What Is Generative AI and How Does it Apply to Customer Service and Call Centers?

Generative AI
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It’s hard to imagine an industry today that has not been directly affected by artificial intelligence (AI). The story of the human race can no longer be told without mentioning AI’s overshadowing force. Already, AI is driving the Internet of Things (IoT), robotics, big data, and other merging technologies, and there’s every reason to believe that it will continue to be an innovation driver well into the future.

According to experts, most people will enjoy significant benefits thanks to artificial intelligence. The global GDP will see a 26% increase to $15.7 trillion by 2030, driven partly by AI. 

MIT Technology Review includes generative AI in its list of the most noteworthy AI advancements in the last ten years. Gartner also lists generative AI as one of the most rapidly evolving and impactful technologies that will revolutionize productivity. 

Today, generative AI accounts for less than 1% of data produced. By 2025, Gartner predicts that this percentage will have jumped to 10%. 

Suffice it to say that generative AI is already transforming customer service and call centers. But what exactly is generative AI and how can you use it to improve contact center operations? Let’s take a look. 

What is generative AI?

Until recently, AI wasn’t seen as a viable tool for creative pursuits; it could not create something new. But with the emergence of generative AI, machines have now become capable of producing meaningful and aesthetically pleasing outputs. This technology goes beyond data analysis and rote cognitive labor by generating brand-new information all on its own.

Generative AI refers to a type of artificial intelligence that produces new data rather than just reviewing or classifying what already exists. It uses sophisticated algorithms to generate data from scratch. Machine learning is one of the most typical applications where it is used to form new images, text, and videos based on training data.

Generative AI works by learning patterns in existing datasets and then using them to create new ones. This is opening up a world of opportunity, from crafting novel molecules for medicinal use to engineering more effective algorithms to resolve optimization problems. In the customer service arena, generative AI applications can improve automation and speed up customer service responses.

As generative AI advances, it is quickly becoming less expensive and more efficient than work done by hand, and in some cases, surpassing what humans create. Every profession that requires creativity — such as social media management, games development, graphic design, coding, or product design, to name a few — will soon be revolutionized by this technology. Advertising strategies and sales processes are already being changed thanks to the power of generative AI.

What is generative AI? We asked an AI to explain

What is generative AI?

Until recently, AI wasn’t seen as a viable tool for creative pursuits; it could not create something new. But with the emergence of generative AI, machines have now become capable of producing meaningful and aesthetically pleasing outputs. This technology goes beyond data analysis and rote cognitive labor by generating brand-new information all on its own.

Generative AI refers to a type of artificial intelligence that produces new data rather than just reviewing or classifying what already exists. It uses sophisticated algorithms to generate data from scratch. Machine learning is one of the most typical applications where it is used to form new images, text, and videos based on training data.

Generative AI works by learning patterns in existing datasets and then using them to create new ones. This is opening up a world of opportunity, from crafting novel molecules for medicinal use to engineering more effective algorithms to resolve optimization problems. In the customer service arena, generative AI applications can improve automation and speed up customer service responses.

As generative AI advances, it is quickly becoming less expensive and more efficient than work done by hand, and in some cases, surpassing what humans create. Every profession that requires creativity — such as social media management, games development, graphic design, coding, or product design, to name a few — will soon be revolutionized by this technology. Advertising strategies and sales processes are already being changed thanks to the power of generative AI.

What is generative AI? We asked an AI to explain

Last month, OpenAI released ChatGPT, an AI chatbot you can ask questions to and, more often than not, get useful answers. Less than a week from its release, it had already garnered over 1 million users

In case you’re unfamiliar, ChatGPT allows you to type questions in natural language, which the chatbot responds to with a conversational, sometimes slightly robotic, voice. It considers previous queries and replies that have been provided so far, utilizing an immense amount of data found on the internet for its answers.

So, we decided to join the frenzy and ask ChatGPT to explain what generative AI is. Here’s its unedited response:

Generative AI is a type of artificial intelligence that is focused on generating new content. This can include anything from text and images to music and video. Generative AI systems use machine learning algorithms to analyze existing data and then create new content that is similar in style or content to the original data. This allows them to create new content that is original and unique, without the need for human input. Some examples of generative AI include language translation systems, image and video generation, and music generation.

Generative AI

Generative AI’s true power lies in language, not images

The fervor for AI-generated images is currently reaching its peak, with text-to-image AI models being the driving force. These groundbreaking algorithms can create breathtakingly realistic images using simple sentences. Midjourney, Stable Diffusion, and OpenAI’s DALL-E are just a few examples of how advanced generative AI has become.

Earlier this year, when text-to-image AI models emerged unexpectedly, it sparked a frantic rush of activity. Billion-dollar investment rounds for startups were everywhere, along with large launch parties and nonstop media coverage. We also witnessed numerous venture capitalists and entrepreneurs rapidly pivoting to focus on AI technology.

