This episode is available to stream on-demand.

As AI takes on a larger role in managing and securing networks, traditional methods of oversight are no longer enough. Decisions are being made faster, deeper in the infrastructure, and often without direct human involvement. This panel explores how automation, machine learning, and distributed control are reshaping what trust means in modern network environments - and what needs to change to keep that trust intact.

• The limits of static controls in real-time, AI-driven networks
• Risks from data drift, opaque models, and automation errors
• The role of telemetry and observability in maintaining control
• Applying zero-trust principles in autonomous systems
• How trust models must adapt to AI-native environments