Extracting Key Perceptual Factors Shaping Consumer Attitudes Toward AI-Enabled Advertising: An Exploration

In an ever-evolving digital ecosystem, artificial intelligence (AI) is establishing itself as a disruptive power in advertising, significantly transforming how organisations engage with customers. While programmatic advertising provides unparalleled levels of personalisation and precision in ad-targeting, it also poses challenging issues related to trust among consumers, perceived intrusion, emotional discomfort, and ethical data practice. Understanding the psychological underpinnings of consumer perception in this context is imperative, particularly in emerging markets such as India, where digital literacy is uneven and regulatory frameworks are still maturing. This study aims to extract and interpret the latent factors that shape Indian consumers' perceptions towards relevance of AI-enabled advertising. Employing a structured survey instrument, data were collected from 302 digitally active Indian respondents via a Likert-scale questionnaire. The data were analyzed using Exploratory Factor Analysis (EFA) through Principal Component Analysis (PCA) with Varimax rotation to reveal the underlying constructs governing consumer attitudes towards AI-enabled Advertisements. Nine distinct perceptual factors were identified, namely Perceived Privacy Intrusion, Perceived Ad-Relevance, Perceived Trustworthiness, Perceived Ad-Value, Perceived Privacy Assurance, Purchase Intent, Perceived Information Quality, Information Disclosure Discomfort and Click Willingness. Together, these factors provide a nuanced conceptual framework for understanding how Indian users engage with AI-generated advertisements at cognitive, affective, and behavioural levels. This study adds to the literature by finding and naming the factors for consumer perception in AI advertising, including implications for advertisers, and policymakers looking to create effective AI advertising ecosystem