Mastering Shadow AI: See, Govern, and Secure Your Organization

Artificial intelligence adoption is moving faster than most organization’s governance programs.

Employees are using ChatGPT, Claude, Gemini, Microsoft Copilot, and other AI applications to research topics, summarize documents, analyze information, write code, and complete everyday business tasks. At the same time, organizations are developing AI-powered applications and autonomous agents that can access data, invoke tools, interact with business systems, and perform actions with limited human involvement.

These technologies offer tremendous opportunities—but they also create a new category of security, privacy, compliance, and operational risk.

The problem is that many organizations cannot answer some fundamental questions:

• Which AI applications are being used by employees?
• Are employees using approved enterprise accounts or personal accounts?
• What sensitive information may be shared with these services?
• Which AI agents are operating within the environment?
• Who owns each AI system?
• What applications, data, credentials, and tools can an agent access?
• Are appropriate safeguards in place before an agent is deployed into production?

Cyberator’s new AI Governance Module helps organizations answer these questions by bringing AI application discovery and AI agent governance together in one centralized platform.

Discover AI Usage Across the Organization

Employees often begin using AI applications before security, privacy, or compliance teams have had an opportunity to evaluate them. This creates “shadow AI”—the use of AI tools that have not been formally reviewed or approved.

Cyberator’s AI Application Discovery capability helps organizations identify the AI services being used across their environment, including applications such as ChatGPT, Claude, Gemini, Microsoft Copilot, and other browser-based or SaaS AI tools.

Depending on the organization’s available integrations and privacy requirements, Cyberator can use authorized information from identity systems, SaaS administration platforms, secure web gateways, CASB or SSE solutions, DNS and proxy logs, managed endpoints, and browser telemetry.

Discovered AI applications can be classified as:

• Approved
• Restricted
• Under Review
• Unapproved
• Prohibited
• Unknown

Cyberator also records when the application was first and last observed, how frequently it is being accessed, the source of the observation, and the level of confidence in the result.

The objective is not to monitor employee conversations or collect AI prompts and responses. The objective is to give security and governance teams enough visibility to identify potential exposure and determine whether an application requires review.

Turn Shadow AI Into a Governed Process

Discovering an AI application is only the beginning. Organizations also need a consistent process for deciding what should happen next.

When Cyberator identifies a new or unapproved AI service, the organization can initiate a structured review that considers:

• The business purpose for using the application
• The type of information employees may share with it
• Whether enterprise licensing and contractual protections are available
• The provider’s data retention and model-training practices
• Authentication and account-management controls
• Available administrative and audit capabilities
• Regulatory and contractual requirements
• The number of users and business units involved
• The potential impact of unauthorized use

Based on the review, the organization can approve the application, approve it with restrictions, prohibit its use, require employees to migrate to an enterprise-managed version, or grant a time-limited risk exception.

Cyberator tracks the decision, accountable owner, required remediation, supporting evidence, approval history, and future review date.

This transforms shadow AI from an informal security concern into a measurable and auditable governance process.

Govern AI Agents Before They Act

Browser-based AI applications represent only one part of the risk. AI agents introduce additional concerns because they can move beyond producing information and begin taking actions.

An AI agent may be able to:

• Access internal databases and documents
• Call external APIs
• Read or modify files
• Execute code
• Send emails or messages
• Interact with cloud services
• Use stored credentials
• Communicate with other agents
• Trigger business workflows
• Consume significant API or computing resources

Cyberator’s AI Agent Governance capability creates a centralized inventory of these systems and documents their purpose, ownership, deployment environment, data sensitivity, integrations, permissions, tools, and degree of autonomy.

Each AI agent can be assessed across critical governance and security areas, including:

• Business and technical ownership
• Operator identity and command authorization
• Network exposure and outbound connectivity
• Tool and plugin permissions
• Code-execution and file-access capabilities
• Credential and secret protection
• Logging and monitoring
• Cost and usage guardrails
• Human approvals and intervention points
• Evidence collection and control testing
• Periodic recertification

Organizations can use the assessment results to determine whether an agent is ready for testing, staging, or production.

A high overall score does not hide a critical weakness. If an agent has unrestricted tool access, exposed credentials, unverified operators, or uncontrolled outbound connectivity, Cyberator highlights the condition separately and can prevent production approval until it is addressed or formally accepted by an authorized risk owner.

Maintain Continuous Visibility After Approval

AI governance cannot end when an application or agent is approved.

Configurations change. New tools are added. Permissions expand. Owners leave the organization. Evidence becomes outdated. Monitoring stops working. Employees begin using new AI services.

Cyberator supports continuous governance by tracking:

• Newly discovered AI applications
• Continued use of prohibited or unapproved tools
• Changes to AI-agent configurations and permissions
• Control failures and configuration drift
• Expired evidence
• Overdue remediation
• Expiring risk exceptions
• Connector failures
• Missing ownership
• Upcoming and overdue recertifications

When a material change occurs, Cyberator can create a finding, assign remediation, notify the responsible parties, and initiate reassessment.

This gives leadership a current view of AI risk rather than a static snapshot from the last annual review.

One View of Enterprise AI Risk

The AI Governance Module connects AI discovery, risk assessment, evidence, remediation, exceptions, approvals, and continuous monitoring within the broader Cyberator platform.

Security and governance leaders can see:

• Which AI applications are being used
• Which applications are approved or unapproved
• Where shadow AI is creating exposure
• Which AI agents are operating in production
• Who owns each application and agent
• Which systems have critical security gaps
• Which remediation activities are overdue
• Which approvals or exceptions are expiring
• Whether the organization’s AI risk is improving or deteriorating

This information can also support executive reporting and Cyberator’s AI-powered CISO Briefing, helping leadership focus on the AI risks that require immediate attention.

Move From Uncontrolled AI Adoption to Responsible AI Governance

Organizations should not have to choose between enabling AI innovation and maintaining security and control.

Cyberator helps organizations discover how AI is being used, evaluate the associated risk, establish clear ownership, approve appropriate use cases, secure AI agents, and continuously monitor the controls that matter.

The result is a practical and auditable AI governance program that enables organizations to adopt AI with greater confidence.

Ready to discover and govern AI across your organization? Contact Cyberator to schedule a demonstration of the AI Governance Module.