Paper Title

AI Enabled Effective Employee Engagement framework leading to productivity & Retention

Article Identifiers

Registration ID: IJNRD_217460

Published ID: IJNRD2404221

DOI: Click Here to Get

Authors

I V S Ranganath , Dr. N V J Rao , Dr. A Niharika,

Keywords

1. AI-enabled employee engagement 2. Productivity enhancement 3. Retention strategies 4. Manufacturing industries 5. Telangana State 6. Artificial intelligence adoption 7. Workplace dynamics 8. Predictive analytics 9. Personalized engagement initiatives 10. Organizational effectiveness

Abstract

In today's dynamic workplace landscape, organizations are continuously seeking innovative strategies to enhance employee engagement, improve productivity, and retain top talent. Traditional approaches to employee engagement often fall short in addressing the evolving needs and preferences of modern workforce demographics. However, recent advancements in artificial intelligence (AI) present unprecedented opportunities to revolutionize employee engagement practices. This paper proposes an AI-enabled employee engagement framework designed to optimize productivity and increase retention rates within organizations. Leveraging AI technologies such as natural language processing, machine learning, and sentiment analysis, the framework aims to personalize engagement strategies, identify key drivers of employee satisfaction, and predict potential turnover risks. By harnessing real-time data and insights, organizations can tailor interventions and initiatives to meet the unique needs of their workforce, thereby fostering a culture of continuous improvement and growth. The effectiveness of the proposed framework is demonstrated through case studies and empirical research conducted across various industries. Results indicate significant improvements in employee satisfaction, productivity, and retention rates following the implementation of AI-driven engagement initiatives. Moreover, the framework offers scalability and adaptability, enabling organizations to navigate complex challenges and uncertainties in today's competitive business environment. Overall, this paper contributes to the growing body of literature on AI in human resource management by presenting a comprehensive framework for enhancing employee engagement and driving organizational success. By embracing AI technologies, organizations can cultivate a culture of engagement, empower their workforce, and achieve sustainable growth in the digital age.

How To Cite

"AI Enabled Effective Employee Engagement framework leading to productivity & Retention", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b946-b955, April-2024, Available :https://ijnrd.org/papers/IJNRD2404221.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : b946-b955

Other Publication Details

Paper Reg. ID: IJNRD_217460

Published Paper Id: IJNRD2404221

Downloads: 000121148

Research Area: Management

Country: Hyderabad, Telangana, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404221.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404221

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

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