation trend is that of generative AI. Powered by large language models (LLMs), this type of artificial intelligence is uniquely adept at producing various forms of content, including original text, audio, and imagery.

“Gartner predicts that by 2025, 80% of customer service and customer support organizations will use it to improve agent productivity and CX. Why? Because the use cases are practically endless, and the technology is readily available.” - Caitlin Barrett, 10 contact center automation trends to look out for in 2025, Webex Ahead; X: @Webex

11. Healthcare companies turn to medical chatbots to automate routine tasks. “Medical AI chatbots are increasingly used to manage routine tasks, including appointment scheduling, patient onboarding and prescription refills.

“They can also help contact center employees manage complex patient cases more efficiently, Barave says. ‘Instead of agents struggling to read through all of their notes, generative AI tools are available today and can provide a quick summary of previous transcripts to improve interactions.’

“AI-powered chatbots are developing enhanced smart routing capabilities. For example, if a patient reaches out about neck pain, Cameron explains, the chatbot could direct them to the best specialist by asking questions and understanding the differences between pain caused by trauma and pain from an infection.” - Erin Laviola, Top Trends in Healthcare Contact Center Automation, HealthTech Magazine; X: @HeatlhTechMag

12. There’s an increased focus on robotic process automation (RPA). “Robotic process automation (RPA) replaces tier 0 and other simple interactions that are task-oriented and programmable. Rather than deploying individual bots for each task, a digital worker factory model trains a single intelligent virtual agent (IVA) to handle multiple use cases, and integrate that IVA into multiple channels for a single, consistent, omnichannel experience.” - Contact Center Automation: Tools and Trends for the Decade Ahead, TTEC; X: @tteclife

13. Process and task mining takes automation to the next level. “Business processes are another area that can gain from advances in AI and automation. The previous wave of automation in business processes was mostly driven by robotic process automation (RPA). While RPA has had a tremendous effect on productivity, like other solutions, it has limits too.

“RPA only addresses tasks that you think need automation. It can automate a poorly designed process but can’t optimize it. It also can’t handle tasks that can’t be defined through deterministic rules. This is where “process and task mining” enter the picture. According to Lobig:

“RPA executes scripts to automate what you tell it to do. It’s very deterministic and rigid in what it can do, automating highly repeatable tasks. Process and task mining find inefficiencies you can’t see.

“Process and task mining can answer questions such as, is your business really running the way you think it is? Is everyone completing processes in the same way? What should you optimize first? It helps you get past the low-hanging fruit and find the hidden inefficiencies of your business that can also be addressed with automation.” - Ben Dickson, Psst, automating these 3 parts of your business is the best thing you can do right now, The Next Web; X: @thenextweb

14. Companies develop a verbal brand identity. “Progressive marketers must be thinking conversation first, technology second. Tomorrow, your conversation will be your brand. Verbal identities will be just as important as your social or visual identity. The brands that will succeed will perfect and automate conversations across new channels – when and if the context requires it.

“They will create a human/hybrid intelligence. That means that conversational strategy will enable staff in call centres to act more human, by freeing them of menial legwork. In the same breath, advances in machine learning and AI will beget chatbot conversations that actually sound less robotic than an untrained human reading from a script.” - Conversations not chatbots: why automated conversations will be key to the customer experience, WIRED; X: @WIRED

15. AI provides a deep understanding of customers’ behavior. “Businesses are leveraging AI in their call centers to help agents get a deeper understanding of customers’ purchase and return histories, demographic characteristics, and even their moods in real time. They’re building chatbots for their websites that are capable of far more sophisticated interactions than what was possible just a few years ago. And they’re using AI in data analytics to anticipate customer preferences.

“AI is also revolutionizing the way work gets done. Today’s collaboration solutions are built with AI assistants that can summarize meetings or provide live subtitles or even translations into different languages. Modern productivity suites, such as those from Google and Microsoft, are leveraging generative AI too.” - Norm Lillis, How Should Small Businesses Take Advantage of Generative Artificial Intelligence?, BizTech Magazine; X: @BizTechMagazine

16. Call centers optimize their infrastructure with IT automation. “Previously, IT experts may have optimized their infrastructure through informed judgments and overprovisioning their resources. Now, they can take the guesswork out of their decisions by using AI to analyze the data of the IT infrastructure, find patterns, estimate usage, and optimize their resources.

