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11. AI Tools Adoption and Utilization Impact: Extending TAM Framework and Exploring Relevance to Job Performance Among Bengaluru IT Professionals

  • 2025
  • OriginalPaper
  • Chapter
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Abstract

This study delves into the transformative impact of AI tools on the job performance of IT professionals in Bengaluru, extending the Technology Acceptance Model (TAM) framework to include variables such as perceived usefulness, ease of use, user knowledge, and self-efficacy. The research reveals that perceived usefulness significantly influences attitudes and intentions towards AI tool adoption, emphasizing the need for organizations to focus on training programs that highlight the practical benefits of AI. Perceived ease of use, while not directly impacting behavioral intentions, plays a crucial role in shaping positive attitudes. The study also challenges the assumption that higher user knowledge leads to more favorable attitudes towards AI, underscoring the importance of continuous education and training. Notably, perceived self-efficacy emerges as a strong predictor of both behavioral intentions and actual usage, highlighting the need for targeted training and supportive environments. The research concludes that organizations should foster a culture of innovation and professional development, encouraging the use of AI tools to supplement human abilities and drive job performance. By addressing the complex interplay of factors influencing AI adoption, this study provides valuable insights for organizations aiming to optimize performance and stay competitive in the rapidly evolving IT sector.
This chapter is part of Ph.D. work conducted by Author 1 at Presidency University, Bengaluru.
This chapter has been presented as a paper in English language at 3rd ISCM & SEC, 2024, a conference conducted during 26th & 28th May, 2024 by the School of Law, KIIT, Bhubaneswar, India.

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Title
AI Tools Adoption and Utilization Impact: Extending TAM Framework and Exploring Relevance to Job Performance Among Bengaluru IT Professionals
Authors
Samuel Mores Geddam
A. Ameer Hussian
N. Nethravathi
Copyright Year
2025
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-96-7434-3_11
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