The impact of artificial intelligence on business performance: a proposed conceptual framework
The impact of artificial intelligence on business performance: a proposed conceptual framework
Artificial Intelligence (AI) enable organizations to enhance performance through the implementation of various applications in the organizational structure. But unfortunately, the hidden factors of AI become the hurdle for organizations which abandon the organizations to implement it. Therefore, this paper attempts to find the business performance by analyzing such factors which are essential while implementing the AI applications or systems. A hybrid methodology based on Interpretive Structural Modelling (ISM) and Analytical Network Process (ANP) is used to identify inter-relationships among AI factors. Results shows that deep learning, neural networks and employee motivation are the factors with highest weightage and ranking. This study presents a new look to the firms, especially in Pakistan in order to enhance the performance. Eventually, this paper offers a useful map and perspectives into additional investigation in a Pakistani context in particular for AI.
Kusi-Sarpong, Simonov
a7e68240-2b34-456e-9849-c01bd10c68f7
Khan, Sharfuddin Ahmed
4e5d9744-cff5-4e3f-9a3f-08535970d2a4
Kusi-Sarpong, Simonov
a7e68240-2b34-456e-9849-c01bd10c68f7
Khan, Sharfuddin Ahmed
4e5d9744-cff5-4e3f-9a3f-08535970d2a4
Kusi-Sarpong, Simonov and Khan, Sharfuddin Ahmed
(2022)
The impact of artificial intelligence on business performance: a proposed conceptual framework.
International Journal of Business Excellence.
(doi:10.1504/IJBEX.2022.10049018).
(In Press)
Abstract
Artificial Intelligence (AI) enable organizations to enhance performance through the implementation of various applications in the organizational structure. But unfortunately, the hidden factors of AI become the hurdle for organizations which abandon the organizations to implement it. Therefore, this paper attempts to find the business performance by analyzing such factors which are essential while implementing the AI applications or systems. A hybrid methodology based on Interpretive Structural Modelling (ISM) and Analytical Network Process (ANP) is used to identify inter-relationships among AI factors. Results shows that deep learning, neural networks and employee motivation are the factors with highest weightage and ranking. This study presents a new look to the firms, especially in Pakistan in order to enhance the performance. Eventually, this paper offers a useful map and perspectives into additional investigation in a Pakistani context in particular for AI.
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Accepted/In Press date: 15 June 2022
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Local EPrints ID: 478380
URI: http://eprints.soton.ac.uk/id/eprint/478380
ISSN: 1756-0055
PURE UUID: daa266dd-b757-49ad-95f8-d7527ef22ad5
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Date deposited: 29 Jun 2023 16:50
Last modified: 12 Jul 2024 04:07
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Author:
Sharfuddin Ahmed Khan
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