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Exploring the Readiness of Organisations to Adopt Artificial Intelligence

Author(s):
ORCID

Medium: journal article
Language(s): English
Published in: Buildings, , n. 8, v. 14
Page(s): 2460
DOI: 10.3390/buildings14082460
Abstract:

Front-end planning (FEP) is the first step in identifying a problem and analysing a project’s goals and the business case for management to decide whether to proceed with the project. Despite its crucial significance, projects are still underperforming and failing to achieve their objectives. Current research suggests that the emergence of AI promises significant advantages to organisations, particularly for FEP. The purpose of this paper was to explore the readiness of organisations to use AI in the FEP phase to enhance project outcomes. The technology–organisation–environment (TOE) framework was used to evaluate factors influencing the readiness to adopt AI in construction projects in Saudi Arabia. Thirty interviews were conducted with public and private stakeholders in the sector. The knowledge and insight gained from the viewpoints of key decision makers and practitioners allowed for an examination of the main factors impacting the adoption of AI, and any challenges and barriers to it. Findings showed that the support of the government and senior management, and the attitudes and behaviour of employees, were the top three factors in the framework that facilitate the readiness of organisations to adopt AI. Government support influences external support and enhances competitive pressure between organisations; senior management support influences the absorptive capacity and maturity of an organisation; and employees’ attitudes and behaviours are the main contributors to organisational readiness. The proposed framework will assist policymakers in using these factors to overcome the challenges of AI adoption. Additionally, creating strategies aligned with Vision 2030 focuses not only on choosing the best technology to implement but also on how employees can benefit from it.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10795193
  • Published on:
    01/09/2024
  • Last updated on:
    01/09/2024
 
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