AI's growing acceptance is changing project management's human-centric approach. Project management is using AI to automate and support duties. This change could improve workflows, decision-making, and project efficiency. The full influence of AI on project success is unknown. There is little empirical evidence linking AI use to project outcomes. This ignorance highlights the necessity to study AI's impact on project management. The project management AI industry is expected to expand 38% annually. Since the late 1980s, AI has improved project management by providing more intelligent and autonomous help. Data privacy, accountability, strategic leadership, communication, innovation, and emotional intelligence are important ethical issues. This study examines how AI adoption affects project success through communication and feedback. This mixed-method study examines how AI adoption affects project success. The quantitative phase measured AI communication, feedback, and project progress via a predefined questionnaire. The sample includes construction, IT, manufacturing, healthcare, and finance project managers and team members. Multiple regression analysis and structural equation modelling were employed in IBM SPSS AMOS to examine AI adoption and project success measures. A qualitative phase of semi-structured interviews with respondents contextualised the quantitative data. Thematic analysis gleaned insights from interview transcripts. AI's impact on project success was examined using integrated data, with ethics in mind. The study examined AI tool-project success relationships using a structural equation model. Communication mode, feedback style, and frequency explained 3% of project success variance. Quantitative research showed that AI communication frequency improves project success, whereas mode and style negatively impact it. Participants' qualitative comments indicated six themes that match quantitative findings, and their replies enhance quantitative results and recommend improvements. The study concluded that AI communication frequency positively increases project success, while mode and style negatively affect it. The mixed-methods approach showed that AI tools alone cannot ensure project success; communication style and frequency are. The study recommended among others that organisations should integrate AI tools into project management systems, match AI communication modes to project team preferences, optimise feedback styles, and provide regular updates to improve AI communication. Project teams need ongoing training.
| Published in | American Journal of Management Science and Engineering (Volume 9, Issue 4) |
| DOI | 10.11648/j.ajmse.20240904.12 |
| Page(s) | 84-96 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Artificial Intelligence, Communication, Frequency, Mixed Method, Style, Project Success
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APA Style
Lawal, Y. A., Abdul-Azeez, I. F., Olateju, O. I. (2024). Artificial Intelligence Adoption and Project Success: A Mixed-Method Study. American Journal of Management Science and Engineering, 9(4), 84-96. https://doi.org/10.11648/j.ajmse.20240904.12
ACS Style
Lawal, Y. A.; Abdul-Azeez, I. F.; Olateju, O. I. Artificial Intelligence Adoption and Project Success: A Mixed-Method Study. Am. J. Manag. Sci. Eng. 2024, 9(4), 84-96. doi: 10.11648/j.ajmse.20240904.12
AMA Style
Lawal YA, Abdul-Azeez IF, Olateju OI. Artificial Intelligence Adoption and Project Success: A Mixed-Method Study. Am J Manag Sci Eng. 2024;9(4):84-96. doi: 10.11648/j.ajmse.20240904.12
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author = {Yusuf Adedayo Lawal and Ibraheem Forson Abdul-Azeez and Olawale Ibrahim Olateju},
title = {Artificial Intelligence Adoption and Project Success: A Mixed-Method Study
},
journal = {American Journal of Management Science and Engineering},
volume = {9},
number = {4},
pages = {84-96},
doi = {10.11648/j.ajmse.20240904.12},
url = {https://doi.org/10.11648/j.ajmse.20240904.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20240904.12},
abstract = {AI's growing acceptance is changing project management's human-centric approach. Project management is using AI to automate and support duties. This change could improve workflows, decision-making, and project efficiency. The full influence of AI on project success is unknown. There is little empirical evidence linking AI use to project outcomes. This ignorance highlights the necessity to study AI's impact on project management. The project management AI industry is expected to expand 38% annually. Since the late 1980s, AI has improved project management by providing more intelligent and autonomous help. Data privacy, accountability, strategic leadership, communication, innovation, and emotional intelligence are important ethical issues. This study examines how AI adoption affects project success through communication and feedback. This mixed-method study examines how AI adoption affects project success. The quantitative phase measured AI communication, feedback, and