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Analysing trends and patterns in employee engagement through AI

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysing trends and patterns in employee engagement through AIby Soumi Majumder, Bitan Misra.
Author:	Majumder, Soumi.
other author:	Misra, Bitan.
Published:	Singapore :Springer Nature Singapore :2025.
Description:	xv, 75 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Personnel managementData processing.
Online resource:	https://doi.org/10.1007/978-981-96-4496-4
ISBN:	9789819644964$q(electronic bk.)

Analysing trends and patterns in employee engagement through AI
Majumder, Soumi.

Analysing trends and patterns in employee engagement through AI[electronic resource] /by Soumi Majumder, Bitan Misra. - Singapore :Springer Nature Singapore :2025. - xv, 75 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology. Computational intelligence,2625-3712. - SpringerBriefs in applied sciences and technology.Computational intelligence..

Introduction -- Importance of measuring employee engagement trends in organisations -- Employee engagement challenges -- Significance of Employee Engagement Levels in the Workplace -- Employee Engagement Models -- Artificial intelligence in employee engagement and retention -- Leveraging AI for Employee Engagement -- AI-powered analytics uncover hidden patterns in employee engagement data -- Predictive analytics: Anticipating future engagement trends with AI -- Ethical Considerations and Future Directions of AI in Employee Engagement.

This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.

ISBN: 9789819644964$q(electronic bk.)

Standard No.: 10.1007/978-981-96-4496-4doiSubjects--Topical Terms:

668747
Personnel management
--Data processing.

LC Class. No.: HF5549.5.D37

Dewey Class. No.: 658.30028563

Analysing trends and patterns in employee engagement through AI
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505 0 $a Introduction -- Importance of measuring employee engagement trends in organisations -- Employee engagement challenges -- Significance of Employee Engagement Levels in the Workplace -- Employee Engagement Models -- Artificial intelligence in employee engagement and retention -- Leveraging AI for Employee Engagement -- AI-powered analytics uncover hidden patterns in employee engagement data -- Predictive analytics: Anticipating future engagement trends with AI -- Ethical Considerations and Future Directions of AI in Employee Engagement.
520 $a This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.
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650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Employee Health and Wellbeing. $3 779338
700 1 $a Misra, Bitan. $3 980735
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