Customer Service is the Proving Ground for Generative AI
Customer service is on the cutting edge of generative AI, a capability that navigates uncharted territory and creates unprecedented business value. In fact, as this new technology transforms how work gets done across the enterprise, customer service has become a top adoption priority for C-level executives. This isn't surprising, as it's the natural next step for companies that have been using traditional artificial intelligence in customer service for years.
From chatting with customers to creating targeted content to optimizing call and contact center performance, generative AI is taking customer service transformation to the next level. By delivering dynamic, personalized experiences for both customers and human agents, it significantly enhances traditional AI and has the potential to dramatically change productivity and effectiveness. If you make the right bets, you can expect exponential returns, but where your business should invest depends on where you start.
Every leader we surveyed said their organization plans to use generative AI for customer service, and 67% say they have already started.
So where do business leaders at different stages of their AI journeys see the most potential? To answer this question, the IBM Institute for Business Value (IBM IBV) surveyed nearly 1,500 customer service managers, directors, and executives across 34 countries and all major industries whose organizations have been using conversational AI for at least 12 months. We asked how their organizations are currently using generative AI in customer service, which use cases show the greatest potential, and where the technology is already delivering the most business value through automation and augmentation.
Overall, customer service leaders agree that adopting generative AI is essential to their business. In fact, 100% of respondents said their company plans to use generative AI in customer service, and 67% said they have already started. More than half of these organizations (54%) have deployed generative AI in one to four customer service use cases.
But not all organizations plan to use generative AI in the same way. Our data shows that the number of years an organization has used conversational AI, designed to understand and respond to customer inquiries in natural language, is a strong predictor of whether the organization will be an early adopter of generative AI. We find that organizations with the most experience using conversational AI in customer interactions have the confidence to act boldly and implement more sophisticated use cases. For example, 89% of organizations that have been using conversational AI in customer service for at least three years are already using generative AI to directly answer customer inquiries.
65% of customer service leaders expect the combined use of generative and conversational AI to improve customer satisfaction.
But our research also reveals that generative AI, when used in conjunction with conversational AI, can improve customer experience, support agents, and deliver significant business benefits, regardless of an organization's AI experience. While veterans certainly deliver best-in-class performance, novices may gain the greatest advantage over their peers. This means that regardless of maturity level, organizations have the opportunity to deliver better customer support, outperform competitors, increase customer engagement, and realize breakthrough performance improvements. All they need is to know the best next steps to take.
AI gets nitro boost
When conversational AI emerged, it helped businesses improve on early chatbot experiences that were driven by rules-based systems and returned predefined responses. These early AI systems were primarily used to address common, easily answered customer questions and had limited functionality.
Conversational AI has improved chatbot experiences by leveraging natural language processing (NLP) and machine learning algorithms to understand and respond to customer questions. When properly trained, these AI models become more human than machine. However, while these enhanced AI assistants can successfully execute much more complex interactions, their capabilities eventually hit a wall.
Generative AI offers the next evolution in AI technology. It uses natural language generation and customer data to answer customer questions with more fluent, contextual responses. It can also leverage a customer's interaction history to customize responses and provide more personalized responses. These capabilities allow customers to chat with a generative AI assistant just like they would with a human agent.
Over 40% of organizations use generative AI to create test cases to train conversational AI.
Moreover, the uses of generative AI go far beyond direct customer interactions: the technology can enhance customer service functions more generally by supporting customer service agent training, improving personalization, translating content, and predicting future customer behavior to improve agent productivity. It can also support customer-facing conversational AI by generating test cases and dialogs, and reviewing interactions to identify opportunities for improvement.
Experience matters, but generative AI is the tide that floats all boats
Our research shows that, on average, all organizations using generative AI in customer service report higher customer satisfaction than those that don’t. However, organizations that have been using conversational AI for longer report the best business outcomes overall.
Bold Step Forward: Veterans experiment with more customer-facing use cases than novices.
Download the report to learn how organizations are currently using generative AI in customer service, how it impacts key performance metrics like cost per contact and ROI, and what approaches work best for beginners and veterans. Then read our action guides outlining how organizations in each group can optimize generative AI to derive the most value.
