Proceedings of the Kautz Conference on Business and Economics 2025 (KCBE 2025)

generAtIon – Exploring Generational Differences in Perception and Use of Artificial Intelligence

Authors
Gabor Keresztes1, *, Nikoletta Nemeth2, Katalin Meszaros3
1University of Sopron, Sopron, Hungary
2University of Sopron, Sopron, Hungary
3University of Sopron, Sopron, Hungary
*Corresponding author. Email: keresztes.gabor@uni-sopron.hu
Corresponding Author
Gabor Keresztes
Available Online 1 May 2026.
DOI
10.2991/978-94-6239-658-6_12How to use a DOI?
Keywords
AI; generation; social innovation
Abstract

The rapid advancement of artificial intelligence (AI) is reshaping everyday life, the economy, and society. Generational differences strongly influence how people relate to AI, shaped by their technological experiences, trust levels and ethical considerations. While younger generations—especially Generation Z—tend to be more open and adaptable, older groups are generally more cautious. Understanding these differences is essential for fostering social acceptance of AI.

This study examines how the Hungarian population perceives and uses AI, with particular attention to generational variations. It focuses on AI use in work and private life, frequency of use, responsibility issues, and expected impacts on the labor market and human development.

The primary research (n = 374) involved quantitative data collection through online and in-person questionnaires across all primary age groups. The sample reflects the population’s generational distribution, and the use of a standardized questionnaire ensured comparability.

Findings show that Generations Z and Y are more knowledgeable about AI’s benefits and risks and use these technologies more frequently. Younger respondents associate AI with opportunities and rapid progress, whereas older individuals adopt a more skeptical and risk-focused view. Most participants believe human oversight should remain essential and express concerns about job loss and potential risks to humanity.

Overall, although it includes demographic, educational, and occupational factors, it should include qualitative insights to emphasize opportunities, while older generations highlight risks. Future research should expand its focus to include demographic, educational, and occupational factors, and should incorporate qualitative insights to deepen understanding of generational patterns.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Kautz Conference on Business and Economics 2025 (KCBE 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
1 May 2026
ISBN
978-94-6239-658-6
ISSN
2352-5428
DOI
10.2991/978-94-6239-658-6_12How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Gabor Keresztes
AU  - Nikoletta Nemeth
AU  - Katalin Meszaros
PY  - 2026
DA  - 2026/05/01
TI  - generAtIon – Exploring Generational Differences in Perception and Use of Artificial Intelligence
BT  - Proceedings of the Kautz Conference on Business and Economics 2025 (KCBE 2025)
PB  - Atlantis Press
SP  - 219
EP  - 238
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-658-6_12
DO  - 10.2991/978-94-6239-658-6_12
ID  - Keresztes2026
ER  -