AI-POWERED PREDICTIVE ANALYTICS IN MARKETING: ETHICAL CONCERNS SURROUNDING CONSUMER MANIPULATION AND PRIVACY
AI has taken marketing to a new level by ensuring the use of predictive analytics in developing new marketing strategies that accurately address clients' needs. While bringing about changes in the corporation's ability to efficiently meet its customer needs, these technologies raise ethical issues of explicit customer manipulation, privacy violation, and customer data use. This research uses a quantitative research method with a deductive approach to investigate these matters and hypotheses on 300 online consumers impotent with AI-based marketing advertisements. Both closed-ended questionnaires were used to collect the data and were analyzed using the statistical package of social sciences. Based on the general view of participants, 72% of consumers think that AI in advertisements is invasive, and 58% of customers easily fall victim to purchasing products they never intended to purchase due to AI recommendations. Unfortunately, only 35 percent of the consumers polled showed an understanding of how their data is collected and used, a decision that indicates that there remain transparency gaps in current procedures. In addition, 81% of the participants showed a high level of concern for restrictive regulation of AI in marketing to protect privacy and selfdetermination. These conclusions pave the way for the demand for increasing uses of ethical AI tools and measures, increased procedures for accountability, and improvement of legislation in data protection. The work can add to the current discussions of the responsible use of AI in marketing and bring some empirical results for policymakers and other stakeholders. By tackling these ethical issues, businesses can improve user trust and the continued use of AIbased predictive analytics in today's dynamic business environment.
Authors
- TUBA SAMEEN
Institutions
- Haliç University (TR)
Publication Details
- Journal
- International Journal of Social Sciences and Management Review
- Published
- 2025-01-01
- DOI
- https://doi.org/10.37602/ijssmr.2025.8326
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00