Empowered generative artificial intelligence in retail service recovery: Recovery justice, customer effort reduction, trust restoration, and purchase behaviour

Retailers increasingly deploy generative artificial intelligence (GenAI) to handle complaints, yet evidence remains limited on when these agents restore purchasing rather than merely improve immediate evaluations. We develop a configuration model in which recovery agent identity (GenAI versus human) is separated from recovery agent empowerment, defined as authority to complete a remedy during the encounter. Across a qualitative study, two pretests, two randomised experiments, and two secondary-data studies in United Kingdom retailing, we examine perceived recovery justice, customer effort reduction, and trust restoration as mechanisms linking recovery configurations to subsequent behaviour. The experiments capture an incentivised purchase choice, whereas the field studies observe repeat purchase, spending, time to next purchase, and churn. GenAI was not inherently superior to a human agent. Its advantage emerged when it had visible and executable authority to issue refunds, replacements, delivery upgrades, or account credits. Empowered GenAI improved justice, reduced effort, and restored trust, and generated the strongest purchase outcomes. Failure severity weakened this advantage, while customer relationship strength amplified both the penalty for low-empowerment GenAI and the reward for empowered GenAI. The study contributes an authority-identity decoupling perspective: customers respond not only to who communicates, but also to whether the recovery architecture gives that agent the data access, decision rights, and operational capability required to act. The findings support selective empowerment for routine failures and accountable hybrid escalation for severe or data-constrained cases.