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Hyper-Personalization at Scale versus Consumer Privacy in AI-Powered Marketing

 

 

Dr. Pradeep Munda1, Mr. Amitabh Chandan2, Mr. Vaivaw Kumar Singh3

1Assistant Professor, Department of Management, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

2Assistant Professor, Department of Management, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

3Research Scholar, Faculty of Business Management, Sarala Birla University, Ranchi, Jharkhand, India

p.munda@bitmesra.ac.in1 ; amitabhchandan@bitmesra.ac.in2 ; vaivawsingh@gmail.com3

 

 

Abstract: The rapid expansion of Artificial Intelligence (AI) and big data analytics has changed the ways that brands use to contact their customers. They now can communicate directly with the consumer by using hyper, personalized marketing instead of traditional segmentation (Hemantha, Reddy, & Kamble, 2025). Hyper, personalisation is an AI, driven process where algorithms automatically generate marketing messages, content, and user experiences that best suit each consumer by analysing a large volume of data such as the route a user takes while browsing, purchase history, GPS coordinates, and preferences that are inferred (Al Prince et al., 2022). These programs, when used properly, draw in customers, increase the rate of transactions, and thus, long, term loyalty is solidified (Mulyono & Saputra, 2024).

Nevertheless, they compromise consumers' privacy very deeply. The switch to behavioural and contextual data as a source of information has led to the emergence of challenges of ethical, regulatory, and trust kinds, as users, in most cases, have no power over the way their data are harvested, treated, and employed for automated decision, making (Gupta, Sharma, & Mathew, 2025). Literature findings imply that consumers demand relevance and ease of use, however, they voice uneasiness and reluctance when personalisation invades their privacy rights, thus marking the so, called "creepiness threshold" (Beniwal, Khanna, & Kaur, 2025).

Furthermore, lawful regimes like the EU’s General Data Protection Regulation (GDPR) and India’s Digital Personal Data Protection Act (DPDPA) require that entities observing norms of data minimisation, acquiring clear consent, and algorithmic transparency be fulfilled (Mulyono & Saputra, 2024). Marketers are having a hard time strategically balancing these legal mandates with their endeavor for personalisation on a large scale.

This paper discusses the increasing compromise between the scalability of hyper, personalisation and the safeguarding of consumer privacy in AI, powered marketing ecosystems. It thoroughly examines present literature, pinpoints the technological and organisational contributors to large, scale personalisation, and deliberates the ethical and regulatory restrictions accompanying data, driven marketing practices (Gupta et al., 2025). A conceptual framework is put forward to depict the interplay between scale, perceived benefits, privacy risks, and consumer trust. The research ends with the viewpoint that enduring hyper, personalisation is contingent on the implementation of privacy, by, design, transparency, and user empowerment principles (Tran et al., 2025), which give assurance to organisations that they are able to use AI in a responsible manner while at the same time, keep consumer trust and abide by regulations.

Keywords: Hyper-personalisation, AI-powered marketing, consumer privacy, scale, ethical marketing, data protection.

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