AI call center: A complete guide

Customer service technology has come a long way from the oldest documented customer complaint inscribed on a more than 3,700-year-old clay tablet. Now, businesses are utilizing AI models that use machine learning to create human-like, conversational interactions. Though documenting complaints has come a long way from that clay “ticket,” it’s still just as important to meet and exceed customer expectations.

Thankfully, implementing AI technology with call center software makes delivering an exceptional customer experience easy. Our guide details the benefits, best practices, trends, and ways to use AI call center tools for voice and digital channels.

More in this guide:

• AI’s emergence in contact centers
• Benefits of using AI in a call centers
• Different ways to use AI in contact centers
• Best practices for implementing AI in call centers
• Call center AI trends for 2024
• Frequently asked questions
• Make the right call with AI

AI’s emergence in contact centers

Traditional contact centers continue to keep up with evolving technologies. The rise of artificial intelligence, most notably generative AI, has transformed customer service operations in contact centers. Businesses are now implementing AI within their voice solutions to:

• Summarize calls to save agents time and boost productivity
• Transcribe and analyze calls to assist in agent training and development
• Direct customers to digital channels to reduce call volume

Integrating AI into call center software for small businesses, startups, and enterprises helps companies of any size or industry deliver more efficient customer service experiences. Using machine learning, natural language processing (NLP), and automation technologies, AI’s potential is seemingly limitless.

Benefits of using AI in a call centers

Implementing AI with your call center software benefits customer service teams and their customers. Here are a few notable examples.

Increase customer satisfaction

According to the Zendesk CX Trends Report 2024, 81 percent of consumers say the quick and accurate resolution of issues or complaints heavily influences their decision to purchase. AI in call centers enhances customer satisfaction by helping teams offer faster support.

For example, call center teams can deploy a chatbot to support customers over digital channels while call center representatives are off the clock. AI can also generate a summary after each call, saving agents valuable time from manually summarizing calls so they can help the next customer faster.

Boost agent efficiency and productivity

AI and automation can handle routine, time-consuming tasks—such as call routing—freeing agents to focus on more complex and high-value interactions. For example, on average, call center agents spend 10.2 minutes out of one hour (17 percent of their time) working on post-call wrap-up. With Zendesk, AI can automatically summarize calls and create call transcripts so agents can save that valuable time after calls for other tasks.

AI-powered tools like these enhance customer service teams’ ability to provide fast, efficient, and accurate solutions and improve agent productivity.

Scale operations and reduce call center costs

Our CX Trends Report found that 71 percent of organizations use digital channels primarily for first contact and the phone as the primary channel for resolving complex customer issues or escalations. In fact, consumers rank the phone as the top preferred channel for nuanced problems.

AI can help support teams scale by directing customers to digital channels for quick questions and straightforward requests. This can also reduce call center overhead costs, as digital channels are typically more cost effective than the phone.

AI in contact centers even accelerates agent onboarding, reducing costly training time. AI-powered transcriptions enable managers to perform quality control on calls and train new agents. For example, AI-powered tools—like Klaus—automate QA by reviewing and analyzing interactions, pinpointing areas for improvement, and automatically sending personalized feedback surveys. AI can also provide agents with guidance by offering real-time suggestions on how to resolve an issue.

Predict future workload volume and ensure superior quality

AI in contact centers can gather and analyze historical data to forecast future trends, customer behaviors, and potential challenges. For example, call center workforce management tools (WFM)—like Tymeshift—leverage AI to predict:

• Future workload volume

• Required staffing

• Shift scheduling

These AI-powered WFM insights help call centers proactively refine resource allocation and create strategies that increase agent satisfaction.

Additionally, call center quality assurance tools use AI to proactively analyze agent interactions, pinpoint conversations with positive or negative sentiment, identify customer churn risk, and more.

Different ways to use AI in contact centers

CX leaders are continuously finding new ways to use AI in customer service. Here are a few of the most common ones.

Enhance self-service and knowledge management

AI enhances customer self-service and knowledge management, significantly reducing call volume. Implementing AI knowledge base software allows customers to quickly access accurate information and troubleshoot common issues independently while streamlining knowledge management for your call center team.

For example, Zendesk Content Cues can review support conversations to flag help center content gaps and identify articles that are outdated. Zendesk generative AI tools can also help support teams write self-service content by turning a few bullets into a comprehensive article or changing the tone for consistency.

Reduce call times with intelligent routing

AI can also reduce call times using intelligent routing. AI analyzes the request and directs the customer to the best-suited agent based on skill, expertise, language, or previous interactions. This prevents transfers and minimizes customer wait times.

Perform call quality control

AI helps with call quality control to enhance call monitoring, uncover insights, and facilitate agent training. Here are a few ways to perform call quality control with AI:

• Analyze call transcription: AI generates accurate call transcripts, allowing managers to comprehensively review interactions and identify areas for improvement in agent-customer conversations.
• Gather insights: AI-powered analytics assess call transcripts at scale, revealing trends, common issues, customer preferences, and customer sentiments. Managers can make data-driven decisions for process enhancements based on these call center metrics and key performance indicators (KPIs).
• Assess agent performance: AI-driven algorithms evaluate calls based on customer service goals and benchmarks. This information helps managers determine areas of improvement and whether additional call center training is needed.

