Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
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2026
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| _version_ | 1866901722114293760 |
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| author | Dr. Amita Koli |
| author_facet | Dr. Amita Koli |
| contents | <p>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.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18758071 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India Dr. Amita Koli Artificial Intelligence, Decision-Making, Manufacturing Sector, India, Industry 4.0 <p>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.</p> |
| title | Artificial Intelligence in Management Decision-Making in the Manufacturing Sector in India |
| topic | Artificial Intelligence, Decision-Making, Manufacturing Sector, India, Industry 4.0 |
| url | https://doi.org/10.5281/zenodo.18758071 |