Exploring the Impact of Technology Dominance on Audit Professionalism through Data Analytic-Driven Healthcare Audits

Abstract

ABSTRACT Artificial intelligence (AI)-enabled tools and analytics hold the potential to radically alter audit processes by disseminating centralized audit expertise. We examine this potential in the context of data analytic-driven audits mandated to reduce fraud, waste, and abuse in a government-sponsored healthcare program. To do so, we draw on semistructured interviews with healthcare providers (i.e., auditees) subject to healthcare audits. Our work shows how use of paraprofessional auditors guided by AI-enabled tools and analytics reflects a very different audit environment. Specifically, auditees’ experiences suggest paraprofessional auditors lack specific expertise and credentials to conduct data-driven audits, apply judgment in deference to technology, and disregard the impact of AI-driven decisions on the public interest. Such experiences raise potential concerns for all audits over unbridled use of AI-enabled tools and analytics by novice-level auditors/paraprofessionals, but even more for audits conducted in contexts where adherence to professional norms is essential to minimizing public interest consequences. JEL Classifications: M42; M48.