Authors :
Dr. V. Lakshmi; Dr. R. Raghuveer
Volume/Issue :
Volume 10 - 2025, Issue 12 - December
Google Scholar :
https://tinyurl.com/ys8h42ep
Scribd :
https://tinyurl.com/43j4nvfk
DOI :
https://doi.org/10.38124/ijisrt/25dec763
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
The growing reliance on data-driven decision-making has transformed both human resource management and
marketing functions within organizations. While HR analytics focuses on extracting insights from workforce data to enhance
talent management and employee performance, marketing analytics emphasizes understanding customer behaviour and
market dynamics. Artificial Intelligence (AI) has emerged as a critical enabler that integrates these traditionally siloed
domains by linking human capital insights with market-oriented outcomes. This conceptual study, based on secondary data,
synthesizes extant literature to examine how AI-driven HR analytics and marketing analytics interact to generate strategic
value. The paper proposes an integrative framework illustrating how talent insights translate into market impact through
AI-enabled mechanisms. Further, it discusses managerial implications, ethical challenges, and future research directions.
The study contributes to interdisciplinary analytics literature by offering a structured perspective on AI-enabled
convergence of HR and marketing functions.
Keywords :
HR Analytics; Marketing Analytics; Artificial Intelligence; Talent Insights; Market Impact; Data- Driven Decision- Making.
References :
- Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1–11.
- Bassi, L., Carpenter, R., & McMurrer, D. (2012). HR analytics handbook. McBassi & Company. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd. Norton.
- Chui, M., Manyika, J., & Miremadi, M. (2018). What AI can and can’t do. McKinsey Quarterly. Davenport, T. H. (2018). The AI advantage. MIT Press.
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- Rust, R. T., & Huang, M. H. (2014). The service revolution. Marketing Science, 33(2), 206–221.
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- Wamba, S. F., et al. (2017). Big data analytics and firm performance. Journal of Business Research, 70, 356– 365.
The growing reliance on data-driven decision-making has transformed both human resource management and
marketing functions within organizations. While HR analytics focuses on extracting insights from workforce data to enhance
talent management and employee performance, marketing analytics emphasizes understanding customer behaviour and
market dynamics. Artificial Intelligence (AI) has emerged as a critical enabler that integrates these traditionally siloed
domains by linking human capital insights with market-oriented outcomes. This conceptual study, based on secondary data,
synthesizes extant literature to examine how AI-driven HR analytics and marketing analytics interact to generate strategic
value. The paper proposes an integrative framework illustrating how talent insights translate into market impact through
AI-enabled mechanisms. Further, it discusses managerial implications, ethical challenges, and future research directions.
The study contributes to interdisciplinary analytics literature by offering a structured perspective on AI-enabled
convergence of HR and marketing functions.
Keywords :
HR Analytics; Marketing Analytics; Artificial Intelligence; Talent Insights; Market Impact; Data- Driven Decision- Making.