This study examines how artificial intelligence (AI) adoption reshapes work and enhances organizational agility in selected financing and lending institutions in Cabanatuan City, guided by Sociotechnical Systems (STS) Theory. Using a quantitative descriptive–correlational design, data were collected from 120 managers and employees across 20 institutions through a validated survey instrument. The study assessed AI adoption across the social subsystem (redefinition of human roles, employee adaptation, and engagement), technical subsystem (AI capability, task–technology fit, and system usability), and the human–technology interface (human–AI collaboration quality and workflow integration). Descriptive and inferential analyses, including Pearson correlation and structural modeling, were employed. Results reveal strong and statistically significant relationships between the social and technical subsystems (r = 0.909, p < 0.01) and between the technical subsystem and the human–technology interface (r = 0.922, p < 0.01). Findings indicate that AI functions primarily as a complementary tool, enhancing employee adaptability, engagement, decision quality, and workflow efficiency rather than replacing human roles. The study contributes empirical evidence supporting the joint optimization of human and technological elements and offers policy directions for human-centered, ethical, and agile AI integration in financial institutions.