Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial Intelligence is everywhere nowadays. It helps teams to be more productive, but at the same time, it can threaten your critical project management data. The introduction of AI into Jira opened up new paths for attackers to exploit, new vulnerabilities coming up internally, and human errors. So, in this article, let’s speak about AI data loss in Jira and what measures to take to protect your sensitive data in Jira Cloud.

Breaches got faster. Architectures got messier. And data stopped living in tidy tables. Modern stacks push personal and regulated data through microservices, data lakes, event streams, vector stores, and LLM prompts. Encryption still matters, but it protects containers, not behaviors. As soon as an app decrypts a record, risk comes roaring back.

Security leaders spent most of the past year testing AI driven security automation. Many discovered that the promise of fully autonomous SOC operations collided with the reality of hallucinations, opaque recommendations, and inconsistent outcomes. McKinsey research now shows that more than 80 percent of organizations have not realized meaningful results from gen AI programs.

Innovation has always been the engine of American advancement. With the launch of the Genesis Mission, the White House is signaling a new era of AI-accelerated scientific discovery. This executive order directs the Department of Energy to build an integrated, national-scale AI platform designed to unlock scientific breakthroughs across biotechnology, energy, materials, quantum systems, and beyond.

As enterprises embrace agentic AI, a new security risk equation emerges. In this episode of Security Matters, host David Puner sits down with Lavi Lazarovitz, VP of Cyber Research at CyberArk Labs, to unpack how AI agents and identity security are reshaping the threat landscape. Learn why privileged access is now the fault line of enterprise security, how attackers exploit overprivileged AI agents, and what security teams must rethink before scaling AI.

Snyk empowers organizations to build fast and stay secure. As security and engineering teams scale their use of Snyk across the enterprise, understanding what's happening across your group and organizations becomes critical–from API integrations and user access patterns to policy changes and security events. However, raw audit logs alone can be overwhelming and difficult to interpret. Security leaders need instant visibility into critical events, risk patterns, and user activity.