International Journal For Multidisciplinary Research

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The Explainability Edge: Bridging the Awareness, Trust Gap in Indian AI

Author(s) Ms. Priyanka Thapa, Dr. Mini Agrawal, Ms. Khushi Varaiya, Ms. Pallavi Parihar, Ms. Anushka Kushwaha
Country India
Abstract Abstract
This study examines the effect of artificial intelligence (AI) on consumer trust and the buying process for ecommerce products in India. It includes the Mediation of Awareness on AI, the level of Personalization, explain ability (XAI) and the frequency of interaction with AI in the mediation of trust in the recommendations provided by the AI and the subsequent purchase decision. The study was of quantitative type and cross-sectional design in which from the major Indian e-commerce vendors (Amazon, Flip kart, Myntra, Meesho) questionnaire with structured likert scale was administered using of purposive sampling and snowball sampling techniques. Data were analyzed using multiple regression, which explained 61.4% of variance in consumer trust (R² = 0.614, F (4, 95) = 37.84, p < .001). Personalization effectiveness was the strongest predictor (β = 0.412, p < .001), followed by XAI (β = 0.308, p < .001) and AI awareness (β = 0.197, p < .01). The frequency at which AI was interacted with was not significant (β = 0.089, p = .143). A gap in structural awareness and trust, referred to as a Likert scale (Likert points) of 0.72, was found, significantly demonstrating that the more familiar an individual is with AI, does not automatically equate to trust or confidence in its purchase. The study provides primary regression evidence from the emerging market context, which is seldom studied, and it suggests two very promising ideas for the platform design: focus on XAI and personalization to address the awareness–trust gap.
Keywords Keywords: artificial intelligence, e-commerce, consumer trust, regression analysis, personalization, explainable AI, Technology Acceptance Model, India
Field Business Administration
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-05-29
DOI https://doi.org/10.36948/ijfmr.2026.v08i03.79958
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