ArticleFrontiers in artificial intelligence2026
Factors influencing intention to use AI in business decision making among professional employees in Malaysia's financial industry.
Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: This research investigates the factors influencing professional employees' intentions to use AI in business decision-making within Malaysia's financial industry by integrating the Technology Acceptance Model (TAM) with the Value-Based Adoption Model (VAM). More specifically, the study examines how perceived usefulness, perceived ease of use, perceived enjoyment, perceived risk, perceived value, and attitude jointly influence behavioral intention to use artificial intelligence. Research design and methodology: A quantitative approach used structured online questionnaires distributed to 210 professional employees across various Malaysian financial institutions (digital financial services, banking, insurance, investment management, and provident funds). Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4 to assess the measurement model and test the eleven hypothesized relationships. Findings: The integrated TAM-VAM framework explained 74% of the variance in AI use intention, with seven of eleven hypotheses supported. Attitude was the strongest direct predictor of intention ( Research limitations: This study used convenience and snowball sampling within Malaysia's financial sector, which may introduce selection bias and limit generalizability. The sample overrepresented FinTech employees (50.5%), who may hold more favorable views toward AI compared to employees in traditional banking or insurance. Moreover, the cross-sectional design captured perceptions at a single point in time and measured behavioral intention rather than actual usage behavior, further limiting external validity. Practical/theoretical implications: Theoretically, this research extends technology acceptance theory by validating the integrated TAM-VAM framework in emerging markets, showing that value-based mechanisms mediate utilitarian perceptions' influence on attitudes. Findings offer valuable insights for financial institutions' AI implementation, vendors' user-centered solutions, and policymakers' supportive regulatory frameworks for responsible AI use in Malaysia's financial sector.
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