Gartner: Customer Service Should Use AI to Offer Insights
January 24, 2022
user experience and process improvement are three ways artificial
intelligence (AI) can benefit customer service organizations, according
to Gartner, Inc. Service and support leaders should understand these
three benefits in order to thoroughly develop and track the right
metrics for evaluating their solutions’ effectiveness and prove business
cases for further investment.
Ensuring Optimal User Experiences – Another key benefit of AI is in how it creates optimal customer and agent experiences. AI can help guide agents’ decisions while serving customers or while performing administrative tasks, making it easier for them to perform their core job duties. Simultaneously, AI can make it easier for customers to resolve issues on their own, providing a better customer experience. Two examples of how AI is deployed to ensure optimal user experiences are chatbots, also known as conversational assistants, and language sentiment analysis.
Process Improvement – A third key benefit of AI is in the automation and augmentation of physical and software business processes. While this usage is one of the most commonly pursued AI benefits, leaders often overfocus on the automation and removal of tasks, overlooking the benefits that augmenting existing tasks can have on service operations. Automation and augmentation can reduce costs, and improve efficiency and growth potential by freeing up resources to pursue more value-added tasks. Four examples of using AI to improve customer service processes are intelligent document processing, workforce management, post call wrap-up, and task and process workflow automation via robotic process automation and process mining.
“Customer service and support leaders seeking to use AI to improve digital and self-service customer service should ensure they have sufficient, accurate and relevant data to support customer service insights and predictions use cases,” said Bern Elliot, distinguished vice president analyst at Gartner. “Successfully deployed AI requires high-quality data.”