Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The challenge isn’t just that AI agents are new. It’s that they blur traditional boundaries of data control, creating hidden sub-processors and uncontrolled data flows. For CISOs, compliance officers, and security leaders, this presents a fundamental governance problem: if you don’t know which AI services are touching your data, you cannot prove compliance.

In effect, organizations must now treat sensitive data not only as a privacy concern, but as a national security asset. This is no longer the domain of compliance officers alone—it’s a cross-enterprise challenge that demands executive-level ownership.

On June 23, 2025, the Federal Trade Commission’s sweeping amendments to the Children’s Online Privacy Protection Rule (COPPA) took effect, ushering in more stringent duties for any operator collecting or using children’s data—whether via websites, services, or AI‑powered agents. Companies must achieve full compliance by April 22, 2026 (Finnegan | Leading IP+ Law Firm, Bass, Berry & Sims PLC).

AI is moving through enterprises faster than security teams can track. Over the past year, AI privacy incidents have risen 56%, and most of those stem from tools security never knew were in use. 84% of SaaS tools are purchased outside IT, and 62% of CISOs say fewer than a quarter of AI tools in use have been approved through procurement. That means sensitive, regulated, or confidential data is often flowing to AI services invisibly, sometimes across borders, without governance or guardrails.

Here at Riscosity, we believe in making our users’ lives as easy as possible when using our product. Whether users are running scans, triaging results, or viewing reports, the workflows must be intuitive and a seamless part of users’ own environments. To that end, we have finished rounding out our comprehensive support for ticketing system integrations by adding Asana and Linear into the fold.

PwC recently did an AI agent survey where they found the following: This all sounds great, right? For many reasons it is, but agentic AI creates a challenge of visibility for organizations into how AI agents are communicating with each other and external third-party vendors. Imagine a multitude of AI agents autonomously exchanging data across a complex mesh of third-party vendors and applications.