Gone are the days when customers simply called or emailed a company for support. Today’s customers expect a seamless, omnichannel experience where they can engage with a brand through multiple digital channels, such as text, chatbots, and social media. And as 76% of consumers say poor customer service negatively impacts their perception of a business,1 ensuring you deliver the best possible digital experience is vital to staying competitive.
Unfortunately, this shift in customer preferences has left many companies struggling to keep up. Some business leaders are hesitant to adopt new technologies designed to improve the customer experience (CX), while others need more knowledge or resources to upgrade their technology systems. But one solution has gained a lot of attention lately, and it has the potential to improve CX – while reducing costs and increasing efficiency.
That solution is artificial intelligence (AI).
In this blog, we’ll explore how businesses are delivering better customer service by using AI in the call center, and how you can harness its benefits.
Key Takeaways
- AI is reshaping call centers by improving omnichannel support and helping teams meet rising customer expectations, with poor service still hurting brand perception for many consumers.
- Top AI uses include conversational AI (chatbots), sentiment analysis, predictive analytics, smarter routing, and modern AI-powered IVR that reduces friction and repeat questions.
- Benefits for enterprises: higher efficiency, lower costs, 24/7 coverage, deeper insights, personalization, easier scaling, and more consistent service across channels and departments.
- Behind the scenes, AI helps teams run better through agent assist, automated QA and wrap-ups, and workforce forecasting that improves staffing, performance, and agent wellbeing.
How Artificial Intelligence Is Transforming Contact Centers
The call center AI market is expected to reach $4.1 billion by 2027,2 so it’s likely no surprise that many call center providers have already implemented AI capabilities into their platforms. The top ways call centers currently use AI include:
Conversational AI
Conversational AI is typically seen in the form of chatbots, which are AI-powered tools that can automate routine tasks such as answering commonly asked questions, providing account information, and even handling basic support requests.
You’ve probably interacted with a chatbot or two over the past few years, as they’ve become increasingly popular tools for self-service. 88% of online customers had at least one conversation with a chatbot in 2022,3 with around 70% reporting a positive experience. Since they allow customers to engage with websites quickly and use self-support options, chatbots reduce wait times, free up agents to focus on more complex issues, and provide access to support 24/7.
Predictive Call Analytics
AI technologies can analyze call data to identify patterns in customer behavior and predict customer needs before they arise. This allows call centers to offer proactive solutions, reducing the number of support requests and improving customer satisfaction. And since AI measures factors like tone, sentiment, and personality, it can deliver more in-depth analytics than any call center manager ever could.
Emotional Intelligence AI
Emotional intelligence AI uses natural language processing (NLP) and machine learning to identify customer emotions during calls. Also known as sentiment analysis, this tool can provide customer service representatives with real-time insight into how the customer feels throughout the call and what steps they can take to improve the interaction.
A 2022 survey found that 72% of consumers believe they would have better experiences if customer service reps used AI technology to improve their conversational skills in real-time.4 Clearly, sentiment analysis will grow as more companies strive to improve customer service.
Predictive Call Routing
Predictive call routing uses AI to match a call center customer to the specific customer service agent best able to handle the issue, not just based on the department but also on factors like personality, communication style, and expertise. AI software can gain a comprehensive understanding of the customer journey by analyzing customer behavior profiles, enabling the call center to offer hyper-personalized service.
Interactive Voice Response
As one of the earliest call center automation tools, interactive voice response (IVR) tools have been in use for years. However, IVR saw renewed interest as organizations responded to the COVID-19 pandemic: 33% of companies adopted the technology for the first time, and 42% of companies already using IVR increased its use.5
You’re likely already familiar with using IVR systems for customer support. It’s the pre-recorded voice that asks questions when you call a business, such as your name, account number, etc. You’ve probably also had a negative experience using IVR where you were forced to repeat the information. Luckily, this technology has come a long way with advances in AI, paving the way for advanced IVR solutions that improve customer satisfaction and help businesses reduce call center costs.
AI-Powered Quality Assurance & Call Wrap-Up Automation
Quality assurance (QA) is essential for consistent customer service, but traditional QA processes can be time-consuming and limited in scope. AI helps call centers scale QA by automatically transcribing conversations and highlighting key moments that matter, such as escalations, compliance statements, or signs of frustration.
AI-powered tools can also assist with call wrap-up by generating summaries, tagging common topics, and pre-populating fields in the CRM or ticketing system. Agents spend less time on after-call work and more time helping the next customer. For managers, AI-enabled QA provides a fuller picture of performance across the entire contact center, making it easier to maintain standards, fine-tune scripts, and recognize high-performing team members.
How AI Supports Agents & Supervisors Behind the Scenes
AI isn’t just transforming customer-facing experiences, it also gives agents and supervisors powerful tools behind the scenes. AI-powered assistants can “listen” to live interactions and surface relevant articles, previous tickets, and recommended next steps in real time so agents don’t have to search across multiple systems while a customer is waiting.
Supervisors can use AI-driven insights to identify coaching opportunities faster by spotting common blockers, recurring knowledge gaps, or patterns in sentiment across teams. Instead of manually reviewing a handful of calls, they can see trends across channels and guide agents with targeted feedback. The result is a more confident, better-prepared team that can resolve issues quickly while maintaining a human, empathetic touch.
