Zscaler finds enterprise AI adoption soars 600% in less than a year, putting data at risk

The reliance of enterprises on AI/machine learning tools has skyrocketed nearly 600%, with transactions increasing from 521 million in April 2023 to 3.1 billion monthly by January 2024. Concerns over security have led to a substantial rise in AI/ML transactions being blocked, up by 577% in nine months. Cyber attackers have evolved their tactics, employing weaponized LLMs and adversarial AI to target organizations undetected.

Zscaler’s ThreatLabz 2024 AI Security Report underscores the critical need for a scalable cybersecurity strategy to safeguard AI/ML tools. The report, based on over 18 billion transactions analyzed, highlights data protection, AI data quality management, and privacy as top concerns for enterprises. Industries like healthcare, finance, technology, and manufacturing are adopting AI/ML tools but remain vulnerable to cyber threats.

Leading cybersecurity vendors are intensifying efforts to leverage AI in combating evolving cyber threats, aiming to enhance security beyond merely blocking transactions. Insights from telemetry data and collaborations with third-party partners are crucial in detecting novel cyber threats in real-time. While enterprises face heightened risks from generative AI tools and automation, adequate risk management and a robust cybersecurity strategy are imperative.

The amalgamation of productivity and security measures is crucial in navigating the intricate AI threatscape, as attackers increasingly rely on AI for launching ransomware attacks at scale. The use of generative AI in ransomware and targeted attacks is expanding, posing challenges in detection and mitigation for enterprises. Attackers are leveraging AI to amplify ransomware tactics, targeting vulnerabilities in supply chain partners to inflict chaos on organizations.