The Use of Artificial Intelligence in Marketing in the Software as a Service (SaaS) Sector

The thesis examines the impact of artificial intelligence (AI) on the marketing performance of companies operating in the Business-to-Business Software-as-a-Service (B2B SaaS) segment. Based on a systematic literature review, five hypotheses were formulated regarding whether AI improves (1) targeting and segmentation, (2) process automation, (3) market responsiveness, (4) customer behavior analysis, and (5) predictive capabilities. Quantitative research was conducted through an electronic survey. A total of 170 marketers provided valid responses, including 92 from companies that already actively use AI in marketing. Non-parametric statistics (Mann-Whitney U and Wilcoxon tests) were applied to evaluate the data. The analysis revealed that in four out of five observed areas, there was no statistically significant difference between companies using AI and those not using it, with the exception of advanced data analysis, where AI users reported higher satisfaction. Conversely, in the area of automation, companies that had not yet adopted AI achieved better ratings, suggesting a possible decline in efficiency during the early phase of AI implementation. Additional barriers identified through the survey include insufficient data quality and consolidation, low explainability of models, and limited employee skills. The findings suggest that the mere adoption of AI does not guarantee higher marketing success. Benefits arise only when the technology is supported by a high-quality data infrastructure, an appropriate organizational structure, systematic employee education, and transparent, ethically grounded handling of user data.