Paper 1: AI-Driven Predictive Analytics with the Help of IoT for Organizational Change Management
Authors : Esha Srivastava, Shraddha Yadav and Mahesh Kumar Tiwari
Doi: https://doi.org/10.63920/tjths.43001
Abstract
Artificial Intelligence (AI) and Internet of Things (IoT) are increasingly finding their way to the current workplaces thereby transforming Organization Change Management (OCM). The present paper discusses the opportunities of transforming the way organizations should handle change through the integration between AI-driven predictive capabilities and data measured in real-time through the IoT devices. The conventional change models are usually built on basis of stagnant planning and instinctive decisions with the AI and IoT empowering dynamic decisions and in light of data. IoT Sensors are able to record real-time behavioral, physiological, and environmental data that is processed by an AI system to analyze the data to find potential signs of resistance, disengagement, or stress. These insights can be used to intervene in a timely and personalized manner that helps in facilitating the transitional process and aiding in employee wellbeing. Based on the case studies and analyses, this paper demonstrates the opportunities and the ethical implications of such technologies in change management practice. It also ends with propositions on how to create more versatile, individualized, and morality-based change plans in future.
