The AI-Enhanced Trafficking Threat: Examining the Technological Evolution of Trafficking in Persons Operations with AI Tools
Joel Levesque · Journal of Human Trafficking · 2025
This paper examines the emerging threat posed by artificial intelligence (AI) integration into trafficking in persons (TIP) operations, presenting a threat taxonomy of how AI tools enhance trafficking across three stages: identifying potential victims, recruiting and engaging them, and exercising control and exploitation. It draws on law enforcement cases, industry reports, and academic literature to present evidence on the ways in which inexpensive, powerful, and widely available AI tools, such as large language models (LLMs), enable traffickers to profile vulnerable individuals and then use targeted, personalized, social engineering techniques to recruit them. Deepfake and voice synthesis technologies further enable traffickers to mask activities, reinforce control, and exploit victims. The article stresses the accelerating nature of AI technology and the widening gap between malicious AI capabilities and institutional capacity to respond, arguing for adaptive strategies across legal, operational, and technological domains. This includes updated criminal codes, enhanced law enforcement training, regional cooperation frameworks, investment in AI-powered counter-trafficking tools, and platform accountability measures.