AI-BASED PERSONALIZATION AND CONSUMER TRUST: A CONCEPTUAL FRAMEWORK FOR UNDERSTANDING THE PERSONALIZATION–PRIVACY PARADOX

Abstract

The rapid development of artificial intelligence has significantly transformed digital marketing practices, particularly through the widespread adoption of personalized customer experiences. While AI-based personalization enhances relevance, convenience, and decision efficiency, it simultaneously raises concerns about privacy, data usage, and algorithmic control. This duality is conceptualized in the literature as the personalization–privacy paradox. Drawing on existing literature, this study develops a comprehensive conceptual framework explaining how AI-based personalization influences consumer trust. The framework proposes that personalization generates two opposing perceptions-perceived benefit and perceived intrusiveness-which in turn shape trust. Trust functions as the central mechanism linking personalization to behavioral intentions, while algorithmic transparency and privacy assurance are introduced as moderating variables conditioning this relationship. By integrating previously fragmented research streams, the study offers a unified perspective on the dynamics between AI-based personalization and consumer trust, and argues that the impact of personalization on trust is highly conditional-dependent on the balance between perceived benefits and perceived privacy risks.

Keywords

• Artificial Intelligence
• Personalization
• Consumer Trust
• Privacy Concerns
• Algorithmic Transparency

YAPAY ZEKÂ TABANLI KİŞİSELLEŞTİRME VE TÜKETİCİ GÜVENİ: KİŞİSELLEŞTİRME –GİZLİLİK PARADOKSUNA YÖNELİK KAVRAMSAL BİR ÇERÇEVE

Abstract

Yapay zekâ teknolojilerindeki hızlı ilerleme, özellikle kişiselleştirilmiş müşteri deneyimlerinin yaygınlaşmasıyla birlikte dijital pazarlama uygulamalarını köklü biçimde dönüştürmüştür. Yapay zekâ tabanlı kişiselleştirme; uygunluk, kolaylık ve karar etkinliği bakımından tüketicilere belirgin kazanımlar sağlarken, gizlilik, veri kullanımı ve algoritmik kontrol konularında ciddi kaygıların da zeminini hazırlamaktadır. Bu ikili yapı, literatürde kişiselleştirme–gizlilik paradoksu olarak tanımlanmaktadır. Çalışma, mevcut literatüre dayanarak yapay zekâ tabanlı kişiselleştirmenin tüketici güveni üzerindeki etkisini açıklayan kapsamlı bir kavramsal çerçeve geliştirmektedir. Önerilen çerçevede kişiselleştirmenin iki zıt algı ürettiği ileri sürülmektedir: algılanan fayda ve algılanan müdahalecilik. Bu algılar, kişiselleştirme ile davranışsal niyetler arasındaki ilişkiyi aracılayan merkezi mekanizma olarak güveni şekillendirmektedir. Algoritmik şeffaflık ve gizlilik güvencesi ise söz konusu ilişkiyi koşullandıran düzenleyici değişkenler olarak modele dahil edilmiştir. Parçalı literatür akımlarını bütünleştiren çalışma, yapay zekâ tabanlı kişiselleştirme ile tüketici güveni arasındaki dinamiklere daha bütünlükçü bir bakış açısı kazandırmakta ve kişiselleştirmenin güven üzerindeki etkisinin koşullu olduğunu-algılanan fayda ile gizlilik riski arasındaki dengeye bağlı biçimde farklılaştığını-ortaya koymaktadır.

Keywords

• Yapay Zekâ
• Kişiselleştirme
• Tüketici Güveni
• Gizlilik Kaygısı
• Algoritmik Şeffaflık

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