Redefining work and building organizational agility through artificial intelligence in selected financing and lending institutions
Angel Marie D. Gonzales & Ali G. Mamaclay
Abstract
This study examines how artificial intelligence (AI) adoption reshapes work and enhances organizational agility in selected financing and lending institutions in Cabanatuan City, Philippines, 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.
Keywords
sociotechnical systems, employee adaptation, employee engagement, human–AI collaboration
Author information & Contribution
Angel Marie D. Gonzales. Corresponding author. Doctor of Philosophy in Business Administration, Wesleyan University-Philippines. Email: hrd.angelgonzales@gmail.com
Ali G. Mamaclay. Doctor of Philosophy in Business Administration. Faculty Graduate School, Wesleyan University-Philippines. Email: agmamaclay@wesleyan.edu.ph
"All authors equally contributed to the conception, design, preparation, data gathering and analysis, and writing of the manuscript. All authors read and approved of the final manuscript."
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was not supported by any funding.
AI Declaration
The author declares the use of Artificial Intelligence (AI) in writing this paper. In particular, the author used Microsoft Copilot and ChatGPT in searching for appropriate literature, summarizing key points, restructuring language/sentences, and improving clarity. The author takes full responsibility in ensuring proper review and editing of content generated using AI.
Notes
This paper is presented at the 7th International Conference on Multidisciplinary Industry and Academic Research (ICMIAR)-2026
Acknowledgement
First and foremost, heartfelt appreciation is extended to Almighty God for His guidance, wisdom, strength, and countless blessings throughout this journey.
The researcher sincerely thanks his adviser and co-author for the invaluable guidance, encouragement, and constructive recommendations that greatly contributed to the improvement of this study.
The researcher is deeply grateful to the participating financing and lending institutions in Cabanatuan City for their cooperation, openness, and willingness to share information necessary for the completion of this study.
Appreciation is likewise extended to colleagues, friends, and associates who provided encouragement, support, and motivation during the conduct of this research.
Most importantly, the researcher expresses profound gratitude to her family for their unwavering love, understanding, prayers, and support, which served as a source of inspiration throughout this endeavor.
To all who have contributed in one way or another, the researcher offers her sincere thanks.
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Cite this article:
Gonzales, A.M.D. & Mamaclay, A.G. (2026). Redefining work and building organizational agility through artificial intelligence in selected financing and lending institutions. Industry and Academic Research Review, 4(1), 1-19. https://doi.org/10.53378/iarr.230
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