As dependence on integrated systems and IoT increases, industrial control systems (ICS) continue to remain vulnerable to cybersecurity threats. The cyber risks that could affect ICS include; unauthorized data access, system disruptions and loss of data. To reduce such risks, the adoption of artificial intelligence (AI) is being seen rising rapidly. Such applications have the potential to identify anomalies, identify problems, and immediately take steps to minimize risks. In this paper, the authors aimed at analyzing the application of AI technology for enhancing cybersecurity of ICS with concerning techniques including anomaly detection, intrusion detection, and behaviour analysis. It also discussed the issues correlated with the AI solutions used for cybersecurity, including data privacy, system of AI, and continuous monitoring, as well as updates of the AI. In the last conclusion, the authors introduced an innovative hybrid model of machine learning to detect the anomalies in the ICSs. From this paper, insights on the usage of AI in strengthening the ICS security, and minimizing chances of an attack and data breach will be developed.