Feature
The Gist
- Big improvements. AI enhances call centers with real-time analytics and improved customer experiences.
- Streamlined tasks. Conversational AI and IVR systems streamline and personalize customer interactions.
- Higher satisfaction. Predictive behavioral routing matches customers with compatible agents, boosting satisfaction.
Editor's Note: This article was updated April 16, 2025, to include new data and information.
AI call center technology is rapidly transforming how businesses handle customer service. In 2025, AI call center platforms are poised to dominate by providing real-time feedback, predictive analytics and in-depth analysis.
AI call center technology is AI call center technology is enhancing the customer experience while improving the daily workflow for agents. This article will explore how call center AI is changing the game when it comes to call center dynamics.
Table of Contents
- Interactive Voice Response (IVR) in the Call Center
- AI's Rapid Evolution in Call Centers
- AI Is Set to Enhance Customer Experience
- Conversational AI and the Call Center
- Predictive Behavioral Routing
- The Future of Contact Center AI
- Core Questions About AI in the Call Center
Interactive Voice Response (IVR) in the Call Center
Most of us are familiar with IVR when calling customer service centers, and have found them to be annoying, time-consuming and not very helpful. Most consumers are used to the ubiquitous, robotic voice saying, "Press 1 for Spanish, 2 for English,” and so on. It’s gotten to the point where, when the first prompt is heard, the caller just keeps pressing zero to speak with a live customer service agent before getting trapped in a maze of repeating, endless frustration. Still, when IVRs first came out, they served a purpose and saved customer service agents a lot of time, even if they didn’t do much to improve the customer experience.
Since then, the situation has greatly improved, largely through the use of AI call center platforms. IBM’s natural language understanding (NLU) software was used to create an AI-enabled system that is able to provide real answers to the questions that customers ask. IBM partnered with Humana, a healthcare insurance provider, in collaboration with IBM’s Data and AI Expert Labs & Learning (DAELL), and created what became the Provider Services Conversational Voice Agent with Watson. The unique solution combines multiple Watson applications in a single conversational assistant and runs on the IBM cloud, while the Watson Assistant for Voice Interaction runs on location at Humana.
The voice assistant features seven language models and two acoustic models, each of which is targeted towards a specific type of user data. This solution achieves an average of 90-95% sentence accuracy, and is able to handle several sub-intents within the major groupings of eligibility, benefits, claims, authorization and referrals. This allows Humana to more quickly provide answers to questions that were not answerable before. The previous IVR system was likely to produce a seven-page fax in response to a request for “benefits,” while the new solution can respond with a specific point benefit using natural language, such as “the co-pay for optometrist visits is USD 75.”
Evolution of IVR Systems in AI Call Centers
AI has revolutionized traditional IVR systems, transforming them from static voice menus into responsive, conversational platforms that improve efficiency and customer experience.
| IVR Generation | Description | Impact on CX |
|---|---|---|
| Traditional IVR | Scripted prompts and static menus (e.g., "Press 1 for sales") | Frustration from limited navigation and poor personalization |
| AI-Powered IVR | Natural language understanding (NLU), contextual awareness and dynamic response handling | Faster resolutions, higher accuracy, improved caller satisfaction |
The evolution of IVR systems highlights how call center artificial intelligence is turning static menus to dynamic, conversational interfaces, reducing the need for customers to navigate complex IVR trees or seek immediate human assistance.
Related Article: What Is a Call Center? How They Work
AI's Rapid Evolution in Call Centers
The pandemic forced businesses to rethink their approach to both employees and customers—accelerating adoption of AI contact center technology environments especially as call centers transitioned to remote work.
Magnus Geverts, VP of product marketing at Calabrio, described 2020 as "the year of reinvention," with AI-based solutions playing a critical role in maintaining operations and empowering employees. Similarly, Shawna Wolverton, chief product officer at Benchling, noted that record-high ticket volumes during the pandemic drove businesses to accelerate their adoption of AI call center chatbots to address common customer queries efficiently.
As the AI call center market continues to grow, vendors are racing to deliver integrated solutions that combine advanced analytics, real-time feedback, and intuitive agent tools.
Healthcare call centers, under immense pressure to manage vaccination efforts, quickly integrated AI to automate repetitive tasks like answering vaccine-related questions and scheduling appointments. Wolverton emphasized that call center AI solutions also enabled trend detection and improve resolution times through natural language processing and predictive analytics. And with businesses under pressure to do more with less, AI call center software has become a key driver of both efficiency and resilience.
AI Is Set to Enhance Customer Experience
Barry Cooper, president of the NICE CX division, told CMSWire that AI contact center software will soon automate most customer interactions — efficiently resolving issues, offering proactive support and even driving upsell opportunities.
"Businesses will not only benefit from reduced operational costs but will also unlock new revenue streams through personalized AI-driven engagements," Cooper said. "The shift will be transformative, with AI enhancing both customer satisfaction and the bottom line, as contact centers evolve into critical revenue-generating hubs."
