Risks Associated with the Use of Artificial Intelligence: A Comprehensive Review

Abstract

Artificial Intelligence (AI) is increasingly being adopted across healthcare, finance, manufacturing, cybersecurity, education, and other sectors because of its ability to support prediction, automation, pattern recognition, and decision-making. However, the growing use of AI also introduces technical, security, economic, ethical, and social risks. This study examines the major risks associated with AI and classifies them into data privacy and security, algorithmic bias, lack of transparency and explainability, cybersecurity threats, economic and employment effects, and ethical and social concerns. A qualitative review-based methodology is used to examine relevant research and established AI risk-management frameworks. The study further discusses how these risks can affect different industries and reviews mitigation approaches including data governance, explainable AI, cybersecurity controls, human oversight, continuous monitoring, and governance mechanisms. The findings indicate that AI risk management should be addressed throughout the AI lifecycle rather than only after system deployment. A coordinated approach involving technical safeguards, organizational practices, human oversight, and appropriate governance can support more responsible and risk-aware deployment of AI systems.