EXPLORING CUSTOMER PERCEPTIONS OF ARTIFICIAL INTELLIGENCE AND SERVICE FAILURE RECOVERY

For some time, debate has been taking place around consumer behaviour and actions in relation to AI agent service failure vs human agents service failure and how organisations design appropriate recovery and response strategies to counteract these challenges. Artificial intelligence (AI) is a growing contemporary issue that is heavily leveraged by organisations as part of their marketing strategies. Drawing on existing literature and a number of relevant concepts from the field of AI agent service failure and service failure recovery strategies, the current study utilises expectation discrepancy theory and frustration aggression theory to develop a conceptual framework to explore the perceptions of various customer segments when it comes to AI agent manipulation ‘behind the scenes’ by humans. We explore the impact of such perceptions on the perceived fairness of offer (AI agent vs human agent failure). The findings reveal the complexity of AI agent vs human agent preferences by various customer segments and factors which shape customer expectations and their impact on perceived fairness of price offer.