Top 6 Cybersecurity Threat Detection Use Cases: How AI/ML Can Help Detect Advanced and Emerging Threats

AI/ML tools and technologies heavily influence the modern digital landscape by introducing numerous use cases involving AI-based malware detection, preventing social engineering attacks, and threat identification and remediation. Many organizations have acknowledged AI/ML's prominence in the cybersecurity threat landscape and have started to leverage AI/ML in their business and security requirements. AI/ML-based solutions assist employees to complete their day-to-day tasks more efficiently and in no time. However, at the same time, we have also witnessed an exponential increase in the cybersecurity threat landscape. Hence, cybersecurity professionals and software developers have also started using AI/ML to build more innovative, adaptive, and robust systems and applications to protect an organization's IT and network infrastructure.    

Statistics: AI/ML in Cybersecurity

In recent times, we have witnessed the widespread adoption and exponential growth of AI and ML technologies. Below are the statistics taken after thorough research highlighting the impact of AI/ML tools and techniques on cybersecurity threat detection and increasing overall cybersecurity performance.