As companies adopt AI-driven and agent-assisted experiences, a new tension is emerging inside the enterprise. Growth teams see clear upside: smoother discovery, faster purchasing, and more automated customer journeys. Security and identity teams, however, are being forced to rethink how trust works.
It’s no longer enough to verify a user or distinguish a human from a bot.

The real question is what kind of actor is interacting with your systems, whether they are acting on behalf of a legitimate user, and what level of access they should have.
In this environment, the shift is not just in signals but in decision-making. Instead of one-time access checks, teams must evaluate intent over time, trust across sessions, and the relationship between accounts, devices, behavior patterns, and non-human actors. These trust decisions increasingly overlap with fraud prevention and real-time business policy, especially during high-risk moments like login, account creation, recovery, and purchase.
In high-demand commerce scenarios, such as limited product releases, fraud actors exploit gaps at scale. The challenge is not just blocking automation, but connecting signals across sessions and accounts to make better, real-time trust decisions.