Today, different tools may be used to discover AI applications, monitor cloud environments, control employee interactions with AI, and manage emerging AI agents: while each solution addresses a specific requirement, this fragmented approach can introduce overlapping licenses, duplicate alerts, inconsistent policies and limited visibility across the organization.

Abnormal AI is addressing this challenge by expanding its AI security suite around the same behavioural platform used for email and identity protection: the strategy is based on creating a more unified security layer capable of providing shared context across different AI-related activities.

The solution focuses on discovering sanctioned and unsanctioned AI usage while supporting policy management, spend visibility, and audit evidence.

As the number of AI applications and autonomous agents grows, organizations will need to maintain visibility over what AI is being used, who owns it, which systems and data it can access, and how risky activities are controlled.

For security leaders, the question is therefore becoming increasingly relevant: is adding more security tools really improving protection, or is fragmentation becoming part of the problem?

A more integrated approach to AI security and governance could help organizations reduce operational complexity while establishing more consistent visibility and control as their AI environments expand.

The challenge is no longer simply securing AI. It is securing AI at scale without losing visibility, governance, and control

Read more: Abnormal AI’s expanded security suite asks the question: What’s the true cost of fragmented security?