Implementing challenges of artificial intelligence: evidence from public manufacturing sector of an emerging economy

Sharma, Manu, Luthra, Sunil, Joshi, Sudhanshu and Kumar, Anil (2021) Implementing challenges of artificial intelligence: evidence from public manufacturing sector of an emerging economy. Government Information Quarterly. ISSN 0740-624X (In Press)

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Abstract / Description

The growing Artificial Intelligence (AI) age has been flooded with several innovations in algorithmic machine learning that may bring significant impacts to industries such as healthcare, agriculture, education, manufacturing, retail etc. But challenges such as data quality, privacy and lack of a skilled workforce limit the scope of AI implementation in emerging economies, particularly in the Public Manufacturing Sector (PMS). Therefore, to enhance the body of relevant literature, this study examines the existing challenges of AI implementation in PMS of India and explores the inter-relationships among them. The study has utilized the DEMATEL method for identification of the cause-and-effect group factors. The findings reveal that poor data quality, managers’ lack of understanding of cognitive technologies, data privacy, problems in integrating cognitive projects and expensive technologies are the main challenges for AI implementation in PMS of India. Moreover, a model is proposed for industrial decision-makers and managers to take appropriate decisions to develop intelligent AI enabled systems for manufacturing organizations in emerging economies.

Item Type:	Article
Uncontrolled Keywords:	artificial intelligence; implementing challenges; public manufacturing sector; AI enabled systems; emerging economies
Subjects:	000 Computer science, information & general works 600 Technology > 650 Management & auxiliary services
Department:	Guildhall School of Business and Law
Depositing User:	Anil Kumar
Date Deposited:	13 Sep 2021 08:52
Last Modified:	08 Dec 2021 10:58
URI:	https://repository.londonmet.ac.uk/id/eprint/6974

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