The surge of generative artificial intelligence (AI) applications is spurring exciting innovations and consumer experiments, but it also worries many people who are concerned about data privacy or only being able to communicate with a company through a bot. These concerns are especially acute in industries where customer interactions and data privacy are critical, such as banking or healthcare.
Some level of anxiety typically accompanies breakthrough technologies, and it’s natural to worry about a technology that mimics human intelligence. As this new class of large language models has emerged, however, most companies have put model risk, accuracy of the model’s output, and ethical use of data at the heart of their risk frameworks. They aim to ensure responsible uses of new AI technology.
Less appreciated is the risk that companies will cede the customer experience to models and bots designed to extract value in the short term, not to foster long-term customer loyalty. Companies might increasingly pair traditional AI and machine learning models with generative AI to deliver messages and offers to customers in more human-like ways. If we are not careful, profit-seeking bots, algorithms, and predictive models could indeed lead to dystopian experiences.
Even in the world of AI, customer love should lead the way. Traditional metrics of customer sentiment, such as Net Promoter Score (NPS), may start to look different, but one premise will endure: Every interaction enhances or diminishes a customer’s perception the company involved.
Informing each decision with the goal of enriching customers’ lives will lay down a reliable route to an AI-enabled future that creates more value for customers, employees, and shareholders. In fact, early published results from researchers at Stanford University and Massachusetts Institute of Technology show favorable effects from the rollout of an AI-based conversational assistant tool to 5,200 customer support agents in several countries. Not only did the tool raise agent productivity by 14% on average, but the AI-assisted interactions had higher average NPS, and monthly agent attrition dropped by 9%.
Continue reading: https://hbr.org/2023/08/using-ai-to-build-stronger-connections-with-customers