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AI call center: How voice and digital channels are changing CX

Implementing AI call center solutions helps businesses increase customer satisfaction, boost team productivity, and scale operations.

Ultimo aggiornamento December 17, 2024

An individual wearing a headset and sitting at a desk while working in an AI call center.

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, AI in customer service allows businesses to adopt AI models to create human-like, conversational interactions that help teams meet and exceed expectations. From addressing customer complaints to answering questions, AI call centers make delivering exceptional customer experiences (CX) easy by automating interactions, simplifying wrap-ups, and unifying customer data.

Whether through voice or digital channels, use our guide to learn how AI improves CX by discovering the benefits, best practices, examples, and common use cases of AI in contact centers.

More in this guide:

AI call centers and their evolution

75 percent of CX leaders believe support teams will look drastically different in three years as agents become AI managers.

To stay relevant (and effective), traditional contact centers must keep up with evolving technologies—most notably, artificial intelligence (AI). The growth of AI, including conversational AI and generative AI, has led to many call center operation evolutions, including:

  1. Manual to intelligent call routing: Instead of manually choosing where a support ticket lands (or sending it to the wrong person or place), teams can automatically route inquiries based on language, intent, and sentiment.
  2. Live chat to AI agents: While live chat support isn’t gone, the newest advancement in live chat is AI agents—the most autonomous AI-powered bots in CX equipped to handle interactions of every complexity.
  3. Manual QA to AI-powered QA: Many AI call centers are equipped with automated quality assurance (QA), allowing teams to consistently monitor interaction quality, update processes based on findings, and enhance CX.
  4. Human intervention to human management: According to our Zendesk AI-powered CX Trends Report 2024, 75 percent of CX leaders believe the skillsets of support teams will look drastically different in three years as agents become AI managers and AI will handle day-to-day service operations.
  5. Manual analytics to AI analytics: From sampling small portions of calls to analyzing 100 percent of customer interactions in real time, AI call centers can automatically process vast datasets across multiple channels.

The landscape of AI call centers has changed dramatically in recent years, and these changes don’t seem like they’ll slow down anytime soon. As machine and deep learning, natural language processing (NLP), and automation technologies continue to grow, AI’s potential—and its evolution—is seemingly limitless.

10 ways to use AI in contact centers

A list of the ways to use AI in contact centers, including AI agents and intelligent routing.

CX leaders are continuously finding new ways to use AI in the workplace. Here are a few of the ways to use AI in contact centers.

1. Solve complex issues with AI agents

AI agents are the next generation of intelligent bots that can autonomously solve a range of customer problems. These AI-powered bots are built on billions of customer interactions, and AI agents transform customer experiences by detecting customer sentiment and intent, identifying customers through voice recognition, and automating call routing. With Zendesk AI Agents, teams can even automate more than 80 percent of customer interactions—no matter how complex.

2. Enhance call routing

Using intelligent routing, AI can automatically send tickets to the agent or team best suited for the request. This automated routing also uses customer intent and sentiment and agent skill, expertise, language, or previous interactions to determine where requests should land. This can prevent transfers and minimize customer wait times.

3. Perform call quality control

By enhancing call listening, AI in call centers helps teams maintain call quality control. 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.
  • Review insights: Assess call transcripts at scale to monitor call center metrics and identify trends, common issues, customer preferences, and sentiments.
  • Assess agent performance: AI-driven algorithms evaluate calls based on customer service goals and benchmarks, enabling managers to determine areas of improvement.

Consistent quality monitoring and quality assurance principles empower call center managers to maintain high-quality performance and service.

4. Facilitate 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.

5. Reduce call wrap-up times

By automating call summaries and transcriptions, AI in call centers significantly reduces call wrap-ups for agents.

  • Call summaries: AI-powered systems can use real-time or post-call recordings to generate accurate summaries based on interactions that identify key points, topics, and crucial information, such as customer complaints and required follow-ups.
  • Call transcripts: AI tools convert spoken conversations into written text and provide full, word-for-word, or near-identical transcriptions of each call.

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.

6. Understand customer behavior

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. This insight helps agents understand consumer behavior and gauge difficult situations, enabling them to:

  • Respond effectively.

  • Adjust their tone.

  • Escalate interactions.

By understanding behavior driven by customer sentiment, agents can produce faster and more proactive and effective responses for all types of customers.

7. Support interactions with AI copilot

Contact centers with AI tools like AI copilot can enhance call center agent performance by providing real-time guidance and support throughout customer interactions.

This AI-powered tool actively listens to interactions and surfaces relevant information from knowledge bases, previous interactions, and customer profiles while suggesting optimal responses and next steps. Plus, agents using AI copilot can maintain natural conversation flows without sacrificing quality or searching through multiple interfaces for customer data.

8. Monitor performance and interaction quality

AI call centers provide comprehensive, real-time analytics and feedback on agent performance and interactions. For example, Zendesk QA automatically evaluates 100 percent of calls, flagging compliance issues, stellar support examples, and agents that need additional training.

With AI-powered tools, teams can also monitor call center workforce management, track key metrics like average handling time (AHT), and identify targeted training and support needs.

9. Analyze data for smarter decision-making

With AI, call centers can transform data analysis into actionable intelligence by processing vast customer data. AI tools can track customer service analytics, behavioral patterns, and consistent skills gaps, identify emerging issues, and highlight opportunities for service improvement.

