Why self-running agents are creating the biggest security crisis of 2026 (www.techradar.com)

In 2026, the landscape of enterprise artificial intelligence has transformed into an era characterized by autonomous agents that actively perform complex tasks across business systems without human intervention. This significant shift, while enhancing efficiency and scalability, has also created a stark trust gap in security, as traditional tools struggle to differentiate between legitimate and malicious automated actions. Security teams are now facing the challenge of managing risks at a pace that outstrips human oversight, making it imperative to distinguish between beneficial and harmful behaviors in real time. The rise of these agents has expanded the corporate attack surface, introducing new vulnerabilities, such as "Shadow AI 2.0," where unauthorized agents can operate beyond established security protocols. To combat these risks, organizations must implement dynamic and continuous AI asset inventories and deploy deep network observability to monitor real-time agent behavior. By focusing on the behavior of data rather than the identity of users, security teams can effectively identify anomalies indicative of potential breaches, such as unauthorized data transfers. This comprehensive approach to monitoring and governance is crucial for ensuring that the benefits of agentic automation are harnessed while maintaining data integrity and regulatory compliance.