Title: The impact of artificial intelligence on business performance: a proposed conceptual framework

Authors: Simonov Kusi-Sarpong; Sharfuddin Ahmed Khan

Addresses: Southampton Business School, University of Southampton, Southampton S017 1BJ, UK; Department of Transport and Supply Chain Management, University of Johannesburg, Johannesburg, South Africa ' Industrial Systems Engineering, Faculty of Engineering and Applied Sciences, University of Regina, Regina, SK, S4S 0A2, Canada

Abstract: Artificial intelligence (AI) enables organisations to enhance performance through the implementation of various applications in the organisational structure. But unfortunately, the hidden factors of AI become the hurdle for organisations which abandon the organisations to implement it. Therefore, this paper attempts to find the business performance by analysing 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. A result 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.

Keywords: artificial intelligence; business excellence; business performance; machine learning; deep learning; neural network; leadership; organisational change.

DOI: 10.1504/IJBEX.2026.153064

International Journal of Business Excellence, 2026 Vol.38 No.3, pp.350 - 380

Received: 22 May 2022
Accepted: 13 Jun 2022
Published online: 21 Apr 2026 *

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