Artificial intelligence (AI) and automation as a workforce disruptor is a genie out of the bottle. The Brookings Institute, a little more than a year ago projected about 25% disruption of the U.S. workforce – about 36 million jobs – in the coming decades. But at the same time, the needle also is moving on A.I.’s transformation of how businesses and their customers interact.
To give this collective shift more context, AI has moved from replacing jobs associated with inspecting equipment, manufacturing goods, repairing things to replacing humans in thinking tasks–the likes of data dives and calculations. The shift originated in the Industrial Revolution and gave rise to the current “Thinking Economy.” Just as the industrial revolution automated physical tasks by decreasing the value of human strength and increasing the value of human cognition, AI taking over thinking tasks is further reshaping the landscape and ushering in a “Feeling Economy.”
AI in this Feeling Economy is doing more of the ‘brain’ work. Subsequently, humans increasingly are handling the ‘heart’ work, including social interaction, emotion recognition, nuanced communication and genuine care for customers. In the workplace, the feeling tasks of jobs – communicating with co-workers and clients, selling to or persuading others, and building and maintaining interpersonal relationships – are more important than the thinking tasks of jobs.
The rapid proliferation of “thinking AI” also is significantly transforming the goods and services marketplace. The consumer interface to the business often is AI-driven.
Online-connected consumers with smartphones can tap digital assistants — from Apple’s Siri, to Google Assistant, to Amazon’s Alexa, Samsung’s Bixby, and Microsoft’s Cortana — to answer questions, order supplies and control home electronics among other capabilities, some of which have not even been thought of yet. As time goes by, as digital assistants become more understanding of such things as context and can do a better job of personalization. GPS navigation systems, such as Waze and Google Maps, simplify the difficult navigation task of finding destinations, even if the consumer has never been to those destinations before.
The machine-to-machine transactions — consumers purchasing via the likes of Amazon Prime through Amazon’s website or app, for example — leaves the emotional connection largely to humans. To match the emotionality of the consumer, the customer-facing personnel must become more empathetic, which in turn makes the consumer even more emotionally driven – requiring greater feeling intelligence on the part of the business.
Further consider the case of the customer service representative, whose easy, repetitive tasks like providing information and making appointments are being taken over by A.I. In this context, a consumer with a non-routine problem is much more likely to be emotionally involved, and the service person to whom AI escalates the problem will need to be much more empathetic than the traditional customer service person. The emotionality of the consumer forms a feedback loop: the consumer is more emotional, so the business must become more emotional, which makes the consumer even more emotional, and so on.
In our new book, The Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy, we describe a real-life scenario reflecting the thinking-to-feeling transition happening in customer service:
A recent doctoral graduate, an African-American man named Jared, was trying to buy a car. He started out with one salesperson, who took a more thinking-oriented approach. This was a good match for Jared, because PhDs are among the most thinking-oriented people on Earth. The salesperson, being good at his job, was trying to match Jared’s interaction preferences. Unfortunately, Jared was then passed off to an African American salesperson, no doubt to try to match Jared’s cultural background and ethnicity. This salesperson, knowing that business needs to be more emotional as time goes by, tried an emotional approach with Jared, calling him “my Black brother,” and using other emotional appeals. Such an approach will work the vast majority of the time as consumers become more emotionally driven. For Jared, though, it was not what he needed. The one thing we know, however, is that there will be fewer and fewer thinking-oriented consumers like Jared.
As thinking AI is making consumers more feeling-oriented—from their product expectations to their everyday life—companies can take advantage of this trend by tailoring sales, marketing and service to meet the needs of these increasingly emotionally-driven buyers.
About the Authors
Roland T. Rust is Distinguished University Professor, David Bruce Smith Chair in Marketing, and founder and Executive Director of the Center for Excellence in Service at the University of Maryland’s Robert H. Smith School of Business. An award-winning scholar, he has edited several major journals and consulted with American Airlines, AT&T, Dupont, Eli Lilly, FedEx, Lockheed Martin, Microsoft, NASA, and Sony, among many companies worldwide. Ming-Hui Huang is Distinguished Professor in the College of Management at National Taiwan University. A Fellow of the European Marketing Academy, she also is International Research Fellow of the Centre for Corporate Reputation at the University of Oxford, UK, Distinguished Research Fellow of the Center for Excellence in Service at Maryland Smith and incoming Editor-in-Chief of the Journal of Service Research. Their book, The Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy (Springer International Publishing; January 2021), can be found at https://www.amazon.com/Feeling-Economy-Artificial-Intelligence-Creating/dp/3030529762.
Related content from StrategyDriven