Bibliographic Details
| Title: |
ARTIFICIAL INTELLIGENCE APPLICATION IN ENTERPRISE BASED ON BUSINESS MODEL CANVAS. |
| Authors: |
KRAWCZYK, Tomasz1 tj.krawczyk@uw.edu.pl, NOWAKOWSKI, Wojciech1 w.nowakowski@delab.uw.edu.pl |
| Source: |
Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie. 2026, Issue 251, p277-323. 47p. |
| Subject Terms: |
*Value proposition, *Customer relations, *Value creation, *Digital transformation, *Econometrics, *Artificial intelligence |
| Abstract: |
Purpose: This article aims to identify the business model canvas (BMC) areas in which enterprises most frequently implement artificial intelligence (AI) tools and to determine the structural and operational factors that determine their use. Design/methodology/approach: This survey uses a mixed-methods study that combines a systematic literature review with a two-stage quantitative analysis. First, Z-tests and Chi-square tests examined nine BMC areas using a proportion test (50% population share) to evaluate AI tool prevalence. Second, 18 logit models explained the impact of structural and operational variables on AI use. Findings: The proportion test results showed that in 2024, significant AI tool use was concentrated in key activities and value propositions. In 2025, customer relationships were added as another area with statistically significant AI use. Econometric research results showed that the implementation of an AI tool in one BMC area depends on its implementation in other areas. Research limitations/implications: Limitations include the survey's geographic sample size and the evolving level of organizational awareness and knowledge regarding AI tools. Practical implications: The proportion test results indicate that companies should prioritize implementing AI tools in value propositions, key activities, and customer relationships to improve efficiency and competitiveness. Econometric results indicate that the successive diffusion of AI in a single area of a business model generates network benefits, which can reduce psychological barriers and foster the effective adoption of AI tools within enterprises and increase employee competency. Social implications: The application of AI tools in specific areas of business models can accelerate digital transformation in a broader context, improve user experience, and influence organizational and management practices. Originality/value: Unlike other studies, a unique hybrid methodology was conducted based on a systematic literature review with a two-stage quantitative study consisting of simple statistical tests and a set of 18 logit models, which allowed for the identification of AI adoption locations and their mechanisms of diffusion in the business models. [ABSTRACT FROM AUTHOR] |
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Copyright of Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie is the property of Silesian Technical University, Organisation & Management Faculty and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Business Source Index |