For every enterprise CISO in the world right now, the burning question isn’t about cloud, TPRM, or internal threats. It’s about how to securely and responsibly adopt AI—specifically, agentic AI, the buzziest of today’s AI buzzwords. There’s no shortage of stats on skyrocketing adoption trends. Consider EY’s recent Technology Pulse Poll, which found that half of tech leaders have at least begun deploying agentic AI within their organizations.

In 2025, data is everywhere, in your inbox, on your phone, and flowing through a maze of corporate servers. It’s the lifeblood of business, medicine, and everyday life. Unfortunately, that makes it irresistible to thieves. Not the smash‑and‑grab burglars of old but quiet intruders who watch and learn before they start siphoning off secrets. In cybersecurity circles, this quiet theft is called data exfiltration. There’s a good reason security experts are ringing alarm bells.

Managing users in Atlassian Crowd often feels like walking a tightrope. You’re expected to ensure seamless access for every team member, revoke access the moment someone leaves, manage directory syncs, assign and revoke group permissions, and keep everything audit-ready at all times. And while Crowd gives you a central place to manage users across Jira, Confluence, Bitbucket, and more, it still largely demands manual efforts from admins.

Why unifying fraud, security, and compliance functions is key to resilience, trust, and agility in the age of AI-powered financial crime.

‍Cyber risk quantification (CRQ) is the process of translating cyber intelligence, both organization-specific and external, into measurable business terms. Typical high-level outputs include Average Annual Loss (AAL), or a business's expected financial loss from cyber events, and the Annual Events Likelihood. With CRQ, cyber governance, risk, and compliance (GRC) leaders can also drill down into more granular metrics for additional, scenario-specific context.