OI Blog


Peter Iansek

CEO & Co-Founder

Peter Iansek


Oct 2023
OI Blog
Oct 2023

Artificial Intelligence in Call Centers: How AI is Used in Call & Contact Centers

Artificial Intelligence in Call Centers: How AI is Used in Call & Contact Centers
Peter Iansek


Peter Iansek

CEO & Co-Founder

Table of Contents:

  • How Is AI Used In Call & Contact Centers? == How Is AI Used In Call & Contact Centers?
  • Benefits of AI in Call Centers == Benefits of AI in Call Centers
  • Limitations of AI in Call Centers == Limitations of AI in Call Centers
  • Use AI to Improve Your Call & Contact Center Service == Use AI to Improve Your Call & Contact Center Service

How Is AI Used In Call & Contact Centers?

Many businesses now rely on AI to streamline their operations and improve efficiency. These are some of the tools they use to achieve this.

1. Predictive Call Routing

call routing

Call centers traditionally route incoming calls to available agents in a linear, first-come-first-served manner. However, AI-driven predictive call routing is used in contact centers to identify the most suitable agent to handle a customer's call. The software evaluates past customer behaviors and criteria to predict the necessary skills of the contact center agent to best serve each caller. 

According to a study by Replicant in 2022, almost half of customers (44%) experience feelings of annoyance, irritation, or anger when they are placed on hold for a period ranging from 5 to 15 minutes. The study further indicates that long wait times do not just cause inconvenience but also negatively impact the customer's perception of the brand. When customers are kept on hold for extended periods, they may start feeling undervalued or anxious due to the lack of clarity about when their call will be answered.

Predictive call routing helps in reducing hold times, preventing the need to pass on customers to a different agent, and improving the overall customer experience. Predictive call routing also leads to higher first contact resolutions, reducing queue and agent overload, and improving contact center efficiencies.

2. Interactive Voice Response

interactive voice message

IVR (Interactive Voice Response) is an automated phone system that greets callers with a prerecorded message and provides menu options for routing their calls to the appropriate department. IVR can also support multilevel menus, allowing for the collection of additional information before routing the call to a specific team. 

IVR is commonly used with automatic call distribution (ACD) to prioritize calls and reduce wait times. IVR can also be used for self-service options, such as answering simple questions or taking actions that would otherwise require human assistance, and for payment processing.

IVR solutions are especially useful for contact centers and businesses that experience high call volumes since they help reduce wait times and expedite service, ultimately leading to customer satisfaction and retention.

3. Voice Analysis

voice inquiries analysis
Operative Intelligence determines the root cause of customer contact by analyzing 100% of inbound interactions. 

Research by McKinsey revealed that by utilizing speech data, companies have reported cost savings ranging from 20 to 30%, improved customer satisfaction scores of 10% or more, and increased sales.

Voice analysis uses artificial intelligence to analyze customer interactions, including voice-to-text transcription. Sentiment analysis is a type of voice analysis that uses technology like Natural Language Processing (NLP)  to identify the attitudes or intent behind text or speech. 

The data extracted from speech can provide valuable insights into customer behavior that cannot be obtained from other sources. This right software can identify the root causes of customer dissatisfaction and reveal opportunities for improving compliance, operational efficiency, and agent performance.

For example, the Operative Intelligence platform uses AI and machine learning to analyze 100% of inbound interactions and identify the exact, root cause reasons, why customers contact support in their own words. The system accurately captures the sentiment, intent, and emotion behind each customer interaction, providing contact centers with a wealth of actionable insights into customer needs, preferences, and pain points. 

4. AI-powered Recommendations for Agents

Operative Intelligence platform uses AI & machine learning to improve agent productivity and effectiveness

AI-powered recommendations for agents involve providing real-time guidance and support to customer service representatives. Using agent analytics, call and contact center managers can track key metrics including 

Operative Intelligence empowers call and contact center managers with agent analytics dashboards to track performance and allocate resources while giving agents insights into their performance and how they can improve their interactions with customers.

5. Chatbots

According to Forbes, conversational assistants powered by AI are not only providing customers with basic information but also feeding human agents with valuable insights behind the scenes. 

Chatbots can be used to handle customer inquiries, support requests, and complaints. They’re often integrated into a company's website, mobile app, or social media channels but can also be deployed on messaging platforms to engage with customers through chat interfaces.

