Mare, Zivai Machaka ORCID: https://orcid.org/0000-0002-9742-3602 and Dogru Dastan, Humeyra ORCID: https://orcid.org/0000-0002-3595-1274 (2025) Leveraging AI in social marketing: exploring the role of AI in healthy eating and exercise behaviour. In: World Social Marketing Conference (ISMA) 2025, 5th - 7th November, 2025, Alicante, Spain.

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Abstract

Obesity is a widespread and complex public health issue linked to reduced life expectancy and numerous chronic diseases, including heart disease, type 2 diabetes, cancer, and mental health disorders. Regular physical activity (exercise) and a healthy diet rich in fruits and vegetables can contributes significantly to maintaining healthy weight and overall health. Despite efforts by public and private institutions to implement interventions aimed at promoting healthier lifestyles, the issue remains highly prevalent. Despite ongoing interventions by both public and private sectors to promote healthier lifestyles, obesity remains persistently widespread in society. Recently, artificial intelligence has emerged as a promising tool that can be integrated into such interventions to support and enhance positive behaviour change.
This study forms part of a broader research initiative aimed at generating formative insights into the application of artificial intelligence (AI) in social marketing interventions focused on health and well-being. The study explores the perceptions on AI as a tool for supporting positive healthier eating and exercise behaviour. The facilitators and challenges associated with its use using contextual data online are explored. The social cognitive theory is referred to as a guiding framework. The study uses a netnographic approach to capture naturally occurring online discourse on the use of AI in healthier eating and exercise behaviour.
The study analysed the qualitative data from 2 online communities that discussed AI use in healthy eating and diet for weight loss using NVivo software. Findings showed that facilitators of AI use included the perceived usefulness such as content creation, interactivity, and organisation features. Also noted was the perceived ease of use, with users noting its simplicity, convenience of photo uploads for calorie counting and time saving. However, challenges were identified in personal, technical, and accessibility aspects, included limited technical knowledge, emotional barriers, and privacy concerns. Technical criticisms included poor personalisation, a lack of holistic understanding of weight loss, and high costs for premium versions of AI. Related to external determinants, users commented on the abundance of incorrect information about weight loss and lack of external mental support.
The contribution of this research is twofold. First, it employs a netnographic methodology, to capture naturally occurring online discourse. This approach enables the collection of rich, contextual data that emerges organically in digital environments. Second, the study investigates authentic public conversations surrounding the use of AI for social good specifically on healthier eating and exercise, thereby uncovering nuanced perceptions and sentiments often overlooked by conventional survey-based methodologies. Consequently, both the methodological approach and the AI focus of this study contribute significant insight to the field of social marketing. The insights derived may inform practitioners in the development of more effective social marketing interventions that incorporate AI strategies which are customised to the preferences of the target audience and aligned with global health and well-being objectives.

Item Type:	Conference or Conference Paper (Paper)
Uncontrolled Keywords:	social marketing, AI, behaviour change, healthy lifestyle
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce R Medicine > RA Public aspects of medicine
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > School of Management and Marketing
Last Modified:	27 Jan 2026 10:46
URI:	https://gala.gre.ac.uk/id/eprint/52344

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