How does artificial intelligence implementation affect firm performance: a mixed-methods study

Purpose Drawing on the resource-based theory and human-organization-technology (HOT) framework, this study investigates the impact of AI implementation on firm performance through a mixed-methods approach. Design/methodology/approach This study employs qualitative research to establish the research model. Subsequently, using 291 survey responses, structural equation analysis is used to examine the influence of AI implementation on firm performance. Findings The results of PLS-SEM show that AI infrastructure, affordability, skill variety, use capability, and responsiveness to market knowledge significantly affect business process and decision-making performance. Data quality significantly affects the decision-making performance, and innovative culture significantly affects business-process performance. Subsequently, business processes and decision-making performance significantly affect firm performance. Originality/value This study extends current knowledge on the impact of AI implementation on firm performance from technological, human, and organizational perspectives and provides valuable insights for effective AI implementation in organizations.