Utilization of digital technologies in the industry has been very effective in boosting the performance of the organizations. At the same time, it has increased the attack surface available to the cyber criminals. Diversity of cloud services, networks and applications has made it challenging to ensure that there will be effective detection of threats and policy enforcement. Traditional measures have limited scope and cannot effectively tackle cyber threats. AI based policy enforcement and threat detection model that combines the Artificial Intelligence, Data Analytics and Machine Learning to protect the organization and ensures compliance with the regulations.

Purpose of AI-drive policy enforcement is to verify privacy, access control and data governance principles. Models in AI predict accurately on suspected violations, since they learn continuously from the workflow in the organization unlike the traditional systems. Therefore, such system has the capability of automatically blocking any action when the employees try to conduct fraudulent data transfer. Usage of natural language processing in emails and documents ensures that there will be ethical and legal compliance in the communications. Therefore, AI eliminates the manual error prone process in applying policies into intelligent purpose.

AI contributions to threat detection: When machine learning and deep learning models analyze the volume of network traffic, system logs and user activities, they are equally important. AI creates baselines of normal activities and detects the irregularities in form of abnormal logins, erratic data download and abnormal trends in accessing the systems. These irregularities may indicate phishing, ransomware and zero-day threats. AI has the capability of identifying new and hidden threats that are opposite to the traditional signature based systems. Some systems also automatically react to prevent worst attacks by actions such as removing access privileges, blocking malicious IP addresses or isolation of the affected systems.

Models of AI powered detection and enforcement can be seen in several areas. AI enhanced Intrusion system and security information and event management solutions provide visibility for various attack patterns in cyber security. Artificial Intelligence in the Banking Industry provides compliance to anti-money laundering regulations by prohibiting fraud transactions after detecting the unusual patterns. Health care industries use AI in order to protect patients' information and ensure compliance with regulations such as HIPPA. Cloud infrastructure uses the AI capability in detecting configuration errors, policy infractions and unusual access activity where traditional monitoring proves insufficient. Similarly, Business sectors use AI to ensure compliance across geographically distributed IT Systems, access control and prevention of data leakages.

The advantage of this strategy is immense. Scalability – processing massive amount of information beyond the capabilities of human beings - and adaptability – learning new attack methods and changes in regulations - are two of the advantages of artificial intelligence. With such abilities, it becomes possible to implement proactive defense measures by identifying and eliminating threats in advance. Moreover, it helps to eliminate the inconsistencies which occur in the manual monitoring by minimizing human errors. AI based solutions offer enterprises a comprehensive defensive solution which helps to increase resilience and trust by integrating governance and security.

The enormous possible of AI powered threat detection and policy enforcement is obvious; however, there are challenges in terms of false alarms, privacy concerns and necessity of frequent updates. AI can provide adaptive security, ensure compliance and be the base of secure and resilient digital ecosystems under correct supervision and moral usage.

Key Words:  Attack, IOT, Defence, Artificial Intelligence, NLP