INNOVATIVE ARTIFICIAL INTELLIGENCE ALGORITHMS IN ANTI-DRUG SECURITY STRATEGIES

Abstract

This article examines the transformative impact of Artificial Intelligence (AI) on the detection, prevention, and suppression of illegal drug trafficking. As illicit networks leverage increasingly complex digital tools, law enforcement must integrate advanced computational strategies to maintain operational parity. The research analyzes primary spheres of AI application, ranging from Big Data analytics and digital platform monitoring to predictive modeling and the automation of forensic processes. By synthesizing current technological achievements with existing systemic limitations, the paper provides a balanced overview of the digital shift in narcotics interdiction. Furthermore, the study addresses the critical ethical, legal, and international challenges arising from algorithmic surveillance, including data privacy concerns and jurisdictional hurdles. The findings conclude that while AI integration significantly augments the efficacy of anti-drug initiatives, its full potential is contingent upon the development of unified regulatory standards and enhanced interagency cooperation. Success in dismantling global syndicates ultimately requires a synchronized, technology-driven framework governed by transparent legal protocols.