Customer service is proving to be one of the most popular applications of generative AI. But how exactly can generative AI aid customer service teams (without alienating customers)? And which companies are already making great use of generative AI? Read on to find out.

The Capabilities Of Generative AI

One of the obvious uses of generative AI is customer-facing chatbots. If you’ve ever had a frustrating interaction with a chatbot that is not particularly helpful, take heart because, with tools like ChatGPT, organizations can create chatbots that better understand customer queries and respond with much greater accuracy and nuance. They can also handle a large volume of queries efficiently and provide more personalized responses over time.

Traditional AI offerings (like some of the not-very-intelligent chatbots you might have interacted with) rely on rules-based systems to provide predetermined responses to questions. And when they come up against a query that they don’t recognize or don’t follow defined rules, they’re stuck. And even when they do give a helpful answer, the language is typically pretty stiff. But a tool like ChatGPT, on the other hand, can understand even complex questions and answer in a more natural, conversational way.

In fact, ChatGPT is so good that UK energy supplier Octopus Energy has built conversational AI into its customer service channels and says that it is now responsible for handling inquiries. The bot reportedly does the work of 250 people and receives higher customer satisfaction ratings than human customer service agents. This is a prime example of how contact centers will increasingly incorporate generative AI chat and voice tools to deal with straightforward, easily repeatable tasks. And, of course, these tools give customers 24/7 access to support, 365 days a year, via multiple channels (such as phone, online chat, and social media messaging).

But answering customer questions isn’t the only way generative AI can add value in customer service. Some of the other tasks that generative AI can do or assist with include:

· Giving customers personalized recommendations based on the customer’s data and previous interactions further helps to enhance the customer experience.

· Providing conversational search functions for, say, FAQs online. Generative AI can take natural language prompts like “Where’s my package?” and either direct the customer to the correct FAQ response or deliver a tailored response. Plus, this can be done in multiple languages.

· Optimizing data to support customer service operations. Generative AI can handle vast amounts of data and turn that information into actionable insights – insights such as “Which are our most common complaints?” It can also track and categorize customer trends.

· Supporting human customer service agents. Generative AI can help human agents be more productive. For example, it can automatically generate responses to common queries, provide summaries of previous complaints and resolutions that agents can use in conversations, and generate product recommendations.

In this way, generative AI can support the work that human agents do and free them up to focus on more complex customer interactions where they can add the most value.

How John Hancock Has Boosted Its Customer Service With Conversational AI Tools

We’ve already seen how one company has improved its customer service function with generative AI. Now, let’s turn to another example. John Hancock, the US arm of global financial services provider Manulife, has been supporting customers for more than 160 years. But this doesn’t stop the life insurance company from embracing the latest technology.

The company has partnered with Microsoft to implement conversational AI tools, including Azure Bot Service, to provide support for common customer queries and issues. Like many companies, at the start of the COVID-19 pandemic, John Hancock contact centers saw a spike in calls, meaning the company needed new ways to help customers access the answers they needed. So they turned to Microsoft to help set up chatbot assistants that could handle general inquiries – thus reducing the total number of message center and phone inquiries and freeing up contact center employees.

In other words, this allows human contact center workers to focus their efforts on more complex cases – those calls that really require their expertise, as opposed to generic queries like “How do I reset my password?” As a result, team members enjoy a better work experience and more manageable workloads – while customers enjoy reduced wait times and a better service experience. As Tracy Kelly, AVP of contact center and LTC operations, puts it, “The call reduction due to chatbot innovation equates to impressive cost savings we’ve been able to reinvest in our customer contact centers…”

Plus, as an added bonus, the customer service team is being upskilled in valuable AI skills, thereby helping to future-proof their jobs.

It’s no wonder customer service has become CEOs’ number one generative AI priority, according to the IBM Institute for Business Value, with 85 percent of execs saying generative AI will be interacting directly with their customers within the next two years. Those companies that ignore the generative AI trend clearly risk being left behind.