Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India

Artificial Intelligence (AI) is increasingly transforming the manufacturing sector in India by enhancing managerial decision-making processes. With the rise of Industry 4.0, Indian manufacturing firms are adopting AI technologies to analyze real-time data, predict outcomes, and optimize operations. This study adopts an exploratory research design based on secondary data to examine the role of AI in strategic, tactical, and operational decision-making. It highlights applications such as predictive maintenance, demand forecasting, quality control, and supply chain optimization. The findings indicate that AI improves decision accuracy, efficiency, and productivity while reducing operational costs. However, challenges such as high implementation costs, skill shortages, and data security concerns continue to hinder widespread adoption. This study specifically focuses on the Indian manufacturing context, which is still under-researched in existing literature. The study concludes that integrating AI with human expertise is essential for sustainable and effective decision-making in Indian manufacturing organizations.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-24
DOI
https://doi.org/10.5281/zenodo.18758070
Primary Topic
Digital Transformation in Industry
Type
article
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article

Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India

Dr. Amita Koli
Zenodo (CERN European Organization for Nuclear Research)
Digital Transformation in Industry
article

Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India

Dr. Amita Koli
article en

Abstract

Artificial Intelligence (AI) is increasingly transforming the manufacturing sector in India by enhancing managerial decision-making processes. With the rise of Industry 4.0, Indian manufacturing firms are adopting AI technologies to analyze real-time data, predict outcomes, and optimize operations. This study adopts an exploratory research design based on secondary data to examine the role of AI in strategic, tactical, and operational decision-making. It highlights applications such as predictive maintenance, demand forecasting, quality control, and supply chain optimization. The findings indicate that AI improves decision accuracy, efficiency, and productivity while reducing operational costs. However, challenges such as high implementation costs, skill shortages, and data security concerns continue to hinder widespread adoption. This study specifically focuses on the Indian manufacturing context, which is still under-researched in existing literature. The study concludes that integrating AI with human expertise is essential for sustainable and effective decision-making in Indian manufacturing organizations.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 48%
Digital Transformation in Industry
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