Infiltration of Organised Crime within Organisations in the Era of Artificial Intelligence: The Implementation of Predictive Indicators in Government Strategies

Abstract

This study examines the infiltration of Organised Crime (OC) within legitimate organizations in the era of Artificial Intelligence, focusing on the implementation of predictive indicators in government strategies. Organised Crime infiltration represents a significant threat to economic and social stability, eroding social trust, discouraging foreign investment, and distorting market dynamics. The research explores how OC employs organizational infiltration as a primary strategy to penetrate the legal economy through both "Shell Organizations" and "Front Organizations." The study proposes implementing AI-powered predictive models within government strategies to enhance detection capabilities of OC infiltration. Utilizing the Technology-Organisation-Environment (TOE) theoretical framework, the research investigates how organizational context influences the integration of AI tools for identifying infiltrated organizations. Three key propositions are examined: P1) AI implementation increases accuracy and speed in detecting OC infiltration; P2) AI-powered models in law enforcement negatively correlate with OC activity; and P3) AI adoption positively correlates with socio-economic community development. The research addresses critical questions regarding current Business, Management and Accounting doctrine effectiveness, AI's role in predictive analysis, and implementation challenges. Despite concerns about data quality, privacy, and implementation costs, the study argues that AI integration represents a strategic opportunity to counteract OC infiltration while promoting socio-economic development and reinforcing legal principles.