Chatbots can handle various tasks, from answering basic questions to providing personalized product recommendations, and even resolving issues. They can work 24/7, which can help reduce wait times and improve customer satisfaction. Chatbots can also reduce operational costs for contact and call centers by automating routine tasks and freeing up human agents to handle more complex issues.

Benefits of AI in Call Centers

AI brings undeniable benefits to call centers, improving the customer experience and optimizing costs.

Improved Customer Satisfaction

According to research by Aberdeen Strategy & Research, companies that utilize AI capabilities outperform those that don't in terms of achieving their goals. Studies found they’ve experienced an annual improvement in customer satisfaction rates and an annual improvement in customer effort scores. 

When agents handle tasks manually, there is always the potential for human error. AI-powered solutions are designed to minimize the potential for error and provide more accurate and consistent responses to customers. 

Cost Optimization  

According to McKinsey, through the application of advanced analytics, companies have achieved significant improvements in their contact center operations. These include reducing average handle time by up to 40%, increasing self-service containment rates by 5% to 20%, cutting employee costs by up to $5 million, and increasing the conversion rate on service-to-sales calls by nearly 50%. 

Operative Intelligence helps call and contact centers identify cost drivers and reduce costs by unlocking the reality of their customers' needs in their own words. By analyzing data from various channels, Operative Intelligence can provide insights into the volume and costs of all inquiry types, and determine customer satisfaction, and first contact resolution for every inquiry as well. By having this data, businesses can identify the areas where they need to improve and take action to reduce costs associated with those areas.

The platform also enables businesses to drill down to uncover the root cause of customer pain points and identify which inquiries can be completed through self-service. This can help businesses reduce costs by automating some of their customer service operations, while still providing high-quality service.

Increased Data Analysis

Data-driven decisions are critical to call center performance. With the help of AI, call centers can analyze vast amounts of customer data they couldn’t before. However, the data can only be beneficial to businesses if they get actionable insights from it.

The sheer volume of data generated by customer interactions can be challenging to manage and extract meaningful insights from without extensive resources. Businesses often rely on skilled analysts to manually stitch together different pieces of data to create actionable business cases. 

But this is complex, expensive, and time-consuming, leaving little room for different discoveries that could impact the customer experience and revenue. Operative Intelligence offers an efficient way to process customer data, by analyzing 100% of inbound interactions and identifying the true driver of customer contact using customer's own words.

Limitations of AI in Call Centers

AI has brought significant improvements to the call center industry, however, it also has its own limitations. 

New Learning Curves

Implementing AI in call centers means that agents and management must learn and adapt to new technologies. The agents may need to undergo training on how to use the new tools and systems, and management may need to restructure workflows and procedures. 

This may initially result in decreased productivity as agents may take time to learn the new technologies and may need to work closely with the AI until they are comfortable with the new tools. 

There may also be a learning curve for the AI technology itself, as it may need to be trained and adjusted to the specific needs of the call center, which can be time-consuming and require specialized expertise.

Lack of Personalization 

AI does a great job automating routine tasks and providing quick and efficient responses to customers, but it lacks the personal touch that human interaction provides. A good customer service experience includes human interaction where someone listens to and resonates with the customer's situation.

In the 2021 Global Contact Center Survey conducted by Deloitte Digital, customers ranked human connection and person-to-person service interactions as the most important factor in feeling valued by a brand. The survey also revealed that customers prefer to engage with the right channel, which increases the chances of resolving their issue on the first attempt.

AI-powered chatbots may not be able to empathize with customers and they may not be able to provide personalized solutions. It’s still critical to have human-led customer service for complex issues and situations that require empathy and understanding.

Use AI to Improve Your Call & Contact Center Service

Deploying AI-powered technology in your call and contact center can improve the efficiency and effectiveness of your customer service processes. Operative Intelligence is a next-gen analytics and insight tool that uses artificial intelligence and machine learning to identify: 

  • The root cause reasons why customers contact support at scale
  • Insights by inquiry driver: volume, cost, sentiment, satisfaction, resolution
  • The root cause of customer pain points and what they cost the business
  • The top contact center automation opportunities and the ROI for each
  • What is driving increases in handle time and cost + how to fix it
  • What is driving negative customer sentiment and satisfaction
  • Agent and team effectiveness (resolution + satisfaction) for 100% of inquiries
  • Top and lowest performing agents by inquiry type

Don't wait to give your customers and agents the best support. 

Book a demo with Operative Intelligence today.

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