Transparent Peer Review By Scholar9
IMPACT OF ARTIFICIAL INTELLIGENCE ON HRM PRACTICES IN INDIA
Abstract
The arrival of Artificial Intelligence (AI) has revolutionized colorful sectors, and Human Resource Management (HRM) is no exception. In India, where companies are fleetly embracing digital metamorphosis, AI is playing a pivotal part in reshaping HR practices. This paper explores how AI- driven tools are transubstantiating traditional HR functions similar as reclamation, hand engagement, and performance operation. AI is helping associations streamline gift accession through automated capsule webbing, prophetic analytics, and converse bots, making reclamation briskly and more effective also, AI is enhancing hand engagement by furnishing substantiated literacy gests and performance feedback through data- driven perceptivity. In performance operation, AI- powered platforms enable nonstop performance shadowing and skill development still, the relinquishment of AI in HRM also presents challenges, similar as ethical enterprises, data sequestration, and the eventuality for job relegation. This exploration paper examines the current trends, benefits, and obstacles faced by Indian associations in integrating AI into HRM practices. By fastening on the Indian environment, the paper aims to give perceptivity into how companies are using AI to produce more effective, data- driven, and hand- centric HR processes.
Chandrasekhara (Samba) Mokkapati Reviewer
24 Sep 2024 05:41 PM
Approved
Relevance and Originality
This paper addresses a vital and contemporary issue in Human Resource Management (HRM) by exploring the transformative impact of Artificial Intelligence (AI) in India. The focus on how AI tools reshape traditional HR functions, such as recruitment and employee engagement, provides original insights that are particularly relevant in the context of digital transformation in Indian companies.
Methodology
The methodology should clearly outline the research design used to examine AI's impact on HRM practices. This includes specifying the data sources—such as surveys, case studies, or interviews—and the criteria for selecting participants. Additionally, detailing the analytical techniques employed to interpret the data will enhance the credibility and rigor of the findings.
Validity & Reliability
To strengthen the validity of the study, it is essential to discuss how the results were cross-validated, possibly through triangulation with existing literature or expert opinions. Information regarding the reliability of data collection methods, including any tools or surveys used, will further support the study's credibility. Addressing potential biases or limitations in the data will also be important for contextualizing the findings.
Clarity and Structure
The paper should be well-organized into clear sections, such as introduction, methodology, results, and discussion, allowing for easy navigation. Each section should logically flow into the next, ensuring that readers can follow the arguments presented. Using accessible language while avoiding excessive jargon will enhance understanding for a broader audience.
Result Analysis
The result analysis should delve into the specific impacts of AI on HR functions, providing quantitative metrics where possible, such as improvements in recruitment efficiency or employee engagement scores. Comparative analysis with traditional HR practices will illustrate the advantages gained through AI. Additionally, discussing the ethical implications and challenges, such as data privacy and potential job displacement, will provide a balanced view and guide future research directions in the field.
IJ Publication Publisher
Ok Sir
Chandrasekhara (Samba) Mokkapati Reviewer