Transforming Customer Service: The Role of AI in Call Centers

An AI call center is a customer service-oriented organization that utilizes artificial intelligence (AI) tools and technologies to automate tasks in order to improve efficiency and customer experience. These call centers do not solely rely on human agents to handle phone calls. AI in call center tools, such as Natural Language Processing (NLP), automated chatbots, virtual assistants, and conversational AI, are used to handle customer inquiries and resolve issues.
 

AI is used in call centers to find areas for improvement through sentimental analysis and analytics, increase operational efficiency by automating tasks, and improve customer experience.

Integrating AI in call centers allows agents to focus on more complex tasks as AI is set up to handle repetitive tasks. Here are some ways AI is used in call centers.

With NLP, AI systems can give multilingual support. Their ability to understand and extract key information from a call held in any language helps to expand the reach of customer support services. Transcriptions make it easy to identify important details at a glance and spot areas for improvement. Calilio’s AI-powered call summary leverages the power of NLP to extract key information from a call into text, making it easier to analyze conversations.

Virtual agents and chatbots can handle large numbers of calls, provide immediate responses, and resolve simple issues. Customers will no longer have to wait for countless hours on hold to receive answers to their queries. The first commercial chatbot was launched in the mid-1990s to offer 24/7 support to website visitors.

AI-powered call centers use call analytics and monitoring to analyze call metrics such as duration of the call, resolution rates, attitude reflected in the call, and customer satisfaction scores.

Call centers use AI-powered sentimental analysis to measure and analyze customers' tone, intensity, and moods during interactions to find satisfied and unsatisfied customers.
 

AI helps companies respond to a customer’s request for service while also predicting and preparing for a customer’s wants and future needs using analytics and insights. With AI, industries can improve customer experiences by providing faster and more personalized support, reducing costs, and increasing operational efficiency. You can quickly access information obtained from transcripts, sentiment analysis, and analytics to develop strategies for continual improvement.

Banking, financial services and insurance (BFSI), media, IT, telecom, healthcare, and retail are the top sectors that employ advanced AI and ML solutions in call centers.
 

AI tools reduce response time by providing helpful information quickly, freeing agents' time to focus on more complex calls requiring critical thinking. With features such as call transcription, call summary, and sentimental analysis, staff can be more productive and provide better service. Call transcription and AI-powered summaries help reduce note-taking, get more insights, and discover hidden opportunities.

Artificial Intelligence in call centers improves customer satisfaction by quickly and accurately resolving straightforward issues or complaints. Chatbots can handle inquiries related to order status, technical assistance, account support, or FAQs. Similarly, with IVR, customers can serve themselves and reduce hold times.

Using AI, agents are armed with historical data and insights about customers, making it easy for them to deliver meaningful selling opportunities.

Businesses can turn their calls and messages into insights through analytics and reporting. Supervisors can track and measure agent performance, uncover customer sentiment, and discover key points, common themes, and most-used words in the call. Analytics and reporting use NLP to identify call drivers and customer sentiment (positive, negative, or neutral). This helps companies improve their first-contact resolution and increase conversion rates by learning about customer interactions.

In a survey of 300 contact center and IT leaders by 8x8, 87% said conversational AI lowered costs by improving agent efficiency (65%), and 53% said it reduced overall operational costs.

Implementing AI in call centers requires careful planning and strategic implementation to improve operational efficiency and drive business growth. The technology must align with organizational goals and objectives, whether you plan to implement chatbots for 24/7 customer support or analytics and reporting for call monitoring.

Have a road map that prioritizes AI initiatives linked to business value across the organization so that you can choose the right AI tools and software. Is your objective to improve the first call resolution rate, reduce operational costs, improve customer satisfaction scores, or reduce call volumes? The AI strategy should serve a specific purpose and align with the broader corporate strategy and goals.

Start with free AI call center software trials and test the features to see whether they complement your current infrastructure and software. Figure out how the tools fit into your corporate strategy and goals. Tools that easily integrate with your existing tools in one centralized platform enhance functionalities and improve overall efficiency.

Call center agents, managers, and supervisors will interact with customers daily using AI tools, making it necessary they receive ample training on how to use AI tools to increase efficiency and enhance customer experience.

To know whether implementing AI in your call center was a success, you will need to identify metrics and KPIs that indicate certain improvements have been made since the integration. Important key performance indicators are average handle time, first call resolution, and call abandonment rate. Did agent efficiency, customer satisfaction, and overall productivity increase? Analyze data from sentimental analysis, call analytics, and reporting identifying areas for improvement. Continuously refine workflows and processes based on customer feedback and insight from analytics.

The future of AI-based call centers is one of increased automation, improved customer service through AI-powered chatbots and virtual assistants, reduced operational costs, personalized experiences based on customer data, advanced analytics and reporting for better decision-making, and 24/7 availability.


According to Gartner, automation in customer-agent communication is expected to increase fivefold by 2026, rising from 1.8% in 2022 to about 10%.
 

AI call center solution makes it easy for businesses of all industries to handle more calls and provide stellar customer experience with features like call analytics, AI-powered call summary, and sentimental analysis.

Calilio offers all those features plus more to level up your services, such as IVR technology, click-to-call, call pop, auto message, and daily member reports. Daily member reports give you a concise overview of the team’s performance, from handling calls to success and failure of engagement. Other details include active and waiting for the duration and attitude reflected during those sessions. Analysis of such information helps pinpoint areas for improvement. 

Sign up on Calilio today to take your customer experience to another level.

AI is used in call centers to automate routine tasks, improve customer service through analytics, virtual agents, and sentiment analysis, optimize call routing through predictive routing, and help agents personalize customer experience.

Call centers will not be completely replaced by AI. Though AI increases efficiency by automating routine tasks, human agents are needed to solve complex problems, empathize with customers, and add the human touch that makes customer interactions personalized. AI will help human agents do their jobs more efficiently with tools that allow them to handle calls that require their time.

The benefits of AI in call centers are improved customer service, reduced call center costs, more productive support representatives, better first-call resolution, and increased efficiency.

To transform to an AI-based call center, you need to assess current call center operations to find out where AI can make the most impact, determine goals and objectives for the AI implementation, select the AI solution that will support your call center, activate the AI tools, train your staff to help support their work with the call center AI, and measure results after the implementation to improve your customer service continually.