Date of Publication

4-12-2025

Document Type

Master's Thesis

Degree Name

Master of Science in Industrial Relations Management

Subject Categories

Commercial Law

College

Ramon V. Del Rosario College of Business

Department/Unit

Commercial Law

Thesis Advisor

Atty. Neptali B. Salvanera

Defense Panel Chair

Dr. Jocelyn P. Cruz

Defense Panel Member

Atty. Charito Fariñas-Rodriguez

Atty. Severo C. Madrona Jr.

Abstract (English)

The use of artificial intelligence (AI) in the organization is rapidly changing the ways of working - and human resource professionals have a critical role to play. As HR continues to support navigating changes and digital transformations, its function is not exempt from doing so. In the Philippines, the banking industry is at the forefront of AI’s integration in its operations and customer services. But there is a spark of interest in expanding its use to other business areas such as human resource management (HRM).

This study examines behavioral intention to use artificial intelligence in human resource management, including the factors influencing it and moderating their relationships. A theoretical framework called ‘unified theory of acceptance and use of technology (UTAUT)’ was adopted in this study, where four variables were identified to determine intention to use: performance expectancy, effort expectancy, social influence, and facilitating conditions. In this study, age was employed in the model and considered a moderating variable for each pairwise. Following a sequential mixed methods approach, data were collected in two stages: 1) quantitative via an online questionnaire, and 2) qualitative via in-depth interviews. Each strand was analyzed using a multilinear regression and thematic analysis, respectively. The participants in this study were HR employees in the banks within NCR, Philippines.

The Multiple Linear Regression Model revealed a high positive and statistically significant aggregate score for all statements in the behavioral intention to use. This means that HR employees are receptive to the use of AI in managing human resources and that they intend to use this tool for work regularly and in the future. And while the model indicates all four UTAUT constructs are contributing to the participants’ behavioral intention to use AI, only effort expectancy and facilitating conditions are strong predictors, and age has no moderating effect. This means that these two variables significantly influence HR employees’ behavioral intention to use artificial intelligence in human resource management. Interestingly, this came out contrary to expectations, as several studies have shown that performance expectancy and social influence have a significant influence on intention.

The themes that emerged from the Thematic Analysis support the quantitative findings, as employees intend to use them for work with accessibility to the tool itself, the resources to train them on its use, and the support to enable them – a similar intention that comes with knowledge and ease of use. Though the lack of knowledge of AI’s capabilities and restrictions due to access privileges has limited their perception of what the technology can do for them, in terms of work efficiency and effectiveness. The employees also acknowledged how the people around them may affect their stance on its acceptance, but they expressed the need to use AI to be digitally literate and be future-ready. This study significantly contributes to the growing literature on human resource development, UTAUT-based adoption research, artificial intelligence, and its use in an organizational context. This study recommends further research in the Philippine context to expound and explore the empirical evidence, generating new insights and potential breakthroughs.

Keywords: UTAUT, artificial intelligence, human resources, banking industry, Philippines

Abstract Format

html

Abstract (Filipino)

None

Abstract Format

html

Language

English

Format

Electronic

Keywords

Artificial intelligence; Personnel management

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Embargo Period

4-12-2028

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Available for download on Wednesday, April 12, 2028

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