AI Exposure Assessment

See the AI your organization can’t.

Identify sanctioned and unsanctioned AI usage, understand where sensitive data may be exposed, and uncover the governance gaps creating enterprise risk.

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Discover shadow AIFind tools and usage outside approved channels.
Classify exposureSeparate material risk from background noise.
Clarify ownershipConnect AI use to accountable business owners.
Prioritize actionTurn findings into a practical remediation path.

The Customer Problem

AI adoption is moving faster than enterprise visibility.

Employees are adopting AI applications, browser extensions, copilots and embedded SaaS features across the organization. Without a reliable inventory, security and governance teams cannot determine what data is moving, who owns each use case, or which applications require immediate attention.

01

Unknown usage

Approved platforms provide only a partial view while unsanctioned tools, extensions and embedded AI remain outside normal oversight.

02

Sensitive-data exposure

Business data may enter prompts, files, knowledge stores, integrations and external AI services without appropriate controls.

03

Governance gaps

Unclear ownership, approval status, risk classification and policy coverage make effective oversight difficult.

What RedSkope Assesses

Build a defensible view of enterprise AI exposure.

The assessment combines discovery, stakeholder evidence and risk analysis to show what AI is present, how it is being used and where intervention is required.

  • Shadow AI discoveryUnsanctioned GenAI applications, SaaS AI tools and usage patterns.
  • Enterprise AI inventoryApproved platforms, copilots, agents, use cases and accountable owners.
  • Browser AI extensionsAI-enabled extensions, permissions and potential data-access concerns.
  • AI agents and integrationsConnected tools, APIs, enterprise workflows and delegated authority.
  • Sensitive-data exposurePotential movement of confidential, personal or regulated information.
  • Approval and ownershipBusiness sponsorship, intended purpose, approval status and accountability.
  • AI risk classificationRisk-ranked applications and use cases based on exposure and business impact.
  • Governance coveragePolicy, monitoring, vendor oversight, exception and reporting gaps.

Engagement Workflow

Structured discovery. Risk-ranked results.

Each engagement follows a repeatable path from scope definition to executive reporting.

01 / SCOPE

Define the environment

Confirm business units, systems, evidence sources, stakeholders and assessment boundaries.

02 / DISCOVER

Identify AI usage

Collect evidence of sanctioned and unsanctioned applications, extensions, agents and integrations.

03 / CLASSIFY

Organize the inventory

Connect tools to owners, purposes, data types, approval status and business processes.

04 / ASSESS

Evaluate exposure

Assess sensitive-data handling, permissions, vendor characteristics and governance coverage.

05 / PRIORITIZE

Rank the risk

Identify the applications, exposures and governance gaps requiring the earliest action.

06 / REPORT

Present the path forward

Deliver clear findings, leadership decisions and a sequenced remediation roadmap.

Deliverables

Visibility your teams can turn into action.

Outputs are designed for both executive decision-making and practical remediation ownership.

  • 01
    Enterprise and shadow AI inventoryKnown tools, unsanctioned applications, owners, business purposes and approval status.
  • 02
    Risk-ranked exposure findingsPrioritized applications, sensitive-data concerns, integrations and material risk scenarios.
  • 03
    Governance gap assessmentGaps across ownership, policy, classification, approval, monitoring and oversight.
  • 04
    Executive summary and remediation roadmapLeadership narrative, immediate actions and a sequenced plan for reducing exposure.

Who It Is For

Organizations that need to understand AI before they can govern it.

A strong starting engagement when leaders know AI adoption is accelerating but cannot yet answer what is being used, where data is going, or which risks matter most.

CISOs and security teamsCIOs and technology leadersPrivacy leadersAI governance teamsEnterprise riskInternal auditProcurementBusiness application owners

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Turn point-in-time discovery into ongoing visibility.

Scout supports AI Exposure Assessments by identifying AI applications, extensions and exposure indicators across the enterprise.

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Start With Visibility

See what AI is really being used across your organization.

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