IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v13y2026i4p1471-1476.html

The Impact of Al Adoption and Transparency on Recruitment Efficiency: The Mediating Role of Satisfaction in the IT Sector

Author

Listed:
  • Dixitha A.

    (Research Scholar, Department of Management Studies, Marudhar Kesari Jain College For Women, Vaniyambadi, Tirupattur District, Tamil Nadu.)

  • Dr. G. Deepalakshmi

    (Research Supervisor & Head, Department of Management Studies, Marudhar Kesari Jain College For Women, Vaniyambadi, Tirupattur District, Tamil Nadu.)

Abstract

Artificial Intelligence (Al) is transforming human resource management, particularly within the information technology (IT) sector. This study investigates the factors influencing recruitment efficiency by analyzing the effects of Al adoption and perceived transparency on recruitment outcomes. Using structural equation modeling, we examined data from IT professionals to determine how Al integration and organizational transparency influence satisfaction and, subsequently, recruitment efficiency. Our findings indicate that both Al adoption and transparency have significant positive impacts on satisfaction and recruitment efficiency, with satisfaction acting as a critical bridge. These results provide strategic implications for HR leaders aiming to optimize recruitment processes through technology.

Suggested Citation

  • Dixitha A. & Dr. G. Deepalakshmi, 2026. "The Impact of Al Adoption and Transparency on Recruitment Efficiency: The Mediating Role of Satisfaction in the IT Sector," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 13(4), pages 1471-1476, April.
    • Handle: RePEc:bjc:journl:v:13:y:2026:i:4:p:1471-1476
    as

    Download full text from publisher

    File URL: https://rsisinternational.org/journals/ijrsi/uploads/vol13-iss4-pg1471-1476-202605_pdf.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrsi/view/the-impact-of-al-adoption-and-transparency-on-recruitment-efficiency-the-mediating-role-of-satisfaction-in-the-it-sector/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arun Rai, 2020. "Explainable AI: from black box to glass box," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 137-141, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Changdong, 2024. "How consumers respond to service failures caused by algorithmic mistakes: The role of algorithmic interpretability," Journal of Business Research, Elsevier, vol. 176(C).
    2. Robertson, Jeandri & Ferreira, Caitlin & Botha, Elsamari & Oosthuizen, Kim, 2024. "Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction," Business Horizons, Elsevier, vol. 67(5), pages 499-510.
    3. Rita Gonçalves, Ana & Costa Pinto, Diego & Gonzalez-Jimenez, Héctor & Dalmoro, Marlon & Mattila, Anna S., 2025. "Me, Myself, and My AI: How artificial intelligence classification failures threaten consumers’ self-expression," Journal of Business Research, Elsevier, vol. 186(C).
    4. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    5. Jan Ole Krugmann & Jochen Hartmann, 2024. "Sentiment Analysis in the Age of Generative AI," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 11(1), pages 1-19, December.
    6. Nan Zhang & Heng Xu, 2024. "Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning," Information Systems Research, INFORMS, vol. 35(2), pages 469-488, June.
    7. Han Li & Feng Tian, 2026. "Advancing Decision-Making through AI-Human Collaboration: A Systematic Review and Conceptual Framework," Group Decision and Negotiation, Springer, vol. 35(2), pages 1-24, June.
    8. Muhammad Sukri Bin Ramli, 2025. "Intelligent Automation for FDI Facilitation: Optimizing Tariff Exemption Processes with OCR And Large Language Models," Papers 2506.12093, arXiv.org.
    9. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
    10. Helena Weith & Christian Matt, 2023. "Information provision measures for voice agent product recommendations— The effect of process explanations and process visualizations on fairness perceptions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-20, December.
    11. Cristina Trocin & Patrick Mikalef & Zacharoula Papamitsiou & Kieran Conboy, 2023. "Responsible AI for Digital Health: a Synthesis and a Research Agenda," Information Systems Frontiers, Springer, vol. 25(6), pages 2139-2157, December.
    12. Alantari, Huwail J. & Currim, Imran S. & Deng, Yiting & Singh, Sameer, 2022. "An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 1-19.
    13. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl & Joshua Gawlitza, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Information Systems Research, INFORMS, vol. 32(3), pages 713-735, September.
    14. Mueller, Alexander & Kuester, Sabine & von Janda, Sergej, 2025. "Socially (un)acceptable errors of AI: Consumer perceptions of different AI-induced errors," Journal of Business Research, Elsevier, vol. 201(C).
    15. Jinjuan Yang & Jiayuan Xin & Yan Zeng & Pei Jose Liu, 2025. "Signaling and perceiving on equity crowdfunding decisions — a machine learning approach," Small Business Economics, Springer, vol. 65(1), pages 315-356, June.
    16. Henner Gimpel & Vanessa Graf-Seyfried & Robert Laubacher & Oliver Meindl, 2023. "Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing," Group Decision and Negotiation, Springer, vol. 32(1), pages 75-124, February.
    17. Jacob Dexe & Ulrik Franke & Kasia Söderlund & Niels Berkel & Rikke Hagensby Jensen & Nea Lepinkäinen & Juho Vaiste, 2022. "Explaining automated decision-making: a multinational study of the GDPR right to meaningful information," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 669-697, July.
    18. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
    19. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    20. Spiekermann, Sarah & Krasnova, Hanna & Hinz, Oliver & Baumann, Annika & Benlian, Alexander & Gimpel, Henner & Heimbach, Irina & Köster, Antonia & Maedche, Alexander & Niehaves, Björn & Risius, Marten , 2022. "Values and Ethics in Information Systems – A State-of-the-Art Analysis and Avenues for Future Research," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130842, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjc:journl:v:13:y:2026:i:4:p:1471-1476. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrsi/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.