Agentic consent governance layer for autonomous AI systems
A governance system that lets organizations control what AI agents may do on a user's behalf according to identity, intent, context, permitted actions, scope, and delegation lifetime. Consent changes with the environment rather than remaining a one-time checkbox approval.
online B2B Deep Tech / Infrastructure
From IBM Technology — Agentic Consent Explained: How AI Agents Act Safely and Responsibly at 00:15
Problem: Static permissions do not adequately control autonomous agents because agents can reason, change scope, involve other agents, and operate in dynamic or non-deterministic environments. The system preserves human control while allowing agents to act with users rather than instead of them.
For: Organizations operating AI agents that can autonomously execute actions, access information, or involve multiple agents and systems.
Examples
- Email-agent access: allow the agent to read email while preventing it from sending or deleting email.
Other takes on AI security infrastructure
- Enterprise agentic last-mile identity and access control layer
- Identity-based security infrastructure for multi-agent AI systems
- AI-agent security and control infrastructure for enterprises
- A guardrail tool that enforces strict test-driven development and other engineering rules for AI coding agents
- AI-powered scam-interception and threat-intelligence service
- Secure compiler for AI-agent skills