BRAIN. Broad Research in Artificial Intelligence and Neuroscience

Volume: 16 | Issue: 3 |

Adoption of AI in Digital Marketing: Comparing Gen Z and Gen Y through the Technology Acceptance Model

Published September 8, 2025
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Adriana Manolică - Alexandru Ioan Cuza University of Iasi (RO), Olga Bucătaru - Alexandru Ioan Cuza University of Iasi (RO), Cristina Teodora Roman - Alexandru Ioan Cuza University of Iasi (RO), Patricea Elena Bertea - Alexandru Ioan Cuza University of Iasi (RO), Alexandra Raluca Jelea - Alexandru Ioan Cuza University of Iasi (RO),

Abstract

The study aims to investigate the degree of acceptance of Artificial Intelligence Implications in Digital Marketing, from a consumer perspective. More specifically, the research proposed to examine the significant differences between Gen Z and Gen Y regarding the level of technology acceptance. The research follows the Technology Acceptance Model and aims to explore various aspects of consumer attitudes towards AI applications in digital marketing. The main objectives include examining the cognitive and emotional components of consumer attitudes, assessing perceived usefulness and perceived ease of use, analysing the intention to use AI applications, and evaluating the extent of actual usage. The study hypothesises that perceived usefulness positively influences the adoption of AI applications, while generational differences impact both attitude and intention to use AI technologies. The research has hypotheses which were firstly formulated and subsequently tested through quantitative research, using questionnaires to collect data from Gen Z and Gen Y respondents. The findings reveal that Gen Z demonstrates higher familiarity and willingness to engage with AI applications, while Gen Y expresses more concerns about data privacy and reliability. Additionally, the results confirm that perceived usefulness significantly influences the intention to adopt AI applications, whereas perceived ease of use does not show a notable difference between the generations.

Academic discipline and sub-disciplines: Marketing; Sociology; Artificial Intelligence

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DOI: http://dx.doi.org/10.70594/brain/16.3/9

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