“For example, J.B. Hunt, a logistics and transportation company, uses IBM Turbonomic software to automate the scaling of its cloud and on-premise resources. For their on-premises environment, J.B. Hunt is automating all non-disruptive actions 24×7 and scaling non-production actions during a nightly maintenance window.” - Ben Dickson, Psst, automating these 3 parts of your business is the best thing you can do right now, The Next Web; X: @thenextweb

The impact of AI call center automation on companies & the human workforce

17. AI doesn’t replace call center agents; it optimizes human interactions. “It’s important to note that automation via AI isn’t about replacing human interactions; it’s about optimizing them. In fact, a recent UJET report found that 78% of consumers still end up needing to connect with a human agent after a chatbot wasn’t able to resolve their issue. Through automating routine tasks and queries, organizations allow their human agents to focus on more complex and nuanced customer issues that oftentimes require empathy and problem-solving skills, which automation cannot provide.” - Alok Kulkarni, The Role Of Automation In Your Customer Experience Strategy, Forbes; X: @Forbes

18. AI drives economic growth. “Another key advantage of AI platforms is their ability to enhance customer experiences. Through advanced natural language processing and machine learning algorithms, these systems can power chatbots and virtual assistants that provide personalised, round-the-clock customer support. This not only improves customer satisfaction but also reduces operational costs associated with traditional support channels.

“Rosanne Kincaid-Smith, Group COO of Northern Data Group, notes the potential for AI to drive economic growth: ‘We've already seen how the power of AI can automate routine tasks, freeing up resources for other strategic initiatives in the business, and better personalise customer experiences. But now we're also seeing businesses monetise their data by offering up their insights as a service to other companies, creating new revenue streams and opening up opportunities for innovation.’” - Marcus Law, The Rise of AI Platforms: Transforming Business Operations, Technology Magazine; X: @TechnologyMagBC

19. Companies take a holistic approach to knowledge work. “It’s clear that the productivity of knowledge workers is critically important to the growth and profitability of any business. Since knowledge workers perform best in a state of flow – where they can be creative, think freely and solve problems – forward-thinking companies in 2024 will find ways to keep the flow state going.

“This year, we can expect organizations to approach knowledge work in a more holistic manner to increase the productivity of knowledge workers by embracing automation. Knowledge work automation helps eliminate information chaos and improve process efficiency, which reduces the amount of time-consuming manual tasks and frees knowledge workers to work smarter, add value and drive better customer experiences. In fact, in a 2023 analyst study, knowledge work automation was found to increase workflow efficiency by 70 per cent and document search by 50 per cent – a time saving that translated to a significant financial ROI of 294 per cent!” - Antti Nivala, Three Ways Knowledge Work Automation and AI Will Change the Way We Work in 2024, Bloomberg; X: @business

20. Call centers get a boost in productivity and profits with smart AI implementation. “The expected productivity and profit boost that automated tech could help deliver are already leading businesses to think about what they'll expect from their human employees as soon as this year.

“MIT's Sloan School of Management partnered with the Boston Consulting Group and found that generative AI can improve performance by as much as 40% for highly skilled workers compared with those who don't use it. Software engineers can code up to twice as fast using gen AI tools, according to studies cited by the Brookings Institute.

“LinkedIn surveyed CIOs, CEOs, data scientists, software engineers and other heavy data users and asked them to use generative AI to see how much time they saved on tasks such as drafting emails, analyzing text and creating documents. What they said is that tasks that would now take them 10 hours manually could take them five to six hours less. That translates into spending 50% to 60% less time on some routine tasks so you can instead devote attention to more rewarding or higher-value work.” - Connie Guglielmo, AI Chatbots Are Here to Stay. Learn How They Can Work for You, CNET; X: @CNET

21. AI elevates human performance. “Despite fears that AI could replace jobs, the CX Landscape Report found that most organizations are leveraging AI to empower their employees rather than replace them. Ninety percent of organizations believe AI will unlock their employees' full potential. This belief is reflected in the 43% of respondents who are using AI to automate repetitive tasks, allowing frontline agents to focus on more strategic, complex work.

“In addition to task automation, AI is playing a role in elevating employee performance. For example, nearly two in five organizations use AI-driven scoring to evaluate customer interactions and agent performance, while 46% employ AI-powered real-time guidance during live customer interactions. These tools are a critical part of boosting productivity, enhancing CX quality, and improving the frontline employee experience.” - Eric Williamson, CallMiner’s 2024 CX Landscape Report highlights AI’s shift from hype to strategic execution, CallMiner; X: @CallMiner

22. The role of agents is evolving. “Regardless of the part AI plays, the role of call center agents is evolving. The future of the call center will focus more on sales and revenue generation rather than its historic role of providing customer service. While automation can and should be optimized any and everywhere it can, AI is just not there yet for more complicated tasks.

“While chatbots can handle simple issues like refund requests or FAQs, agents are still required to produce higher-value exchanges. For example, given the parameters of each, unique customer situation, it would be very hard to train AI models when to upsell when the opportunity presents itself.

