Does Bot Gender Matter? Theory and Evidence from a Tense Service Context

Despite the increasing use of AI-powered voicebots, our understanding of how the choice of bot gender may impact service outcomes in tense service contexts, such as debt collection, remains limited. To address this gap, we draw upon the tensions-based view of customer relationships and gender stereotype theory to hypothesize how and when voicebot gender matters in tense service contexts. We test our hypotheses using a proprietary dataset of debt-collection calls made by AI voicebots. We find that female voicebots increase the odds of a positive repayment intention by 28.3%. This gender effect is more pronounced when service encounters begin with higher tension, such as during weekdays or with initially uncooperative customers. We further show that the gender effect can be explained by the advantages of female voicebots in reducing behavioral and emotional tensions during service interactions.