IJARSAI International Journal of Advanced Research Scientific Analysis & Inferences
Volume 2, Issue 1, January-June, 2026
The Role of Artificial Intelligence in Strengthening Employer Branding in Hospitality Industry
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IJARSAI Int. J. Adv. Res. Sci. Anal. Infer.
Author(s):
Article Dates: Received: 27 March 2026 | Revised Submission: 29 April 2026 | Accepted: 24 May 2026 | Available Online: 13 June 2026
Abstract
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Aparna Devi U
Research Scholar
Loyola College of Social Sciences
Thiruvananthapuram
Affiliated to the University of Kerala, India
Email: aparna6online@gmail.com
Prof. (Dr). Reshmi R Prasad
Principal, All Saints’ College Thiruvananthapuram
Affiliated to the University of Kerala, India
Email: reshmi071@gmail.com
Article Dates: Received: 27 March 2026 | Revised Submission: 29 April 2026 | Accepted: 24 May 2026 | Available Online: 13 June 2026
Abstract
The hospitality industry depends a lot on skilled employees to deliver high quality service and stay competitive in the market. With the growth of digital technologies, Artificial Intelligence (AI) is slowly becoming an important part of human resource management, especially in employer branding. Tools like recruitment chatbots, predictive analytics, and even social media analysis are now being used by companies to find suitable candidates and improve their overall hiring process. These technologies also help organizations present themselves as attractive places to work by highlighting their strengths. In the hospitality sector, this is especially important because reputation plays a big role. This paper looks at how AI supports employer branding efforts and explains how AI-based HR practices can improve an organization’s image, which in turn helps in attracting and retaining talent and maintaining competitiveness.
Keywords: Artificial Intelligence, Employer Branding, Hospitality Industry, HR AnalyticsHow to Cite:
U., Aparna Devi, & Prasad, R. R. (2026). The role of artificial intelligence in strengthening employer branding in hospitality industry. IJARSAI International Journal of Advanced Research Scientific Analysis & Inferences, 2(1), 125–133. https://doi.org/10.5281/zenodo.20679372
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