Factors Affecting Human-AI Collaboration Performances in Financial Sector: Sustainable Service Development Perspective

Abstract

Recent advances in generative artificial intelligence (Gen AI) enable financial services firms to enhance operational efficiency and foster innovation through human-AI collaboration, yet also pose technical and managerial challenges. Drawing on collaboration theory and prior research, this study examines how employee skills, data reliability, trusted systems, and effective management jointly influence innovation capability and managerial performance in Gen AI-supported work environments. Through survey design, data were collected from China's financial sector and analyzed using multiple regression analyses and fuzzy-set qualitative comparative analysis (fsQCA). The findings show that all four factors exert a positive influence on innovation capability and managerial performance, with innovation capability acting as a partial mediator. Complementarily, fsQCA identifies distinct configurations of these factors that lead to high levels of innovation capability and managerial performance. To fully leverage human-Gen AI collaboration, financial services firms should upskill employees, strengthen data reliability through robust governance, establish trusted AI systems, and effectively integrate Gen AI into workflows through strong managerial oversight. These findings provide actionable insights for talent development, data governance, and workflow optimization, ultimately enhancing firms' resilience, adaptability, and long-term sustainability in financial services.