It is not surprising that text-to-image AI has become such a phenomenon in the public eye. Images are captivating, simple to process and share, and can spread quickly across social media platforms — all characteristics that lend themselves perfectly to the greater reach of the technology. Furthermore, text-to-image AI has immense capability; it generates realistic images with stunning complexity and creativity.

Yet, despite the current hype surrounding artificial intelligence-fueled image generation, it will be far overshadowed in terms of value creation by AI’s capacity to generate text. Over time, the power of AI-powered language production—writing and speaking—will prove much more transformative than its potential with visuals.

Language is the foundation of every industry, business, and transaction. Without it, economies and societies would crumble. By automating language, we open up the untapped potential for value creation that has never been seen before. AI-generated language will revolutionize how companies worldwide conduct business — a more significant impact than text-to-image AI which is only applicable to specific industries.

Generative AI in call centers and customer service

One of the niches in which generative AI will have the most substantial impact is customer service and call centers. Generative AI will revolutionize the customer service and call center industry, transforming it in all sectors: from hospitality to finance, healthcare to eCommerce. Even internal IT and HR help desks are set to benefit from this technology.

Language models are revolutionizing customer service conversations as they automate pre-call, in-call, and post-call activities like after-call documentation, agent coaching, and summarization. When combined with advanced text-to-speech technology, these language models will soon take over the entire customer engagement process without needing human interference; unlike traditional call centers that follow strict rules, this transitions into an easygoing, natural conversation indistinguishable from an actual human. Almost all conversations your business has with consumers on any subject will be automated.

Having tailored, personalized responses at your disposal can bring customer support conversations to a new level. Conventional chatbots are usually scripted and lack sufficient machine learning and natural language processing capabilities. Nowadays, however, AI-powered chatbots that leverage external databases have become adept at responding swiftly to complex customer queries, holding more meaningful discussions, and escalating the conversation to humans when necessary.

Although it’s a relatively new technology, some companies have already adopted generative AI. Bank of America has even implemented its own virtual assistant powered by generative AI. The virtual assistant interacts with Bank of America customers via voice commands, text, or simply tapping options in natural language. The bank’s customers have already used it more than 1 billion times since its launch four years ago. It’s an incredible example of how powerful this technology can be.

Generative AI can help drive better customer experiences and increase efficiency in call centers. Call center agents can respond more quickly and accurately to customers’ queries using generative models to generate answers automatically. This technology also helps reduce the need for manual data entry and improves customer service overall, ultimately leading to higher customer satisfaction.

Gartner analysts have predicted that the call center industry will likely save  as much as $80 billion by 2026 if they switch from human employees to AI chatbots. Consequently, more and more customer service companies are investing in conversational AI solutions to access these potential savings. As technologies around text-to-speech models and natural language processing continue to develop, it’s becoming increasingly difficult for people to differentiate when they interact with humans and when they interact with bots.

The battle with agent staff shortages and labor expenses can be harrowing for many contact centers. Conversational AI makes agents more efficient and successful while providing customers a better experience. By the close of this year, the estimated 17 million contact centers worldwide are projected to have spent almost $2 billion on AI software.

According to Gartner’s estimation, the number of agent interactions performed by conversational AI will skyrocket from 1.6% today to a staggering 10% over the next four years. This increase in automation will primarily come in two forms: simulated voice bots and text-based chatbots, which are already beginning their steady rise into prominence across various industries.

Here’s a rundown of ways that generative AI is transforming the customer experience in call centers.

Automated customer service

With generative AI, businesses can automate their customer service experience. By blending advanced machine learning technology with natural language processing, generative AI instantly generates personalized answers to questions, freeing up customer support teams to focus on more value-adding activities while still providing exceptional service.

Generative AI is a powerful tool, as it can be taught to understand customer needs and desires by analyzing existing ticket data and other client communications. It also can effectively direct complex queries to the right departments, making automated customer service more efficient.

Improved customer satisfaction

By leveraging generative AI, businesses can quickly and accurately resolve customer queries — often before they even become aware of a problem. With automated customer service, customers are more likely to achieve the resolution they need faster — leading to greater satisfaction and loyalty in the long run.

Increased customer service team productivity

Generative AI can increase productivity and efficiency by reducing the load on customer service teams. By taking on mundane tasks, such as simple question-and-answer scenarios, customer service teams can focus more on value-adding tasks and develop deeper relationships with their customers. This can ultimately lead to improved customer satisfaction and a greater return on investment for the business.

Conclusion

With customer service teams’ workloads constantly increasing and customers demanding more efficient, responsive customer service, generative AI is quickly becoming an invaluable tool for call centers. Generative models allow businesses to automate their customer service experience while providing a personalized response to each query. As a result, customer service teams can focus on value-adding tasks and build meaningful customer relationships. 

By incorporating generative AI into their customer service strategy, contact centers can take advantage of the potential cost savings and improved customer satisfaction from automated customer service. It’s the easiest way to drive more efficiency across your contact center while improving first contact resolution rates and keeping customers and agents satisfied. What’s not to like?

To see the transformative power of generative AI with your own eyes, request a demo of Level AI today.

Get a free demo today!

Your customers will thank you for it!

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