Beyond Algorithms: Cultural Sensitivity and Cost Considerations in User Acceptance of AI-Driven Personalised Nutrition

Authors

S. Mahalakshmi

Assistant professor, Department of Home Science, Nutrition Food Service Management and Dietetics (India)

Mahasrii.N

B.Sc., Student, Department of Home Science, Clinical Nutrition and Dietetics (India)

Jaya Sri.R

B.Sc., Student, Department of Home Science, Clinical Nutrition and Dietetics (India)

Article Information

DOI: 10.51584/IJRIAS.2026.11050122

Subject Category: Artificial Intelligence

Volume/Issue: 11/5 | Page No: 1412-1428

Publication Timeline

Submitted: 2026-04-01

Accepted: 2026-04-06

Published: 2026-06-04

Abstract

In the realm of digital health, the personalization of AI-driven nutritional guidance has emerged as a critical factor. This study aims to explore the user’s perception regarding personalization and practicality in relation to AI-generated nutrition plans and diet plans created by dietitians. Furthermore, it highlights the significance of cultural sensitivity, emotional intelligence, and cost as essential determinants of user perceptions. It also emphasizes key factors like cultural sensitivity, emotional intelligence, and cost, which are crucial in determining user perceptions. Data were collected from 126 participants across various age groups ranging from adolescents to adults through a structured questionnaire assessing comfort with AI, personalization quality, cultural integration, and effectiveness relative to Dieticians. The economic aspect is also considered when assessing the feasibility of AI-generated plans. The findings suggest that while AI is perceived as advantageous and potentially more economical, reservations persist regarding its capacity to fully comprehend cultural nuances and offer emotionally attuned guidance. Consequently, the results indicate that enhancing personalization features within AI systems and fostering AI-human collaboration (hybrid models) would likely yield superior outcomes in the realm of nutritional care.

Keywords

Artificial intelligence (AI), Personalised nutrition, Cultural Preferences, Cost influence, AI-Human collaboration (Hybrid model)

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References

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