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4 Ways Call Centers Are Being Transformed With Emerging AI

AI Enhanced Call Centers

Recently, call centers have been facing unprecedented volumes of calls. In a survey of 12,000 respondents, Salesforce found that more than half of customers felt businesses needed to improve their customer service.

With the growth of technology, a good call center experience has become high among customer expectations. In fact, 91% of customers reported they would be more likely to purchase as a result of a positive customer service experience. Customers expect business responses to be timely, empathetic, and understanding of their needs.

This pressure to keep up with consumer demand will become a huge business differentiator.

 So what can you do to improve your call center performance? 

The answer is AI Technology.

AI technology allows you to standardize your omnichannel communication and customer experience. This means that wherever your customer finds you, they can get the same level of excellent service. Moreover, analytics features can allow you to take a data dive into your customer’s drives, understanding, and engagement with your team.

Data source

As these statistics highlight, technology is moving to the forefront of how call centers operate. Let’s discuss how these innovations are being used and their benefits.

Chatbots and IVR

The latest chatbot technology is designed to be an auto attendant phone system small business solution for your customers. You might have seen with bots such as Alexa and Siri the ability to accurately interpret text-to-speech. This means when a customer calls your business, the bot can interpret speech, and with machine learning, it becomes better at understanding customer responses and intent. 

Traditionally, businesses used an IVR system for call centers. While this approach made it easier for centers to handle and filter through large call volumes on small business phone numbers, it was not a hit with customers. We’ve all had frustrating conversations with a robotic voice that doesn’t seem to understand our inquiry. This can lead to customer dissatisfaction or, worse, a negative opinion of your brand. 

Luckily, newer conversational AI bots can grasp the language and audio cues much more comprehensively than traditional IVR. Using NLP – natural language processing, they’re more able to mimic human-generated text and language. This allows them to carry out more fluid and natural conversations to communicate with demanding clients. It also means they can understand what your customers are trying to say.

Since these bots can manage inquiries, this reduces customer call time. If you have four-line phone systems for small business operations, chatbots can be integrated with other software so they can do scheduling, provide users with account details, and offer product promotions. It also feeds your team vital information before the customer is passed on to a human caller.

This leads to the second innovation of AI call center technology.

Distributed workforces and Call routing 

By using digital technology to gather basic customer data and inquiry information, you can speed up your response time with predictive call routing. This is especially useful when your agents are based in different countries, and you’re utilizing a call center and BPO (business process outsourcing) to speak to your customers.

The chatbot can use the customer’s responses to direct them automatically to the correct department and person to answer their inquiry. It can conduct an in-depth analysis of customer personality and communication style, which matches them with the best responder. This helps the customer’s experience to not only be more satisfying but it can also help to increase positive engagement with your business.

Answering machine detection 

In addition to directing customers to the right responder, your team may have to engage in outbound calls. With AMD – answering machine detection, you can ensure you reach live callers instead of an answering machine. AMD technology uses AI to detect if a caller has reached voicemail instead of a live respondent. If your caller connects to a customer’s phone, it can determine whether to forward the call to a team member.

Another factor of call rerouting with AI is if you have a distributed workforce. With the rise of homeworking, more and more teams operate remotely. Using an AI redirection service, you can send callers to distributed teams worldwide.

 The benefit of this approach means you can scale your operation with more responders on the clock to answer inquiries. Moreover, a remote workforce allows you to communicate with customers in their language, region, and time zone. 

If you need precise indications of whether your customers are happy with the outcome of these calls, there’s another innovation you can use: a conversational response.

Conversational response

Conversational AI trackers with a VoIP phone app can carry out complex analyses of customer conversations. This includes emotional voice cues that might indicate customer sentiment during a call. 

This technology can measure pauses in conversation, agent interruptions, and the tone and mood of conversations. By looking at these factors, you can provide agents with clearer feedback on how to improve the quality of their customer engagements.

Moreover, these analysis tools can be used to profile customers on their individual communication and linguistic style and preferences. This can go towards your customer segmentation effort (more about this in a bit).

Before you can utilize this tech, you’ll need a good understanding of your customers and teams, but fear not! There’s AI technology for that too.

