Statistically Significant Differences in AI Support Levels for Project Management between SMEs and Large Enterprises

Author:

Tominc Polona1ORCID,Oreški Dijana2,Čančer Vesna1ORCID,Rožman Maja1ORCID

Affiliation:

1. Faculty of Economics and Business, University of Maribor, 2000 Maribor, Slovenia

2. Faculty of Organization and Informatics, University of Zagreb, 10000 Zagreb, Croatia

Abstract

Background: This article delves into an in-depth analysis of the statistically significant differences in AI support levels for project management between SMEs and large enterprises. The research was conducted based on a comprehensive survey encompassing a sample of 473 SMEs and large Slovenian enterprises. Methods: To validate the observed differences, statistical analysis, specifically the Mann–Whitney U test, was employed. Results: The results confirm the presence of statistically significant differences between SMEs and large enterprises across multiple dimensions of AI support in project management. Large enterprises exhibit on average a higher level of AI adoption across all five AI utilization dimensions. Specifically, large enterprises scored significantly higher (p < 0.05) in AI adopting strategies and in adopting AI technologies for project tasks and team creation. This study’s findings also underscored the significant differences (p < 0.05) between SMEs and large enterprises in their adoption and utilization of AI technologies for project management purposes. While large enterprises scored above 4 for several dimensions, with the highest average score assessed (mean value 4.46 on 1 to 5 scale) for the usage of predictive Analytics Tools to improve the work on the project, SMEs’ average levels, on the other hand, were all below 4. SMEs in particular may lag in incorporating AI into various project activities due to several factors such as resource constraints, limited access to AI expertise, or risk aversion. Conclusions: The results underscore the need for targeted strategies to enhance AI adoption in SMEs and leverage its benefits for successful project implementation and strengthen the company’s competitiveness.

Funder

Croatian Science Foundation

Slovenian Research Agency

Publisher

MDPI AG

Subject

Industrial and Manufacturing Engineering

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