6 ways AI can influence the future of customer service

Organizations have always used some degree of technology to provide an excellent customer experience, but the future of customer service will demand even more advancements to meet customers’ growing expectations.

There is no question that customer service is about to take a massive leap forward, thanks to emerging trends like artificial intelligence (AI). In fact, nearly 50% of CEOs feel increased customer expectations that organizations will accelerate the use of new technologies like generative AI, according to an IBV CEO Guide to Generative AI for Customer Service study. Undoubtedly, the future of customer service must be AI-based for organizations to improve the customer experience and increase customer loyalty.

In a recent report, Gartner predicted that 80% of customer service and support organizations will be applying generative AI technology to improve the customer service experience. In short, CEOs know how important generative AI and other AI technologies are becoming to create a future-proof customer service strategy.

The stakes are incredibly high, especially since the COVID-19 pandemic when customers increased their likelihood of switching brands. Studies have shown that 80% of customers (link resides outside of ibm.com) are likely to switch to a competitor after more than one bad experience with a brand. Customer support is an incredibly important defense against customer turnover.

We’re at an exciting time in the history of customer service where organizations can experiment with these new tools and build a path towards a world where AI is the copilot for every customer interaction. The same IBV study found that 63% of executives expect to have already invested in generative AI use cases to serve agents directly by the end of 2023.

AI will become the central brain of the contact center, where the organization interacts with the customer base. AI-powered customer service does not necessarily mean that all interactions will be self-serve. It instead means human support teams will utilize AI and machine learning tools as they are helping customers.

While front-line workers will continue to be an integral part of any customer service interaction, the use of new technologies is quickly becoming a competitive advantage.

Here are six AI-based customer service trends that will help provide better customer service across the entire customer journey.

Generative AI-based customer service team training

All talent development will benefit from personalized training built on generative AI, but customer service training will see specific benefits. As issues can vary from customer to customer, customer service reps will need to remain agile when assisting customers. By using generative AI to train unique scenarios that could occur in real situations, reps will be more adept at handling whatever customer issue comes their way.

AI-driven personalization

Organizations looking to increase customer satisfaction should look to meet those customers’ needs before an issue occurs. For example, an organization can use AI to send personalized emails to new customers explaining the benefits and uses of their new products based on the customer profile.

Generative AI call scripts

Organizations are increasingly creating the ability for agents to interact directly with tech applications to deliver instant assistance to customers. Some customers will still want to talk to a human, but those customer service agents at call centers are increasingly enhanced by generative AI scripts and workflows that can update in real-time. This way, customer care representatives have updated information on hand so they can confidently solve the customer’s issue.

Conversational AI bots

Traditional chatbots, while helpful, are somewhat limited by the static scripts on which they are programmed. Conversational AI bots will be better able to react to inputs from customers and update in real-time with new information. These bots get closer to feeling like a human interaction and are more likely to effectively help customers. They will provide a more engaging and personalized experience for customers who prefer self-service tools.

AI-driven insights from customer data

AI excels at finding patterns in data that would either take humans too long to unearth or might otherwise go undetected. Organizations can use AI to analyze the complete history of omnichannel customer experience from customer service call transcripts, emails, social media and forum posts and customer relationship management (CRM) platforms to make smarter decisions. It can also feed back data if customers repeatedly misuse the product; in this case, the organization can create more specific instructions that warn against using the solution incorrectly.

Generative AI-based frequently asked questions (FAQs)

Organizations can no longer draft FAQs based on their own knowledge and forget about updating them for months or years. In our fast-paced world, FAQs need to update constantly, to reflect new issues or uses of the solution. Organizations can use AI to analyze customer calls, emails and social media posts to compile the most frequent questions. Then generative AI tools can utilize the customer care playbook to create the most helpful responses to help with customer retention.

Providing great customer service requires organizations to use every tool at their disposal. As newer technologies like AI become more prevalent, organizations should seek to utilize them for every business unit and support team.

IBM has been helping enterprises apply trusted AI in this space for more than a decade, and generative AI has further potential to significantly transform customer and field service with the ability to understand complex inquiries and generate more human-like, conversational responses.

IBM offers end-to-end consulting capabilities in experience design and service, data and AI transformation. By using the watsonx™ portfolio of AI products and watsonx™ Assistant, IBM’s market-leading conversational AI solution, we partner with you through the AI value creation process to enhance conversational AI, improve the agent experience and optimize call center operations and data analytics.