Automation and analytics 

With integrations to a CRM (customer relationship management) system, you can link customer calls to other interactions they’ve had with your business. This can give your call agents critical information about products and services that customers are interested in. This can then be used to promote relevant products to your callers.

It can tell you which customers are leads that have shown interest and where your customer is within the customer lifecycle. With actionable insights into caller engagement, you can make better decisions and strategies to improve your efforts. 

This information is essential because it can highlight different needs and areas where your team can focus. With AI automation, it can direct customers to the correct respondent or service as well as offer critical data about your calls that can help personalize the customer experience and improve your CAC LTV – the cost of customer acquisitions on their journey through the customer lifecycle. 

Call analytics can also be an essential tool for managing quality control and ensuring your team’s performance. By developing a customer profile this way, the data can be carried over to the rest of your on-premise ERP and operations. 

For instance, it can show you ways to better your customer segmentation. Precise audience segmentation can help you to win leads and improve marketing results around different topic clusters as well as develop better services and experiences for your customers.

Advanced analytics can also contribute to making better predictions and forecasting for your finances. By understanding your sales performance, you can increase conversions and internal alignment and meet your business goals. 

AI & Call Centers – Tips and Takeaways 

Using AI technology is a great way to reduce the cost of outsourcing your customer engagement. It can automate administrative and marketing tasks on your behalf, which gives you time to focus on customer experience. 

This doesn’t mean doing away with your call center altogether. Instead, it’s a way of empowering your team’s performance. However, there are some key things to keep in mind when employing a new AI strategy.

Key points to remember:

  • Identify your problem: before enlisting AI software to help your call center, you want to have a clear understanding of what problem the technology is going to solve. Are you trying to scale, increase conversions, or maybe just improve your response time? Whatever the case, you want to find a provider who can cater to your needs.
  • Choosing the right tools: when you’ve narrowed your choices, consider whether you’re getting the best deal for the service you need. This can include pricing, features, and customer service reviews. Use them to determine if this software is right for you. Don’t forget to carry out cybersecurity risk assessments for the tool you choose.
  • Training: the next step is onboarding your team with the new software. It’s best to set aside time to discuss with them how the new technology is going to affect operations and what problem you intend the software to solve. This will help them to better identify what is working and what isn’t in the future.
  • Measure performance: when thinking about any new software implementation, your main concern should be whether the technology is going to provide a good ROI. To measure this, you need to decide what metrics and KPIs you want to measure, for example, conversion rate, revenue, retention, etc. You might also want to use it alongside SOX software to ensure you’re fully compliant.
  • Scale-up: lastly, when the software has a proven track record of helping your business, you can look at scaling up. Many AI software providers offer enterprise-level services. Again, walk through these steps to determine whether now is a good time to expand your business model.

With these points in mind, we hope this guide has provided some useful insights into the future of AI call center technology. With that said, happy calling!


Q: How is AI transforming call centers?

A: AI is transforming call centers by automating repetitive tasks, providing intelligent virtual assistants, enabling sentiment analysis for customer interactions, and improving call routing and customer service efficiency.

Q: What are some benefits of AI in call centers?

A: AI in call centers brings several benefits, including increased operational efficiency, reduced costs, improved customer experiences through personalized interactions, enhanced call quality monitoring, and faster query resolution.

Q: How does AI automate repetitive tasks in call centers?

A: AI automates repetitive tasks in call centers by using technologies like robotic process automation (RPA) and natural language processing (NLP) to handle tasks such as call triage, data entry, appointment scheduling, and basic customer inquiries, freeing up human agents to focus on more complex issues.

Q: Can AI-powered virtual assistants replace human call center agents?

A: While AI-powered virtual assistants can handle basic customer inquiries, they are designed to collaborate with human agents rather than replace them entirely. Virtual assistants assist with simple tasks, gather information, and provide suggestions, while human agents handle complex queries that require empathy, critical thinking, and decision-making.

Q: How does AI enable sentiment analysis in call centers?

A: AI enables sentiment analysis in call centers by analyzing customer interactions, such as voice tone, choice of words, and overall sentiment, to gauge customer satisfaction or identify potential issues. This helps call centers prioritize and personalize customer interactions, improving customer experiences and retention rates.

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