AI-powered call transcript analysis empowers call center managers to conduct thorough quality assessments, extract actionable insights, and tailor training programs effectively to improve agent performance and customer satisfaction.

Reduce call wrap-up times

AI can significantly reduce the amount of time agents spend on call wrap-ups by automating two tasks: summarizing tickets after calls and providing full transcriptions.

AI-powered systems can listen to call recordings in real time or post call and generate accurate call summaries based on the conversation. Utilizing NLP, AI algorithms analyze the conversation content, identifying key points, topics discussed, and important details. Based on the analysis, AI generates a concise summary highlighting crucial information, such as customer complaints, resolutions, action items, and any required follow-up.

Call transcription tools use AI to convert spoken conversations into written text, providing a full transcription of each call. AI can transcribe recorded calls or do it in real time. Both generative AI summaries and conversation transcripts are automatically added to the customer conversation, saving agents the time and effort of manually summarizing each call.

Detect customer sentiment

AI in call centers can detect customer sentiment through NLP algorithms that analyze verbal cues, tone, and language patterns in real-time or recorded conversations. Simply put, AI can detect how customers or employees feel during interactions. It can determine positive, negative, or neutral sentiments, enabling agents to gauge situations, respond effectively, adjust their tone, or escalate interactions when dealing with angry customers.

AI can automatically escalate the interaction when a strong negative sentiment is detected. These escalations may include:

• Alerting a manager of the customer’s sentiment, allowing the manager to listen in on the interaction and support the agent.

• Escalating the interaction to a team lead or senior agent with more expertise, a better-suited department, or an appropriate manager to handle the issue.

This results in faster, proactive support so you can diffuse the situation for a better customer experience.

Best practices for implementing AI in call centers

Adding AI to your call center doesn’t have to be stressful. You can choose an AI as a service (AIaaS) company—a third-party vendor that handles the AI technology for a subscription price—or you can do it yourself. Here are the top five best practices for implementing AI in call centers.

Following these best practices enables call centers to effectively implement AI solutions, maximize their benefits, and drive improvements in customer service, operational efficiency, and overall business performance.

Call center AI trends for 2024

What’s next for AI in call centers? Glad you asked. Here are a few trends to expect in 2024.

Voice and live human interaction still play an important role

Businesses have changed how they help customers. Now, it’s all about digital methods—like chatbots, messages, and emails—instead of using old-school call centers. However, customers still want real people to talk to, especially when things get tricky.

When customers hop on a phone call, they want things sorted out fast. But sometimes, they get passed around, or agents don’t know the context of the situation, causing customers to repeat the same information. To fix this, CX leaders plan to combine phone systems with AI tools, enhancing the original communication channel with conversational AI without sacrificing experiences with live agents.

71% of organizations use digital channels primarily for first contact and voice for resolving complex customer issues or escalations.Source: Zendesk Customer Experience Trends Report 2024

Predictive agent management tools are on the rise

CX leaders often look for new ways to predict staffing needs and accelerate training now and in the future. With AI, you get innovative tools that make this less of a guessing game. These tools can provide insight into how many people to hire and how to train them better.

AI tools can also predict how many agents to have on staff to make customer interactions smoother and faster, reducing wait times and stress. They not only help improve customer service, but they can also increase ROI from optimized staffing forecasts.

69% of CX leaders say that forecasting future labor requirements accurately remains a significant challenge.Source: Zendesk Customer Experience Trends Report 2024

Immediacy and real-time engagement rule customer service

Customers demand more than an average customer service experience. They want fast, engaging, and personalized support, and the standard is the same whether they are receiving support over the phone or a digital channel.

Customers no longer accept call center experiences where they are put on hold or passed between different departments. They expect call center agents to have access to their previous support conversations and any other details to resolve the issue quickly and effectively.

Imagine a buyer calls customer support and asks a question about a previously purchased product. Call centers with AI and automation tools can route the customer to the right product department and surface customer profiles—including order history—to empower agents to provide faster, personalized support.

80% of consumers expect chat agents and support representatives to assist them with everything they need.Source: Zendesk Customer Experience Trends Report 2024

Frequently asked questions

Make the right call with AI

AI contact center tools make it easy for your business to handle more conversations and provide exceptional customer experiences without adding staff. With features like generative AI, AI-powered chatbots, call summaries and transcriptions, and data-driven insights, you can take your CX to a whole new level.

Zendesk boasts all those features and more. We already specialize in CX, so adding call center AI to our toolset made perfect sense. With AI for customer service, you get AI-powered knowledge management, intelligent routing and triage, and sentiment analysis—everything you need to level up your call center. Start a free trial of Zendesk today.