Guide
• 20 pages
Full autonomy, with full governance
An enterprise guide to agentic AI governance: how to assess security, compliance, cost, and sprawl risks, plus four tactics from production deployments.
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1B+ tasks automated · 333K+ agents deployed
Guide
How enterprises control agentic AI in 2026
AI agents make decisions, take autonomous action, and interface directly with mission-critical systems of record, but old AI governance playbooks were never designed to control systems that act on their own. This guide covers the eight risks to assess before deploying agentic AI, a governance worksheet for your team, and four control tactics that work in production.
What you'll learn
- The eight risk categories to assess before deployment, from security and compliance to cost and sprawl, each with specific mitigations
- What the EU AI Act's Article 12 logging requirements mean for your audit and evidence layer
- The scope, boundary, and responsibility questions to align on with your team before building your first agent
- How VPC deployment and open-weight models reduce data exposure while bending your cost curve down
Gumloop, 2026.
93%
of enterprise agents run without a human prompt.
Gartner, 2026.
150k
the estimated number of agents per average Fortune 500 company by 2028.
Gumloop, 2026.
56%
of agents in enterprise deployments are built by GTM functions.
The multiplayer AI agent builder, with IT in control
Anyone at your company can build agents with any AI model and any integration. IT keeps SSO, audit logs, and access control from day one, so one security review covers every team.
- Any model: frontier where quality matters, open weight where cost does
- Every integration your teams already use, with scoped credentials
- SOC 2 Type II, GDPR, and VPC deployment in your own cloud
Enterprise-grade controls
Usage monitoring
Track organization-wide credit usage in real time. Implement budget and quota controls to avoid surprises.
Audit logging
Capture detailed audit trails for actions across the organization to understand where data is flowing.
VPC deployments
Deploy Gumloop inside your own AWS, Azure, or Google Cloud environment to keep data in your network.
Roles and permissions. Manage reusable roles, credentials, and secrets with scoped access.
SAML SSO and SCIM. Securely streamline identity and access management.
AI model restrictions. Control which AI models teams can use.
SOC 2 Type II. Independently audited and compliant.
GDPR. Zero Data Retention agreements for third-party models.
Credential management. Store secrets in one place and scope who can use them.
App policies and guardrails. Write plain English rules that block, tag, or log actions before they run.
MCP client and server tracking. Trace every tool call through one logging and analytics layer.
Reporting and analytics. See AI adoption, usage, and outcomes for every team in one place.
Spend caps and approvals. Cap spend by agent, team, or org, and approve costly actions.
Want to see Gumloop do this for your team?
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