Speaker
Description
This review synthesizes research on "transparency in AI marketing, consumer trust, brand reputation" to address the fragmented understanding of how transparency initiatives influence consumer perceptions and brand outcomes amid ethical and practical challenges. The review aimed to evaluate transparency’s role in fostering trust and brand reputation, benchmark ethical frameworks, identify mediating factors between transparency and loyalty, analyze ethical dilemmas in personalization and privacy, and compare industry-specific transparency practices. A systematic analysis of 50 interdisciplinary studies from diverse geographic contexts employing qualitative, quantitative, and mixed methods was conducted. Findings indicate that transparency significantly enhances consumer trust by clarifying AI processes and data use, while ethical frameworks integrating transparency, fairness, and privacy remain under-implemented in practice. Transparency mediates the balance between personalization benefits and privacy concerns, fostering brand reputation and consumer engagement, though its impact varies across industries and consumer segments. Communication strategies employing nuanced transparency cues effectively modulate trust but require tailoring to diverse audiences. The synthesis reveals persistent gaps in operationalizing transparency standards, longitudinal impact assessment, and cross-industry benchmarking. These findings underscore transparency’s centrality in responsible AI marketing and highlight the need for standardized frameworks and empirical validation to sustain consumer trust and ethical brand equity in evolving AI landscapes.
