Topic starter
11/08/2026 3:11 pm
TL;DR: AI-generated deepfakes, hallucinations and shadow AI are pushing organisations toward continuous verification of identities, devices and actions rather than default trust, according to Commvault. The governance lesson is clear: responsible AI adoption succeeds when policy, guardrails and approved tools reduce blind trust without blocking productivity.
Editorial analysis by NHI Mgmt Group, based on content published by Commvault: “Trust – The Great Disappearing Act (or Not)”.
Key questions
Q: How should security teams handle trust assumptions when customers use AI shopping agents?
A: Treat the agent as a delegated identity with a limited scope, not as a harmless interface.
Q: Why does shadow AI create more risk when organisations try to prohibit it?
A: Prohibition often shifts usage underground, which reduces visibility and weakens logging, data control, and accountability.
Q: What are the signs that continuous trust controls are too weak for AI-driven environments?
A: A common sign is that access remains unchanged after context shifts, risky actions proceed without step-up checks, and telemetry cannot explain why an identity was still trusted.
Practitioner guidance
- Define approved AI access paths Publish clear, role-based routes for sanctioned AI use so employees know which tools, data types and workflows are permitted without ambiguity.
- Verify identities at the point of use Require live validation of user, device and context before sensitive AI-assisted actions rather than assuming trust from prior authentication.
- Detect shadow AI usage Monitor for unsanctioned AI applications, browser-based use and third-party integrations that bypass the approved control plane.
Bottom line: AI trust now depends on continuous verification of identities, devices and actions rather than a single trust decision made at sign-in.
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This topic was modified 10 hours ago by NHI Mgmt Group
11/08/2026 3:26 pm
AI trust is now an identity and action-verification problem, not a branding problem. The article correctly frames trust as something that must be continuously validated across people, devices and actions rather than assumed after one login or one policy acknowledgement. In practical terms, the security question is whether the current action still fits the approved identity context. That makes the issue squarely relevant to IAM, NHI governance and AI control design.
A few things that frame the scale:
- Organisations that describe themselves as confident in their AI deployment actually experience a 72% security incident rate, compared to 33% for those who remain cautious, according to the 2026 Infrastructure Identity Survey.
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: Should organisations trust AI differently from human users and devices?
A: Yes, because AI can generate deceptive output, imitate people and operate through delegated or non-human paths. The right model is not to distrust AI automatically, but to verify it continuously and separately from the human who initiated the task. That reduces false confidence without blocking useful automation.
👉 Read our full editorial: AI trust now depends on continuous verification, not default trust
This post was modified 10 hours ago by NHI Mgmt Group