project progress via a predefined questionnaire. The sample includes construction, IT, manufacturing, healthcare, and finance project managers and team members. Multiple regression analysis and structural equation modelling were employed in IBM SPSS AMOS to examine AI adoption and project success measures. A qualitative phase of semi-structured interviews with respondents contextualised the quantitative data. Thematic analysis gleaned insights from interview transcripts. AI's impact on project success was examined using integrated data, with ethics in mind. The study examined AI tool-project success relationships using a structural equation model. Communication mode, feedback style, and frequency explained 3% of project success variance. Quantitative research showed that AI communication frequency improves project success, whereas mode and style negatively impact it. Participants' qualitative comments indicated six themes that match quantitative findings, and their replies enhance quantitative results and recommend improvements. The study concluded that AI communication frequency positively increases project success, while mode and style negatively affect it. The mixed-methods approach showed that AI tools alone cannot ensure project success; communication style and frequency are. The study recommended among others that organisations should integrate AI tools into project management systems, match AI communication modes to project team preferences, optimise feedback styles, and provide regular updates to improve AI communication. Project teams need ongoing training.
},
year = {2024}
}
TY - JOUR T1 - Artificial Intelligence Adoption and Project Success: A Mixed-Method Study AU - Yusuf Adedayo Lawal AU - Ibraheem Forson Abdul-Azeez AU - Olawale Ibrahim Olateju Y1 - 2024/09/26 PY - 2024 N1 - https://doi.org/10.11648/j.ajmse.20240904.12 DO - 10.11648/j.ajmse.20240904.12 T2 - American Journal of Management Science and Engineering JF - American Journal of Management Science and Engineering JO - American Journal of Management Science and Engineering SP - 84 EP - 96 PB - Science Publishing Group SN - 2575-1379 UR - https://doi.org/10.11648/j.ajmse.20240904.12 AB - AI's growing acceptance is changing project management's human-centric approach. Project management is using AI to automate and support duties. This change could improve workflows, decision-making, and project efficiency. The full influence of AI on project success is unknown. There is little empirical evidence linking AI use to project outcomes. This ignorance highlights the necessity to study AI's impact on project management. The project management AI industry is expected to expand 38% annually. Since the late 1980s, AI has improved project management by providing more intelligent and autonomous help. Data privacy, accountability, strategic leadership, communication, innovation, and emotional intelligence are important ethical issues. This study examines how AI adoption affects project success through communication and feedback. This mixed-method study examines how AI adoption affects project success. The quantitative phase measured AI communication, feedback, and project progress via a predefined questionnaire. The sample includes construction, IT, manufacturing, healthcare, and finance project managers and team members. Multiple regression analysis and structural equation modelling were employed in IBM SPSS AMOS to examine AI adoption and project success measures. A qualitative phase of semi-structured interviews with respondents contextualised the quantitative data. Thematic analysis gleaned insights from interview transcripts. AI's impact on project success was examined using integrated data, with ethics in mind. The study examined AI tool-project success relationships using a structural equation model. Communication mode, feedback style, and frequency explained 3% of project success variance. Quantitative research showed that AI communication frequency improves project success, whereas mode and style negatively impact it. Participants' qualitative comments indicated six themes that match quantitative findings, and their replies enhance quantitative results and recommend improvements. The study concluded that AI communication frequency positively increases project success, while mode and style negatively affect it. The mixed-methods approach showed that AI tools alone cannot ensure project success; communication style and frequency are. The study recommended among others that organisations should integrate AI tools into project management systems, match AI communication modes to project team preferences, optimise feedback styles, and provide regular updates to improve AI communication. Project teams need ongoing training. VL - 9 IS - 4 ER -
Department of Management Technology, Lagos State University, Lagos, Nigeria
School of Transport and Logistics, Lagos State University, Lagos, Nigeria
Department of Management Technology, Lagos State University, Lagos, Nigeria
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