Overreliance on AI in Oil and Gas Cybersecurity: A Review of Risks and Mitigation Strategies

Abstract Artificial Intelligence (AI) has become a keystone of modern cybersecurity, delivering significant advancements in threat detection, incident response, malware analysis, vulnerability management, risk assessment, and threat intelligence. With AI capabilities to process massive datasets and automate complex decisions, AI enables faster and more resilient cybersecurity operation, and the reliance on AI increases. This paper sheds light on overreliance on AI in cybersecurity solutions and studies how it can introduce risks to critical security functions. This study seeks to provide the best mitigation strategies to strengthen cyber resilience in critical environments such as oil and gas. This targeted study adopts a Systematic Literature Review (SLR) research methodology that aims to analyze AI-driven cybersecurity practices, the risk factors associated with reliance on AI automation, and existing mitigation strategies. It focuses on an in-depth review of the current literature related to AI overreliance in cybersecurity, particularly with a specific focus on the oil & gas industry. This paper suggests that overconfidence in AI can lead to significant risks and aims to show the importance of having the right balance between AI adoption and human oversight. Therefore, achieving resilient cybersecurity requires a balanced framework that merges the capabilities of AI with the critical reasoning, intuition, and contextual understanding of human operators.