Artificial intelligence call centers: A new age in CX

A lot goes into running a thriving contact center, like resolving customer issues, end-of-call wrap-ups, answering customer questions, and agent training. Fortunately, technology is advancing rapidly, and artificial intelligence (AI) is paving the way for call centers to become more efficient and better serve customers.

Zoom’s State of AI in Customer Experience (CX) 2025 report reveals that 64% of companies that are using AI for call centers enjoy a positive ROI, while 79% say AI is tackling more complex problems for them now than it was a year ago.

Here, you’ll learn more about what artificially intelligent contact centers are and what features they provide. We’ll also go over some of the best use cases for AI in call centers to improve customer satisfaction and retention.

An AI contact center combines human support with AI systems built on large language models (LLMs). These models read and interpret conversations to then generate responses or suggestions based on patterns learned from massive volumes of real interactions.

AI call center technology gives agents helpful context in the moment to resolve customer issues more effectively. This may explain why a projected 80% of customer service organizations use it to improve agent productivity, according to recent call center statistics. In this setup, automated agents can manage common questions and route conversations. In contrast, human agents can deal with nuanced situations that require empathy or judgment beyond what AI systems can provide.

A misconception is that AI will replace agents. In reality, it’s meant to assist the entire call center team with an assortment of tasks.

AI provides contact centers with solutions to improve internal workflows, administrative tasks, and much more. But how does it all work? Below, we provide a brief overview of the technology used in AI contact centers:

• Natural language processing (NLP): NLP is an aspect of AI that focuses on the interaction between human and computer languages. It’s what enables AI to understand, interpret, and communicate with its users.
• Natural language understanding (NLU): This subset of NLP enables AI to comprehend natural language. Thanks to NLU, AI can understand the intent and context of user text or speech.
• Large language models (LLMs): AI primarily uses LLMs to learn words. It uses massive pattern-finding networks to consume and understand enormous amounts of text data, which allows it to write and communicate.
• Machine learning (ML): The technology that enables AI to improve over time. As it receives more data with each interaction, it becomes a better system.
• Speech recognition and synthesis: This allows AI to understand and generate human speech. This is similar to text-to-speech, but the result sounds far more human than many of the technologies we’re used to.

These features give your contact center AI capabilities to help improve productivity and customer service from day on

AI call center vs. AI contact center

There are some technical differences between AI call centers and AI contact centers, but the terms are often used interchangeably.

AI contact centers can be multichannel or even omnichannel, meaning they can support communication beyond just calling, including chatbots, video chat, text, email, and more. AI call centers use AI technology exclusively to support call handling.

CCaaS platforms now offer chatbots and virtual agents to engage customers, as well as agent-assist features such as Next Best Action, Auto Translation, and Automatic Wrap-Up.

In the long run, an artificial intelligence call center can speed up resolutions and create more consistent experiences across all channels. Since these systems learn from past conversations, their recommendations also improve over time.

AI contact center software provides a wide range of useful features to assist call center agents, managers, and customers. Understanding these features is helpful to employ this technology in your call center.

1. Quality management assessments

Quality management is an integral part of running a successful call center because quality managers can provide valuable feedback to agents, like the best way to de-escalate a call. Unfortunately, due to the number of calls that come through a call center on any given day, it’s unrealistic for quality managers to review each call individually.

AI can help contact centers with quality management by combing through entire call transcripts and creating simplified summaries with suggestions for improvement. This gives quality managers more time to focus on coaching agents rather than reviewing calls, and it’s so effective that 66% of call center supervisors report improved quality management as of 2024.

2. Agent assistance

Agent assistance supports live agents during customer conversations by listening and analyzing context to offer guidance in real time. This feature, powered by LLMs, can suggest responses or appropriate next steps without interrupting the call’s flow. Using this tool, the agent can stay focused and reduce manual lookups and after-call work.

Suppose a customer calls about a billing dispute that includes multiple products. As the conversation goes on, the agent assist picks up on key phrases and pulls related policies. It then suggests a clear explanation that the agent can adapt how they see fit. Plus, it can prompt the agent to ask follow-up questions or summarize the interaction for later use.

Adoption is picking up quickly, with 64% of companies already using this feature or having plans to use it in 2025. Organizations using it report 64% greater employee efficiency, 60% reduced costs (alongside 49% higher revenue growth), and 39% better CSAT scores.

Zoom’s AI Expert Assist provides a strong example of an AI assistance tool. It offers real-time guidance during live conversations, surfaces relevant knowledge, and helps agents respond more efficiently without putting customers on hold.

3. Automatic call distribution (ACD)

Automatic call distribution (ACD) is the technology that matches the customer with an agent who has the unique skills to help them. For example, you may have bilingual agents who can communicate in different languages or have expertise in specific areas. With ACD, AI can assess what the customer needs and direct them to the agent best suited to meet those needs, saving time and providing the customer with a better experience.

ACD isn’t just for directing calls, either. An AI contact center has routing capabilities that integrate with all of your communication channels. Whether a customer calls, emails, or texts, the AI can direct them to an available agent with the best skills for the situation.

4. Wrap-up summaries

After each call, agents write wrap-up summaries to recap what happened on the call. This helps the next agent who works with the customer know where the last agent left off. While these summaries are necessary, writing them by hand takes up time that the agent could spend helping the next customer.

AI can decrease the time needed for this task by generating a summary of each call once it’s complete. According to a 2024 report from Metrigy and Zoom, generative AI summarizations help agents save 35% after-call time. Previously, agents spent 16.2 minutes on summary generation, which AI helped reduce to 10.4 minutes. Then the agent simply needs to review it for accuracy before moving on to the next customer interaction. With this Zoom CX feature, we’ve seen a 50% decrease in time spent on wrap-up summaries for customers.

