Conversational AI and the future of Customer Service

Of these call center AI solutions, IVA technology is particularly well suited to enhancing agent productivity and making modern call center operations more efficient. Conversational AI enables brand’s call centers to fully or partially automate conversations on messaging channels at scale. ChatGPT is a natural language processing (NLP) model based on OpenAI’s generative pre-trained transformer (GPT). This AI model generates human-like responses and text for almost any question or request, and it has caused an uproar because of the power it has to transform how we do anything. This involves using algorithms to analyse the nature of a customer’s query and route the call to the most appropriate agent or department.

As we continue to see rapid advancements in technology and communication, the call center industry is at the forefront of evolution, adapting and transforming to meet the ever-changing needs of businesses and customers alike. Consequently, it’s crucial to keep abreast of the latest industry trends, as they play a significant role in shaping the contact centers of the future. In this blog post, we will metadialog.com delve into the most significant call center trends that are shaping the landscape, including artificial intelligence, omnichannel strategies, remote workforces, and enhanced data security measures. Understanding trends helps businesses provide exceptional customer experiences for long-term loyalty. According to experts, AI can automate basic tasks, such as responding to frequently asked questions.

Comparing Pros and Cons of AI vs Human Call Center Agents

Bonnie Low-Kramen, author of the book “Staff Matters,” says AI tools lack empathy and intuition and cannot replace people for customer service. Another form of artificial intelligence in call centers is emotional intelligence AI that can track customer sentiment during a phone call. This is when a call center will have an online chat option that is powered by AI. And it’s a necessary form of customer service since 85% of consumers worldwide would like to message with brands, up from 65% last year.

• At its core, AI is a computer technology that is considered “smart,” meaning that it’s able to mimic human thinking.
• Through their integration with industry-specific knowledge bases, conversational AI-powered chatbots have the potential to usher in a new era of customer service.
• It’s at the point of the customer interaction where leadership’s answer to that question most impacts a contact center’s success, and it’s not an either/or, exclusively-AI/exclusively-human calculation.
• This is significant because 90% of consumers consider an immediate response to be of high importance when they have a customer service question.
• McKinsey reports that advanced analytical data can help contact centers put customers first.
• Call center workers are continually leaving, being replaced, and being trained.

Data collection and analytics with AI empowered call centers helps humans make smarter decisions and present the best options to customers. This use of big data in the artificial intelligence call center will only expand in years to come. Speech recognition can also be used to provide in call analysis of customer interactions and make suggestions to agents within a call. It may sound a little big brother-y, but this will lead to better outcomes for customers and companies. Like emotional intelligence, other AI tools provide recommendations to service agents during calls.

Popular built-in Chatbot for businesses

One of the true sages in the customer experience industry is Rich Dorfman, vice president of customer experience for the 120-location Eastern Bank. AI in call centers can also provide organizations with a ‘virtual customer assistant’ in some cases. Like human agents, virtual customer assistants can help reduce queue waiting times while gathering additional information for human agents who can then quickly take over and help the caller resolve their issue or question.

• AI chatbots are incredibly effective at automating repetitive work, but for anything that requires a human touch, they fall short.
• Before that, large language model (LLM) and generative AI were terms used primarily by technologists working in the field.
• It’s incredibly difficult to maintain staffing levels for a decent service level and it’s become increasingly challenging with staffing shortages gripping the country.
• AI-powered call centres can reduce costs, improve efficiency, and enhance customer experience.
• It takes automated response to a new level because it is conversational in nature and not restricted by a library and current source machine learning.
• • Cognitive AI allows software applications to mimic human behavior to solve complex problems and is closely related to machine learning or ML.

That said, once humans start chatting to machines – by voice or instant messaging – discrepancies and other signs in the conversation can reveal the unreal nature of the non-person on the other end of the line or chat box. Contact center operators aren’t deterred by these limitations and expect the technology will only improve over time. Other times, we’re either languishing on hold or are angrily navigating an endless phone tree to nowhere. In those cases, we’re grateful when a chatbot rescues us from our purgatory with a live agent or gives us the option to leave a number for a return call.

best practices for implementing AI in a call center

AI-human interactions have become second nature, and many organizations are starting to deploy the technology in the call center using natural language processing, machine learning, and automation software. Customer experience is the leading driver of AI adoption among businesses and it’s revamping call centers by simplifying agent tasks, personalizing communication more accurately, and speeding the time to customer value. AI adoption in the contact center pays off—early AI adopters report an improvement of almost 25% in customer experience ratings. Furthermore, automated customer service options like virtual agents and bots are the number one use of AI among large companies.

Additionally, AI can be used to analyze customer data and provide insights that can help improve customer service. This can reduce the call volume of live agents and affect the number of agents needed in the call center. This allows them to be more productive and have engaging, personally satisfying conversations that ultimately lead to higher customer satisfaction.

How is AI used in call centers?

Predictive call routing is when AI will match call center customers to specific customer service agents who are best able to handle an issue — whether it be because of personality models, or expertise. In a thoughtful defense of the human agents that work the front lines of contact centers, O’Flahavan said any tool, including AI, that helps create the appearance of empathy — genuine or not — is what they need. It’s a difficult job that often requires talking to angry people all day, every day — or people who could become angry a few sentences into any given conversation. Humans will harness the power of customer service AI tools to make their work easier, more accurate, and efficient. AI makes it so they don’t have to reinvent the wheel every time a new call comes in. Even when an agent doesn’t know the solution to a customer problem, AI can avail to them the entire corpus of answers their fellow agents have given, and zero in on the ones that works best.

Not every customer conversation is easy and some need personalized attention – hand off conversations to live agents seamlessly and contextually for further assistance. You can also transfer back to a virtual assistant for mid-call tasks such as collection of PII information or post-call surveys. IVR works well for companies with many calls about routine, specific, pre-service questions, such as eligibility or bank statement information.

Natural language processing

He then left the bulk of his time for the meat of the matter – how ChatGPT can be used in the contact center, and specifically how it works with Cognigy. OpenAI’s November 2022 announcement of a free research preview of ChatGPT to solicit user feedback took the tech world by storm. Before that, large language model (LLM) and generative AI were terms used primarily by technologists working in the field. Now, its use by one million users in just five days (as reported by Statista) has entered the online services history books, beating Instagram’s record of two-and-a-half months.

Thanks to AI technologies, businesses can reduce costs by revamping how their contact centers and agents operate. AI tools can also assist agents during customer conversations, providing them with real-time insights and recommendations based on the customer’s needs. One of the biggest pain points for traditional call center agents is processing high volumes of simple support queries. Dealing with these queries impedes their ability to focus on more complex tickets. What’s less known is the potential productivity gains and job creation from conversational AI.