Agent trust management: How to secure AI agents without losing revenue

AI agents are increasingly present on websites, serving roles ranging from helpful shopping assistants to malicious content scrapers, necessitating a shift from traditional bot detection methods to a more nuanced approach known as agentic trust management. This approach evaluates AI agents based on their intent and behavior rather than a binary human-or-bot classification, recognizing that AI agents can adapt and change behavior mid-session. The need for continuous monitoring and adaptive authentication policies is emphasized, as legitimate AI agents can become compromised over time. McKinsey research suggests significant economic potential from agentic commerce, with the US B2C retail market alone potentially generating up to $1 trillion in orchestrated revenue. Comprehensive visibility is crucial for organizations before implementing trust management policies, enabling them to safely engage with the agent economy by allowing beneficial automation and maintaining robust security.