Key Call Center AI Benefits for Enterprises
Thanks to its wide range of capabilities, there are several advantages to implementing AI technologies in your call center. Some of the most significant benefits include:
Increased Efficiency
Cost Savings
24/7 Availability
Advanced Insights
Personalization
Scalability
Consistency
Using AI for Workforce Forecasting & Smarter Staffing
Predicting Demand Across Channels
AI-enabled forecasting can analyze historical interaction data across voice, chat, SMS, email, and social media to anticipate when customers are most likely to reach out. By identifying recurring peaks, seasonal trends, and channel preferences, contact centers can prepare in advance instead of reacting to sudden spikes in demand.
Aligning Staffing With Customer Needs
With better forecasts, call centers can align staffing levels to real-world demand. AI helps teams determine how many agents are needed per shift, which skills are required, and where to allocate resources across channels. This makes it easier to maintain service levels while controlling costs, rather than overstaffing during slow periods or stretching teams too thin during busy times.
Supporting Agent Wellbeing & Performance
Smarter staffing doesn’t just benefit customers, it also supports agent wellbeing. When workloads are balanced and queues are under control, agents are less likely to burn out and more likely to deliver high-quality service. Combined with AI-powered insights into handling time, sentiment, and complexity, leaders can build schedules that respect agent capacity while meeting customer expectations.
Real-World AI Call Center Use Cases
High-Volume Customer Support Teams
For high-volume support environments, AI helps by deflecting routine inquiries to self-service options like chatbots and intelligent IVR. Customers can check order status, reset passwords, or update account information without waiting in a queue, while complex cases are automatically routed to the right agents. This combination reduces wait times, increases first-contact resolution, and keeps queues manageable during peak periods.
Regulated Industries & Complex Inquiries
In industries such as healthcare, financial services, or government, AI-powered analytics and sentiment detection help agents handle sensitive conversations with greater consistency. Real-time prompts can surface compliance reminders or relevant knowledge articles during interactions, while detailed transcripts make it easier to document outcomes and support audits. This improves both the customer experience and the organization’s ability to meet regulatory requirements.
Growing Mid-Market Businesses
As mid-market organizations scale, they often face enterprise-level customer expectations without enterprise-level resources. AI-enabled call centers bridge that gap by providing advanced analytics, intelligent routing, and automation in a cloud-based platform. These businesses can add new channels, onboard agents, and support larger customer bases without rebuilding their infrastructure or significantly increasing headcount.
How UniVoIP Can Help With AI In Call Centers
AI-enabled call centers have the power to revolutionize the customer service industry, from providing more self-service options to personalizing each interaction and beyond. And as AI technology continues to advance, you can expect to see even more improvements in call center operations. By embracing AI, companies can provide the best possible service to their customers – now and in the future.
If you’re ready to deliver a seamless digital experience to your customers, UniVoIP can help. Our cloud contact center solution takes call centers to the next level with AI-enabled features, such as IVR routing, real-time analytics, forecasting, and more. Use our platform to standardize interactions across every touchpoint, including web chat, SMS, email, social media, voice, and self-service. Contact the UniVoIP team today to get started.
AI Call Center FAQs
Will call centers be replaced by AI?
Not completely. AI will automate more routine work (simple questions, basic tasks, triage, and routing), but human agents will still be needed for complex issues, high-emotion conversations, exceptions, and relationship-driven support. The most common model is a hybrid contact center, where AI handles the repetitive layer and humans focus on the cases that need judgment and empathy.
How does AI improve omnichannel customer experiences?
AI connects data from voice, chat, SMS, email, and social media to build a unified view of each customer. This allows your teams to see context from previous interactions and maintain continuity as customers move between channels. With this visibility, AI can recommend the next best action, maintain consistent responses, and support a seamless experience across touchpoints.
Can smaller teams benefit from AI in the call center?
Yes. Smaller teams often feel the impact of high volumes and manual processes more acutely. AI-enabled self-service, intelligent routing, and automated summaries help small teams serve more customers without sacrificing quality. By reducing repetitive tasks and after-call work, AI allows each agent to handle more meaningful conversations in less time.
How quickly can businesses see results from AI in the call center?
Timelines vary, but many organizations see improvements in metrics like average handle time, self-service usage, and first-contact resolution within a few weeks or months of implementation. Starting with clearly defined goals and a focused set of use cases helps accelerate time-to-value and makes it easier to measure impact.
Sources:
- https://www.replicant.com/blog/survey-the-effects-of-bad-customer-service-and-how-brands-can-fix-it/
- https://www.marketsandmarkets.com/PressReleases/call-center-ai.asp
- https://financesonline.com/call-center-trends/
- https://www.businesswire.com/news/home/20230131005091/en/73-of-Consumers-Believe-AI-can-have-a-Positive-Impact-on-their-Customer-Experience
- https://financesonline.com/call-center-trends/
- https://www.cxtoday.com/wfo/gartner-bots-cut-agent-labor-costs-80bn/
- https://www.salesforce.com/content/dam/web/en_us/www/documents/research/salesforce-state-of-the-connected-customer-fifth-ed.pdf