“This is why human agents, paired with AI augmentation, have the potential to revolutionize traditional customer service.” - Yishay Carmiel, AI Can Try, But Call Center Agents Aren’t Going Anywhere—Yet, Forbes; X: @Forbes

Potential issues & concerns in AI call center automation

23. Data privacy remains a significant concern. “As data collection continues to expand, it is crucial to establish protective measures for aggregating sensitive information and ensuring full transparency.

“The prohibition of specific applications under the Act is welcomed, such as AI systems employed for workplace emotion recognition and the untargeted extraction of facial images from the internet, or CCTV footage for the creation of facial recognition databases.

“The EU AI Act aims to enhance oversight of AI systems created and implemented within the EU. Those heavily dependent on AI, such as investors, developers, and businesses dealing with potentially high-risk AI systems, stand to gain from proactively conforming to regulations during the initial phases of AI system development. This approach also seeks to increase confidence in their systems.

“Ultimately, only through thoughtful regulation and conscientious development and implementation can we truly unlock the full potential of AI.” - Alex Adamopoulos, AI’s meteoric rise: boundless opportunities ahead, but implementation is key, The Next Web; X: @thenextweb

24. Potential biases in training data remain a concern. “One of the primary concerns with generative AI lies in its susceptibility to biases present in training data. If the data used to train these models reflects societal biases, the AI may inadvertently perpetuate and amplify those biases in its generated content. Addressing this issue is crucial to prevent AI systems from unintentionally reinforcing and spreading harmful stereotypes.” - This is the future of generative AI, according to generative AI, Engadget; X: @engadget

25. Call centers implement advanced security and privacy measures. “With the introduction of generative AI into the industry, and as contact centers collect and process vast amounts of sensitive customer data, security has become an increasing concern. Implementing advanced security protocols and ensuring compliance with data protection regulations will be critical to maintain customer trust and avoid legal repercussions.

“Eric Williamson, CMO at CallMiner, a cloud-based conversational analytics solution provider, told CMSWire that according to CallMiner’s 2023 CX Landscape Report, 45% of CX and contact center leaders said they’re concerned about AI exposing their company to security risks, 43% are worried about the technology spreading misinformation, and 41% are fearful of AI giving biased or inappropriate responses in CX and customer service use cases.

“Contact centers are poised to significantly bolster their data security and privacy measures, addressing the sensitive nature of customer information they handle. Enhanced encryption methods, crucial for protecting data both at rest and in transit, will see the adoption of more sophisticated algorithms. Along with this, the role of AI in threat detection will become more prominent, mirroring initiatives such as CISA's use of AI for security. AI's ability to swiftly identify and respond to security threats through pattern analysis and anomaly detection will be key in this endeavor.” - Scott Clark, 6 Contact Center Trends to Watch in 2024, CMS Wire; X: @cmswire

Transform your call center with AI automation in 2025 and beyond

As we look toward the future of AI in call center automation, it’s clear that the landscape will continue to evolve rapidly in 2025. The integration of AI technologies will not only enhance efficiency but also transform how businesses approach customer service, making it more personalized, efficient, and data-driven. Key trends, such as AI-powered hyper-personalization, natural language processing, and agentic AI, are already redefining customer interactions and workforce dynamics.

To stay competitive, organizations will need to embrace these innovations while ensuring they empower human agents rather than replace them, recognizing the unique value that both AI and human expertise bring to the customer experience. For example, a conversation intelligence solution like CallMiner delivers valuable insights from customer interactions across channels, providing next-best-action guidance to agents, automating QA, and more. Book a demo today to discover how to automate key business processes with the CallMiner platform.

Frequently asked questions

How does AI improve customer service in call centers?

AI improves customer service by providing quick responses, reducing wait times, automating repetitive tasks, and offering personalized support, leading to better customer experiences and higher satisfaction.

Will AI replace human agents in call centers?

While AI can automate certain tasks, human agents are still essential for complex inquiries, emotional support, and situations that require empathy or judgment. AI acts as an assistant, enhancing rather than replacing human agents.

What is hyper-personalization in AI call center automation?

Hyper-personalization uses AI to tailor interactions with customers based on data-driven insights, such as preferences, behavior, and past interactions, offering a more individualized and relevant experience.

How does AI affect the productivity of call center agents?

AI boosts productivity by handling repetitive tasks, providing real-time data and insights, automating responses, and assisting with complex queries, allowing human agents to focus on higher-value interactions.

What is agentic AI and what is its role in call center automation?

Agentic AI refers to AI systems designed to act as virtual agents, performing tasks such as answering questions, processing orders, and resolving issues autonomously, while assisting human agents when needed.