Topic starter
16/04/2026 6:55 pm
TL;DR: AI agent activity grew 300x in 2025, and Obsidian Security says nearly 40% of observed agents now carry medium to critical risk as overprivileged, unaudited workflows expand across enterprise apps. The governance problem is no longer agent adoption itself, but the toxic access combinations created when human-paced IAM controls cannot track machine-speed delegation and data movement.
Editorial analysis by NHI Mgmt Group, based on content published by Obsidian Security: “AI agents are silently changing how data leaves your apps. Here’s how to stay ahead.”.
By the numbers:
- AI agent activity grew 300x in 2025.
- Nearly 40% of agents carry medium-to-critical risk factors.
- The average environment contains over 800 risky agents.
Key questions
Q: What breaks when AI agents are given broad enterprise access without tight governance?
A: Broad access turns AI agents into high-speed execution paths that can move data, spend money, modify records, or delete assets before operators can intervene.
Q: Why do AI agents create risk even when they stay within approved permissions?
A: AI agents can be authorised correctly and still produce harmful outcomes because permission is not the same as intent or behavioural appropriateness.
Q: How can security teams tell whether agent access is actually under control?
A: Look for evidence that the team can trace every tool call, secret use, and cross-system action back to a named owner and a valid approval path.
Practitioner guidance
- Inventory all active AI agents Build a current register of agents, their owners, connected apps and credential types so no workflow is invisible to security or IAM teams.
- Review agent permissions as combined pathways Assess whether read, write and sharing privileges create compound access that exceeds the business purpose of the agent.
- Bind agent credentials to lifecycle ownership Require a named accountable owner, a revocation path and an offboarding event for every agent credential, including OAuth tokens and linked integrations.
Bottom line: The article’s core warning is that AI agent sprawl turns ordinary permissions into compound access paths that widen blast radius across business apps.
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12/10/2026 3:32 pm
Agent sprawl is becoming an access governance problem before it becomes an AI governance problem. The article shows that the immediate risk is not model reasoning or prompt quality, but unmanaged entitlement growth across SaaS and business apps. When agents are allowed to inherit broad access without ownership discipline, the identity layer becomes the weakest point in the AI stack. Practitioners should treat every new agent as a governed identity, not a feature toggle.
A few things that frame the scale:
- 53% of security leaders expect AI to run major portions of their infrastructure autonomously within the next three years, according to the 2026 Infrastructure Identity Survey.
- 19% of organisations give AI systems dramatically more access than human employees, nearly one in five granting unrestricted privilege, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: Who is accountable when an AI agent keeps running after its creator leaves?
A: The accountable owner must be the organisation, not the departed employee. If the agent’s credential was tied only to a personal account, offboarding the user does not guarantee the token is revoked. That is a governance failure in lifecycle design, because ownership and revocation should follow the agent itself, not just the human who created it.
👉 Read our full editorial: AI agent sprawl is exposing toxic access combinations in apps