Advanced AI algorithms can also process historical data to forecast call volumes and optimize staffing levels, enabling managers to make more informed decisions about resource allocation and training priorities.

10. Implement conversational IVRs

Interactive voice response (IVR) can efficiently route and resolve customer inquiries by transforming the traditional menu-driven call experience into natural, conversational interactions. Leveraging NLP, IVR software can understand free-form human language, allowing callers to explain their needs in their own words rather than navigating through rigid numeric menus.

These conversational tools can also authenticate users using voice biometrics and resolve simple issues automatically without agent intervention.

Benefits of using AI in call centers

A list of the ways AI call centers improve customer satisfaction.

Adopting AI for call center software produces various benefits for service teams and their customers, including:

  • Improved customer satisfaction (CSAT): AI in call centers enhances customer satisfaction by helping teams offer omnichannel and 24/7 support, reaching customers where they are—even when agents are off the clock.
  • Boosted agent efficiency and productivity: AI-powered solutions like Zendesk AI can enhance a team’s ability to provide fast, efficient, and accurate solutions for all types of interactions, while tools like AI agents resolve even the most complex issues.
  • Scaled operations: AI can help support teams scale by directing customers to self-service options and digital channels, automating ticket routing, and accelerating employee onboarding.
  • Reduced call center costs: AI call centers reduce overhead costs by directing customers to more cost-effective channels for service and optimizing training time for new and existing agents, improving wait times and other metrics that affect a business’s bottom line.
  • Enhanced workforce forecasting: AI in contact centers can gather and analyze historical data to forecast future trends, customer behaviors, and potential challenges.
  • Automated call monitoring: AI call centers can use call monitoring software to track interaction quality, flag positive and negative interactions, identify areas for improvement, and more.
  • Increased interaction insights: Call center AI allows teams access to real-time insights and predictive analytics, enabling them to proactively respond to potential needs and expectations.

AI tools can handle more than routine, time-consuming tasks, which allows companies to reap the benefits of proactive service and prepared agents.

Best practices for implementing AI in call centers

Whether you use an AI as a service (AIaaS) company—a third-party vendor that handles the AI technology for a subscription price—or AI-powered call center software, these are the key best practices for implementing AI in call centers.

Define your goals and objectives

Set SMART customer service goals that are specific, measurable, achievable, relevant, and time-bound, and define clear customer service objectives that align with your business’s needs. Ensure your AI initiatives serve specific purposes, such as improving customer satisfaction, reducing costs, or enhancing agent productivity.

Provide agent training and change management strategies

Offer call center training so agents can learn how to use newly implemented AI tools effectively and ethically, and don’t shy away from change management models to support their progress.

Use individual and organizational models to emphasize their roles in your company to eliminate fear of replacement and foster acceptance of AI. Plus, use this time to improve old and new call center skills like technical proficiency and communication, improving all aspects of your service.

Ensure data privacy and security

Adhere to customer data privacy regulations and implement robust security measures to safeguard customer data handled by AI systems. Also, prioritize AI transparency so your customers know what data you’re collecting (and why), how you’re using it, how long you’ll store it, and more.

Evaluate and monitor AI performance

Regularly monitor AI performance and gather feedback for ongoing improvements. This allows you to refine AI models, workflows, and processes based on feedback and changing business needs for continuous enhancement.

Focus on personalization

Keep personalization top of mind so you can tailor your interactions to customer expectations and preferences. Allow your AI tools to access historical data and past interactions housed in your unified workspaces to guide conversations and responses. Agents can also use AI to personalize responses in call center scripts based on sentiment, needs, and more.

Integrate with your existing service solution

Make sure you choose AI tools that fit your current business needs, CX strategies, and service software. Test each tool’s features and capabilities before settling on a choice to optimize performance and simplify integration.

3 examples of AI in a contact center

From healthcare to finance and every industry in between, here are a few real-life examples of AI in a contact center.

CNH Care

CNH Care is an end-to-end healthcare solution provider using call center AI to ensure no calls fall through the cracks while maintaining a 96 percent CSAT score. This company uses AI-powered tools to automate ticket routing, optimize proactive support, decrease call waiting times, monitor dropped calls, and facilitate near-immediate agent callbacks.

Netwealth

As one of Australia’s leading financial companies, Netwealth uses call center AI to handle increased query volumes and customer expectations. With an AI call center, Netwealth customers reach an agent within 60 seconds, and agents resolve nearly 99 percent of call tickets with a single touch. Plus, the company fields more than 20,000 inquiries a month while automating call recordings, storage, and access.

Wyze Labs

Smart home technology innovator Wyze Labs uses a unified, omnichannel contact center to optimize scaling and reduce overhead costs. Since adopting Zendesk, Wyze Labs now reports a 78 percent increase in call acceptance and a drastic decrease in first contact resolution time from one week to one hour.

Frequently asked questions

Make the right call with AI

AI call centers make it easy for businesses to handle more interactions and provide exceptional CX without breaking the bank. With generative AI and AI-powered tools like Zendesk AI agents, call summaries and transcriptions, and data-driven insights, you can take your service and experiences to a whole new level.

Zendesk boasts all these features and more. We specialize in call center software with AI at our core. By partnering with us, you have access to AI-powered knowledge management, intelligent call routing, and sentiment analysis—everything you need to level up your call center.

Dial up your services and invest in voice support for the AI era with
Zendesk voice software today.

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