INVESTIGATING THE IMPACT OF GENERATIVE ARTIFICIAL INTELLIGENCE ON DIGITAL MARKETING EFFECTIVENESS

Abstract

Generative artificial intelligence (GenAI) is transforming digital marketing by facilitating automated content creation, audience personalization, campaign development, and data-supported decision-making. However, its contribution to marketing effectiveness depends on technological adoption, professional competence, content quality, and responsible implementation. This study examines the proposed relationship between GenAI adoption and digital marketing effectiveness among marketing professionals and business owners in Lahore, Pakistan. Drawing on the Technology Acceptance Model, the study develops a framework connecting GenAI adoption, marketing productivity, content personalization, customer engagement, and perceived marketing effectiveness. A quantitative, cross-sectional survey design is proposed. To demonstrate the intended analysis and reporting format, the article presents illustrative statistical tables based on a hypothetical sample of 280 respondents. These simulated results suggest positive associations between GenAI adoption, marketing productivity, content personalization, and perceived marketing effectiveness, alongside a negative association between AI-related concerns and perceived effectiveness. The illustrative regression model accounts for 31.5% of the variance in perceived marketing effectiveness. However, these figures are hypothetical and do not constitute findings from actual Lahore-based respondents. The study contributes a context-specific framework for examining GenAI-assisted marketing in an emerging economy and highlights the importance of human oversight, data protection, and evidence-based performance evaluation. The proposed framework may assist marketing professionals in identifying suitable AI applications while balancing efficiency with creativity, authenticity, and customer trust. Empirical validation using genuine survey responses is required before substantive conclusions can be drawn.