OPTIMIZING TALENT ACQUISITION EFFECIENCY IN INDIAN IT: AN AI ENABLED FRAMEWORK FOR SUSTAINABLE OPERATIONS
DOI:
https://doi.org/10.65009/av0q5v41Keywords:
Artificial Intelligence, Talent Acquisition, Best Practices, Organizational Productivity.,,Abstract
How AI is influencing the recruitment process is the subject of this research.
The writers spoke with HR professionals, recruiters, and AI platform vendors. Their
findings suggest that AI is altering the organizational makeup and recruitment practices
of businesses. The research was able to fully grasp AI's role in talent acquisition by
concentrating on these aspects. The authors also provide a theoretical framework to help
readers better comprehend the effects of AI on the hiring process. Their research shows
that fair implementation of AI is necessary to avoid prejudice in hiring, even though AI
has the potential to increase output. The findings from the research will make the positive
and negative aspects of AI in the workplace more-clear. Also included in this document
is advice for businesses on how to make the most of AI.
References
Altemeyer, B. (2019), “Making the business case for AI in HR: two case studies”,
Strategic HR Review, Vol. 18 No. 2, pp. 66-70.
Anita, R. (2019), “Effective strategic talent acquisition process – a conceptual study”,
Gavesana Journal of Management, Vol. 11 No. 1, pp. 42-51.
Balachandar, A. and Kulkarni, D.A. (2018), “A neural conversational model”,
International Research Journal of Engineering and Technology (IRJET), Vol. 5 No. 1248.
Beer, D. (2017), “The social power of algorithms”, Information, Communication and
Society, Vol. 20 No. 1, pp. 1-13.
Bititci, U.S., Ackermann, F., Ates, A., Davies, J.D., Gibb, S., MacBryde, J., MacKay, D.,
et al. (2011), “Managerial processes: an operations management perspective towards
dynamic capabilities”, Production Planning and Control, Vol. 22 No. 2.
Bondarouk, T. and Brewster, C. (2016), “Conceptualising the future of HRM and
technology research”, The International Journal of Human Resource Management, Vol.
No. 21, pp. 2652-2671.
Bondarouk, T., Parry, E. and Furtmueller, E. (2017), “Electronic HRM: four decades of
research on adoption and consequences”, The International Journal of Human Resource
Management, Vol. 28 No. 1.
Hepp, A. (2020), “Artificial companions, social bots and work bots: communicative
robots as research objects of media and communication studies”, Media, Culture and
Society, Vol. 42 Nos 7/8, pp. 1410-1426.
Hiebl, M.R.W. and Pielsticker, D.I. (2023), “Automation, organisational ambidexterity
and the stability of employee relations: new tensions arising between corporate
entrepreneurship, innovation management and stakeholder management”, The Journal of
Technology Transfer, Vol. 48 No. 6, pp. 1978-2006.
Hmoud, B. and Laszlo, V. (2019), “Will artificial intelligence take over human resources
recruitment and selection?”, Network Intelligence Studies, Vol. 7 No. 13.
Cheng, M.M. and Hackett, R.D. (2021), “A critical review of algorithms in HRM:
definition, theory, and practice”, Human Resource Management Review, Vol. 31 No. 1,
p. 100698.
Clauss, T., Kraus, S., Kallinger, F.L., Bican, P.M., Brem, A. and Kailer, N. (2021),
“Organisational ambidexterity and competitive advantage: the role of strategic agility in
the exploration- exploitation paradox”, Journal of Innovation and Knowledge, Vol. 6 No.
, pp. 203-213.
Corbin, J. and Strauss, A. (2014), Basics of Qualitative Research: Techniques and
Procedures for Developing Grounded Theory, Sage publications, London.
Del Giudice, M., Scuotto, V., Ballestra, L.V. and Pironti, M. (2022), “Humanoid robot
adoption and labour productivity: a perspective on ambidextrous product innovation
routines”, The International Journal of Human Resource Management, Vol. 33 No. 6, pp.
-1124.
Dietvorst, B.J., Simmons, J.P. and Massey, C. (2018), “Overcoming algorithm aversion:
people will use imperfect algorithms if they can (even slightly) modify them”,
Management Science, Vol. 64 No. 3.
Duggan, J., Sherman, U., Carbery, R. and McDonnell, A. (2020), “Algorithmic
management and app- work in the gig economy: a research agenda for employment
relations and HRM”, Human Resource Management Journal, Vol. 30 No. 1, pp. 114-132.
Farnadi, G., Babaki, B. and Getoor, L. (2018), “Fairness in relational domains”, AIES
– Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society.
Gioia, D.A., Corley, K.G. and Hamilton, A.L. (2013), “Seeking qualitative rigor in
inductive research: notes on the Gioia methodology”, Organizational Research Methods,
Vol. 16 No. 1.
Gupta, P., Fernandes, S.F. and Jain, M. (2018), “Automation in recruitment: a new
frontier”, Journal of Information Technology Teaching Cases, Vol. 8 No. 2.
Guzman, A.L. and Lewis, S.C. (2020), “Artificial intelligence and communication: a
human – machine communication research agenda”, New Media and Society, Vol. 22 No.
