BACKGROUND-AIM:
Tobacco use and nicotine addiction remain among the most significant preventable causes of morbidity worldwide, particularly affecting young populations who are increasingly exposed to digital environments where risk behaviors evolve rapidly. Traditional prevention approaches are often insufficient to capture early indicators of tobacco initiation and poly-use patterns involving e-cigarettes and emerging nicotine products. This study aims to present the innovative use of artificial intelligence (AI) and digital tools by Green Crescent Türkiye to enhance early detection, prevention and behavioral counselling within tobacco control efforts. The objective is to demonstrate how AI-supported systems can strengthen public health responses, inform policies and scale evidence-based interventions for youth and adults.

METHODS:
A multi-component digital prevention framework was developed, integrating: 1. AI-driven risk analytics, using anonymized behavioral and engagement data from digital platforms to identify early signs of tobacco and nicotine experimentation 2. Digital health education tools, including interactive e-learning modules, gamified prevention apps, and targeted content for adolescents 3. AI-supported counselling models within the Green Crescent Counselling Centers (YEDAM), enabling automated needs assessment, personalized behavioural plans, and enhanced case management 4. Population-level data monitoring, combining survey insights, digital behavioural patterns, and trend analyses to inform prevention strategies Descriptive analytics, user engagement metrics, and pilot evaluation data were systematically reviewed.

RESULTS:
AI-supported risk detection models successfully identified key behavioural markers associated with early tobacco use among adolescents, improving the precision of targeted prevention messaging. Digital education tools reached high engagement levels, with increased knowledge scores and positive shifts in attitudes toward tobacco avoidance. Within YEDAM services, AI-assisted assessment improved counsellor efficiency and contributed to more individualized care pathways. Population-level digital monitoring highlighted emerging nicotine trends, supporting timely policy recommendations and community interventions.

CONCLUSIONS:
Integrating AI and digital technologies into tobacco prevention efforts offers significant potential for enhancing early detection, tailoring interventions and strengthening behavioural health services. The Green Crescent experience demonstrates that technology-enabled, person-centred approaches can complement traditional prevention strategies, particularly among digitally active youth. Scaling such models across public health systems may contribute to accelerated progress toward tobacco-free societies and support global efforts under the Sustainable Development Goals.