The research, forthcoming within the Journal of Marketing, is titled “Bad News? Send an AI. Good News? Send a Human” and is authored by Aaron Garvey, TaeWoo Kim, Adam Duhachek.
Are we extra forgiving of a man-made intelligence (AI) agent than a human once we are let down? Less appreciative of an AI bot than a human once we are helped? New analysis examines these questions and discovers that customers reply otherwise to favorable and unfavorable remedy by the hands of an AI agent versus one other human.
Consumers and advertising and marketing managers presently are in a interval of technological transition the place AI brokers are more and more changing human representatives. AI brokers have been adopted throughout a broad vary of shopper domains to deal with buyer transactions, together with conventional retail, journey, experience and residence sharing, and even authorized and medical providers. Given AI brokers’ superior data processing capabilities and labor price benefits, the transition away from human representatives for administering product and providers is anticipated to proceed. However, what are the implications for buyer response and satisfaction?
The researchers discover that when a services or products supply is worse than anticipated, customers reply higher when coping with an AI agent. In distinction, for a proposal that’s higher than anticipated, customers reply extra favorably to a human agent.
Garvey explains that “This happens because AI agents, compared to human agents, are perceived to have weaker personal intentions when making decisions. That is, since an AI agent is a non-human machine, consumers typically do not believe that an AI agent’s behavior is driven by underlying selfishness or kindness.” As a consequence, customers consider that AI brokers lack egocentric intentions (which might sometimes be punished) within the case of an unfavorable supply and lack benevolent intentions (which might sometimes be rewarded) within the case of a positive supply.
Designing an AI agent to seem extra humanlike can change shopper response. For instance, a service robotic that seems extra humanlike (e.g., with human physique construction and facial options) elicits extra favorable responses to a better-than-expected supply than a extra machinelike AI agent with out human options. This happens as a result of AI brokers which might be extra humanlike are perceived to have stronger intentions when making the supply.
What does this imply for advertising and marketing managers? Kim says, “For a marketer who is about to deliver bad news to a customer, an AI representative will improve that customer’s response. This would be the best approach for negative situations such as unexpectedly high price offers, cancellations, delays, negative evaluations, status changes, product defects, rejections, service failures, and stockouts. However, good news is best delivered by a human. Unexpectedly positive outcomes could include expedited deliveries, rebates, upgrades, service bundles, exclusive offers, loyalty rewards and customer promotions.”
Managers can apply our findings to prioritize (vs. postpone) human to AI function transitions in conditions the place damaging (vs. constructive) interactions are extra frequent. Moreover, even when a task transition isn’t totally handed to an AI agent, the selective recruitment of an AI agent to reveal sure damaging data may nonetheless be advantageous.
Firms which have already transitioned to consumer-facing AI brokers, together with the multitude of on-line and cell functions that use AI-based algorithms to create and administer provides, additionally stand to profit from our findings. Our analysis reveals that AI brokers ought to be selectively made to seem roughly humanlike relying upon the scenario.
For customers, these findings reveal a “blind spot” when coping with AI brokers, significantly when contemplating provides that fall in need of expectations. Indeed, the analysis reveals an moral dilemma round the usage of AI brokers – is it applicable to make use of AI to bypass shopper resistance to poor provides? “We hope that making consumers aware of this phenomenon will improve their decision quality when dealing with AI agents, while also providing marketing managers techniques, such as making AI more humanlike in certain contexts, for managing this dilemma,” says Duhachek.
Source: Eurekalert
