A model to measure the technological acceptance of artificial intelligence in Controlling and Finance

Due to necessary digitization measures and the increasing relevance of artificial intelligence (AI) in companies, this article examines the acceptance and use of AI in controlling. For this purpose, existing technology acceptance models and the decisive factors that influence the acceptance of new technologies are examined in the context of secondary research. From the findings of the literature analysis a model for measuring the technological acceptance of AI in controlling is deductively developed. The model consists of exogenous and endogenous factors. The first of these are independent factors like quality of results, image, subjective norm, experience, task-technology fit, self-efficacy and voluntariness. Their influence has a direct effect on the corresponding endogenous (dependent) factors like perceived usefulness and usability of AI, intention to use and actual use.To validate the developed model an empirical study was conducted and analyzed with SmartPLS. The results show that the most crucial factors influencing the use of artificial intelligence in controlling are the quality of results, the experience gained to date with this technology and the level of acceptance. Personal factors hardly play a role. With reference to these findings, a further analysis of various AI-supported software solutions should be conducted to systematically evaluate their suitability for the controlling area.

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Published
2025-05-21
DOI
https://doi.org/10.1109/iccta65425.2025.11166211
Primary Topic
Economic and Technological Systems Analysis
Type
article
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article

A model to measure the technological acceptance of artificial intelligence in Controlling and Finance

Martin Tschandl, Ganzer Tobias, Brandstätter Claudia
Economic and Technological Systems Analysis
article

A model to measure the technological acceptance of artificial intelligence in Controlling and Finance

Martin Tschandl, Ganzer Tobias, Brandstätter Claudia
article en

Abstract

Due to necessary digitization measures and the increasing relevance of artificial intelligence (AI) in companies, this article examines the acceptance and use of AI in controlling. For this purpose, existing technology acceptance models and the decisive factors that influence the acceptance of new technologies are examined in the context of secondary research. From the findings of the literature analysis a model for measuring the technological acceptance of AI in controlling is deductively developed. The model consists of exogenous and endogenous factors. The first of these are independent factors like quality of results, image, subjective norm, experience, task-technology fit, self-efficacy and voluntariness. Their influence has a direct effect on the corresponding endogenous (dependent) factors like perceived usefulness and usability of AI, intention to use and actual use.To validate the developed model an empirical study was conducted and analyzed with SmartPLS. The results show that the most crucial factors influencing the use of artificial intelligence in controlling are the quality of results, the experience gained to date with this technology and the level of acceptance. Personal factors hardly play a role. With reference to these findings, a further analysis of various AI-supported software solutions should be conducted to systematically evaluate their suitability for the controlling area.

FH JOANNEUM University of Applied Sciences (AT)
Openalex Percentile: Top 66%
Economic and Technological Systems Analysis
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