5. Integration with other platforms

Call centers use a variety of platforms, such as CRMs, knowledge bases, and ticketing systems. Whenever you adopt a new form of technology, you want to be sure it works seamlessly with the platforms you’re already using. AI contact centers provide that functionality.

AI contact center software often integrates with popular CRM platforms. Whether it’s Salesforce, Zendesk, or PCI Pal, you can set up your AI contact center to work with them and utilize valuable tools like wrap-up summaries and agent assist.

6. Sentiment analysis

Sentiment analysis is the technology that enables AI to understand how customers feel when they call by analyzing context and tone.

During a conversation, sentiment analysis can alert the agent if a customer is becoming upset in real time. It can then provide the agent with information and suggestions via agent assist. This can also help with detailed wrap-up summaries and quality management by informing you of the customer’s mood throughout an interaction.

7. Knowledge retrieval

Knowledge retrieval is the contact center’s ability to search for information across sources such as previous calls, standard operating procedures, and FAQs to help agents answer questions quickly. This feature helps limit the need to put customers on hold, keeping them happy and reducing frustration.

AI can also power contact centers with chatbots that answer simple customer questions. Knowledge retrieval helps chatbots answer a broader range of questions, freeing agents to work with customers who require a human touch.

The use cases for AI contact centers are wide-ranging. Below, we go over some common situations where this technology can benefit your call center.

1. Analyze data

Analytics are necessary for any business, and AI can help organize and analyze data efficiently and effectively. For example AI can measure your KPIs, like average call time, and point out key insights. Reporting data could show management that average call time is down due to customers switching to using chatbots rather than calling in. 

Once you have your contact center software set up, you can customize it to run reports on the metrics important to your specifications.

2. Help with workforce management

Contact center AI software can also track call volume, which can help with workforce management. Every call center has busy and slow seasons. When creating schedules, you don’t want to be overstaffed during slow times or understaffed when it’s busy, and AI can help ensure this doesn’t happen.

An AI contact center can monitor historic call volumes and provide you with valuable data for scheduling. Not only does this help you properly staff your call center for effective customer care, but it can also help ensure employees aren’t overwhelmed due to understaffing.

3. De-escalate calls

It’s no secret that customers can get frustrated; that’s just the nature of customer service. Although agents are trained to de-escalate calls, sometimes they don’t have the answers, so they place the customer on hold and find a supervisor. This can frustrate the customer even more and take up the supervisor’s time.

Sentiment analysis can help provide agents with suggestions to de-escalate the situation. The AI-powered contact center is trained on your operating procedures, knowledge base, previous conversations, and much more. Agents can then quickly receive suggestions to help the customer without placing them on hold.

4. Improve customer experience and self-service

AI has access to your knowledge base, which can help you provide customers with a much better experience. Customers want their issues resolved quickly, and many prefer to find the answer on their own rather than having to make a call or get in touch with an agent through other communication channels. With AI, chatbots can handle many of your customers’ common questions.

Whether your customers need help during unstaffed business hours or during the day, the AI chatbot can help. This frees agents to handle more complex issues that require human assistance.

5. Reduce costs

As we’ve covered, a primary benefit of AI contact centers is workforce management, which helps reduce costs by preventing overstaffing during times when it’s slower than usual. AI-powered contact center software has such a wide range of features that it may replace other tools in your stack, saving your company from other monthly or annual fees.

Zoom Contact Center goes a step further to provide value for teams, offering its AI Companion across all eligible paid packages at no additional cost.

6. Make processes more efficient

AI contact centers help make agents more efficient by finding answers for customers and generating wrap-up summaries. They also make life easier for supervisors and quality managers by providing information that allows them to spend more time helping agents improve their day-to-day tasks.

7. Resolve language barriers

ACD enables AI contact centers to connect customers with agents who speak their language, but it can also do much more. AI can translate in real time. For example, a Spanish-speaking client can use your chat to speak with an English-speaking agent. Using the chatbot, the agent will see English text, and when they respond, the customer will see Spanish text.

This kind of real-time translation also improves business communication by helping to bridge language barriers. CX teams can support more customers without increasing language-specific staffing.

Getting started with an AI contact center can feel overwhelming, but you can make the process more seamless by following our best practices.

1. Set clear goals and objectives: Create goals that align with your business’s needs. Do you want to be more efficient, improve the customer experience, or have better training for agents? It may be all of the above, but be sure to define these goals so the contact center is helping you reach them.
2. Thoroughly research software options: Once you have goals, find AI contact center software with the right features. These features should align with your goals and work well with your call center's operations.
3. Have an integration plan: Prior to setting up the technology, have a plan in place to train your agents on how to use the new tool. To do this, be sure your training team properly understands the technology, then create a lesson plan to train the agents. And remember, it’s always helpful to show your agents how this new contact center can make their lives easier.
4. Maintain privacy and security: As with other forms of software that store customer information, it’s important to protect that information with firewalls and strong passwords.
5. Monitor and evaluate performance: Regularly assess how your new AI contact center is performing and whether it’s meeting your goals. Part of this process should involve feedback from call center agents, supervisors, and other users of the contact center.

An AI contact center can help propel your call center to the next level by increasing efficiency, improving the customer experience, and supporting your staff.

Zoom CX uses advanced AI technology, including sentiment analysis, Agent Assist, and ACD. It also integrates with popular platforms like Salesforce and Zendesk. To learn more about how Zoom CX can help your business, request a demo today.