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Shadow AI Detection and Governance for Enterprises

Employees adopt AI tools the moment they're useful, long before security review. The result is shadow AI: confidential data in consumer chatbots, unapproved models wired into workflows, browser extensions with broad permissions, and AI spend scattered across personal cards and team budgets. Trussed AI gives enterprises visibility into unsanctioned AI activity and, more importantly, a path to govern it: detect, apply policy at runtime, and convert shadow usage into sanctioned, audited usage.

What is shadow AI?

Shadow AI is the use of AI tools, models, and agents inside an organization without IT, security, or compliance approval, consumer chatbots used with company data, unapproved API integrations, embedded AI features in SaaS tools, and self-deployed models. It creates blind spots in data protection, compliance, and cost that grow with every new tool.

Why shadow AI is more dangerous than shadow IT

Data leaves instantly: one pasted document can put confidential data into a model's context, or its training set
No audit trail: when regulators or counsel ask what data went where, there is no record
Agentic spread: unsanctioned agents act, calling APIs and touching systems, not just storing files
Invisible spend: AI costs fragment across teams with no attribution or control
Compliance exposure: HIPAA, GDPR, and contractual obligations are violated silently

How Trussed AI detects and governs shadow AI

AI Control Plane, centralize oversight of AI apps, agents, and developer tools with runtime policy enforcement, usage visibility, and deployment options that fit enterprise security architecture.
Runtime Integrations, proxy-based deployment, SDKs, and APIs route AI traffic through governance, surfacing usage that was previously invisible.
Agentic Governance, authorize tool calls, data access, and workflow triggers in real time across multi-agent and connected environments.
Audit Assurance, every governed interaction produces traces, policy records, timestamps, and lineage, turning a blind spot into an evidence base.
Cost Governance, attribute spend by team, workflow, and provider; enforce budgets and thresholds on newly discovered usage.
AI Governance Advisory, design an approval pathway so discovered tools can be sanctioned quickly, governance that says "yes, safely" instead of only "no."

Why enterprises choose Trussed AI

Blocking shadow AI outright just drives it deeper underground. Trussed's approach is detection plus a fast path to sanctioned use: route discovered tools through the control plane, apply policy, restore auditability, keeping the productivity employees already found while eliminating the risk.

Frequently Asked Questions

How does Trussed discover AI usage we don't know about? By governing the paths AI traffic takes, network proxy deployment, gateway integration, and developer tooling, usage becomes visible and policy-evaluable, including tools never formally approved.

Should we block shadow AI tools once found? Sometimes, but usually the better move is converting them: apply runtime policy, add audit logging, and sanction the tool. Pure blocking recreates the incentive to evade.

Does this cover AI features embedded inside SaaS apps? Yes. Embedded AI features in approved SaaS tools are a major shadow AI vector and can be brought under the same policy and visibility framework.

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