Although the time, cost savings and potential profit from call center AI and automation hold tremendous value for brands, the potential returns for improving the customer experience are even bigger and more meaningful. "From providing near real-time feedback on customer and employee insights and stress predictors to voice-of-the-customer innovations, AI-driven analytics can quickly analyze the sentiment of customer interactions equipping contact centers with the visibility they need to help optimize the customer experience," Geverts related.
Seamless, hyper-personalized experiences across all channels are becoming table stakes for modern customer expectations. AI call centers, where AI provides human agents with real-time decisioning and actionable insights, enable agents to create the “next best” action for every interaction. These systems increasingly incorporate predictive analytics and generative AI to suggest personalized responses or identify customer needs before they’re expressed.
AI isn’t just improving customer experiences — it’s also enhancing the daily experiences of employees, making their roles more productive, engaging and fulfilling. “The first thought that often comes to mind when people think of AI is chatbots or intelligent assistants. Yet this is more than just a customer-facing trajectory,” Geverts noted. “Employee-facing self-service powered by AI is a key initiative to embrace and help agents simplify their day, provide information during interactions or assist with training and development while improving work-life balance — all of which goes a long way to ultimately improving CX.”
Improving the employee experience is also key to enhancing and improving the customer journey. “The old adage of happy employees make happy customers remains true. Forward-thinking organizations are using, and should use, AI-powered self-service to maintain loyal customers and empower employees,” said Geverts.
According to Cooper, this shift will also greatly impact the roles of customer experience professionals. “In 2025 and beyond, the focus of human involvement will shift towards overseeing AI performance, ensuring seamless AI-human collaboration and fostering deeper customer relationships. CX professionals will take on strategic roles, managing AI oversight to maintain service quality and accuracy, while also dedicating more time to customer relationship management and complex issue resolution.”
Cooper emphasized that this transformation will elevate the importance of customer experience roles, making them integral to sustaining brand loyalty and driving business growth.
Related Article: 29 Call Center Metrics That Drive Customer Satisfaction
Conversational AI and the Call Center
Conversational AI enables a brand’s artificial intelligence call center to fully or partially automate conversations on messaging channels—creating faster, smarter, and more scalable customer service. AI-powered messaging played a large role in many brand’s pandemic responses, which was simply the acceleration of a trend that had already begun, according to Rob LoCascio, CEO of LivePerson.
LoCascio said that AI call centers enabled brands with no set infrastructure in place to immediately begin to improve the customer service experience even as more and more lockdowns shuttered businesses.
“The technology not only empowered businesses to communicate with customers as physical locations shuttered but gave them the ability to do so on a mass scale. Decreasing wait times while increasing volume allowed business to foster stronger relationships with an expanded network of customers,” explained LoCascio.
Key Benefits of Conversational AI in Call Centers
Conversational AI platforms enhance communication by automating customer interactions across messaging channels while enabling deeper personalization and scale.
| Benefit | Description |
|---|---|
| 24/7 Support | Available anytime to reduce wait times and manage high volumes |
| Personalized Experiences | Uses AI to tailor interactions based on user behavior and preferences |
| Scalability | Manages thousands of conversations simultaneously |
Going forward, these relationships will continue to be developed through the use of AI call center platforms that can personalize communication at scale. “As call centers are now familiarized with conversational AI-powered technology they’ve gained a deeper understanding of its true business potential, not only as a tool to cut losses, but as one to drive revenue,” said LoCascio. Over the course of the next year, he envisions call centers using the technology in a variety of new ways. “Now that many have mastered their process for customer service, we’ll start to see more utilization across marketing and sales practices, from providing tailored product recommendations, to increasingly customized conversations based on consumer intents, to in-messaging purchases.”
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Consumers have been getting more accustomed to using AI-powered customer service. The Forbes 2024 customer service and CX research report revealed that 27% of customers believe that self-service or automated customer support using AI-powered technology can deliver as good of a customer contact center experience as a live agent, a number that will continue to increase as the technology matures. For brands’ call center agents, conversational AI allows them to focus their time and energy on more interesting, complex issues while automation takes care of repetitive tasks.
Using the proper tools, LoCascio told CMSWire that brands are even able to elevate future conversations by analyzing call center KPIs. David’s Bridal offers a strong example of successful AI integration in its call center. Faced with the challenge of maintaining business continuity during a period of retail closures, the chain acted quickly to support its brides and employees through artificial intelligence call centers.
David’s Bridal’s concierge bot, Zoey, became a key part of the brand’s strategy, helping drive ecommerce revenue by simplifying repetitive tasks for customers. “This is an example of how conversational AI can make routine interactions more convenient for customers while enabling employees to focus on providing value in complex situations,” said LoCascio. Zoey served as a fully automated AI call center agent, managing routine inquiries while supporting ecommerce efforts during peak times.
