Human–AI Collaboration in Agricultural Marketing: Consumer Acceptance of AI-Assisted Recommendations

Author

Miss. S. Sivapriya, Dr. A. Leo


Abstract

 Artificial Intelligence (AI) is increasingly transforming agricultural marketing through personalized product recommendations, consumer information, and decision support. However, consumer acceptance of AI-assisted recommendations may depend on perceived usefulness, ease of use, trust, accuracy, transparency, privacy, and human involvement. This paper develops a conceptual framework to explain consumer acceptance of AI-assisted recommendations in agricultural marketing. Grounded primarily in the Technology Acceptance Model (TAM), the framework extends conventional technology acceptance perspectives by incorporating trust in AI, recommendation accuracy, perceived transparency, privacy concerns, and human–AI collaboration. A review of relevant theoretical and empirical literature is used to develop eight propositions linking these factors with consumer acceptance and, subsequently, purchase intention and consumer decision-making. The framework proposes positive relationships between consumer acceptance and perceived usefulness, perceived ease of use, trust, recommendation accuracy, transparency, and human–AI collaboration, while privacy concerns are proposed to have a negative relationship with acceptance. The paper contributes to the emerging literature by integrating technological, trust-related, risk-related, and human factors within a unified framework. The proposed framework provides a theoretical foundation for future empirical research on consumer responses to AI-assisted recommendations in agricultural marketing.


Keywords

Artificial Intelligence; Human–AI Collaboration; Agricultural Marketing; Consumer Acceptance; AI-Assisted Recommendations; Trust in AI; Recommendation Accuracy; Transparency; Privacy Concerns



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References


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