Edward Tian, CEO at GPTZero, said that one of the biggest focuses that AI developers have had over the past year has been to make AI more conversational, and he believes a big reason for this is because that’s what lots of businesses have expressed a desire for. "From a business perspective, the customer experience is extremely important,” said Tian. “When AI is used in customer-facing ways, businesses want to be able to use it in ways that then boost the customer experience, and the idea has been that when AI is more conversational, that will improve CX because it will make customers feel like they are talking to real people. Whether or not that’s having the desired results, this focus on conversational AI has thus been significant for developers over the past year."
Predictive Behavioral Routing
Predictive behavioral routing (PBR) leverages AI and analytics to match call center customers with agents whose communication styles are most compatible with the caller's personality. Initially introduced by Mattersight Corporation in 2014, the concept gained significant traction when NICE Nexidia acquired Mattersight four years later, enhancing the system with advanced interaction analytics and a vast database of customer behavioral profiles.
Today, PBR is evolving as a key tool in delivering personalized customer experiences by turning what would otherwise be random call assignments into tailored interactions. By analyzing the natural predispositions and communication habits of both customers and agents, PBR ensures more seamless and positive exchanges. Modern PBR solutions integrate with CRM software, IVR systems and skills-based routing to provide agents with the most relevant data in real time, enabling faster resolutions and greater customer satisfaction.
How Predictive Behavioral Routing (PBR) Enhances Agent Matching
PBR leverages AI to align customer personalities with agent communication styles, improving outcomes and satisfaction.
| Feature | Function | Customer Impact |
|---|---|---|
| Personality Profiling | Analyzes historical behavior and tone | Ensures better agent alignment and rapport |
| Skill-Based Routing Integration | Combines personality and technical skill matching | Faster resolutions, improved satisfaction |
PBR is increasingly being integrated with artificial intelligence call center software such as real-time sentiment analysis, natural language understanding (NLU), and omnichannel journey mapping. These developments promise to enhance its predictive accuracy and enable smoother transitions across digital and voice channels. As customer expectations for personalization grow, AI in the contact center will move beyond automation to enable meaningful, human-like conversations informed by behavioral insights.
Related Article: 5 Ways Artificial Intelligence Boosts Contact Centers
The Future of Contact Center AI
AI vs Human Agent Roles in AI Call Centers
Understanding where AI excels and where human agents are essential helps build a balanced, efficient customer service strategy.
| Task | Handled Best By | Why |
|---|---|---|
| Routine Inquiry Resolution | AI | Fast, scalable and always available |
| Emotional or Complex Issues | Human Agent | Requires empathy, judgment and adaptability |
| Real-Time Escalations | Hybrid | AI flags issues, human resolves with context |
With the emergence of contact center AI software and increasingly sophisticated call center artificial intelligence tools, brands are discovering new ways to serve customers with empathy, speed, and precision. AI has transformed call centers into hubs of personalized, efficient customer interactions. From conversational AI resolving simple queries to predictive behavioral routing and AI-enhanced IVR systems streamlining complex issues, these technologies empower agents and enhance experiences. As the artificial intelligence call center continues to evolve, call centers are becoming central to proactive, hyper-personalized customer engagement.
Core Questions About AI in the Call Center
Question: What is the role of artificial intelligence in modern call centers?
Artificial intelligence in call centers plays a critical role by automating routine tasks, enhancing customer-agent interactions, and providing real-time insights. From IVR to predictive behavioral routing, AI-powered call center solutions help businesses improve efficiency, reduce costs, and deliver more personalized customer experiences.
Question: How are contact center AI solutions transforming customer service in 2025?
Contact center AI solutions are transforming customer service by enabling self-service, real-time sentiment analysis, and conversational AI that mimics human interaction. These tools not only improve response times and customer satisfaction but also empower agents with data-driven insights to handle complex issues more effectively.
Question: Will AI replace call center agents?
No, AI isn’t replacing call center agents—it’s helping them. While AI can handle routine tasks like answering FAQs or summarizing calls, human agents are still essential for handling complex issues, building rapport, and showing empathy. The future of contact centers is a hybrid model where AI supports agents, not replaces them.
Question: What is contact center AI?
Contact center AI refers to technologies that use artificial intelligence to improve customer service operations. This includes virtual agents, real-time coaching tools, sentiment analysis, automated call summaries, and intelligent routing systems—all designed to make customer support faster, more personalized, and more efficient.
Question: How does AI work in the call center?
AI in the call center works by analyzing voice or chat interactions in real time to support agents and automate repetitive tasks. It can suggest responses, detect customer sentiment, summarize conversations, and even alert supervisors if an agent needs help. AI helps reduce agent workload while improving the customer experience.
Question: What are the key features to look for in AI call center software?
Top features to look for include real-time agent assist, conversation summarization, sentiment analysis, intelligent routing, and integration with CRM or ticketing systems. Strong AI tools also offer analytics dashboards, compliance support, and the ability to escalate complex issues to a human when needed.
