inforedge

Shadow AI Assessment

Shadow AI Assessment:
See Unmanaged AI and Prioritize Your Response

Inforedge helps organizations identify unmanaged AI usage, understand observable exposure and build an actionable remediation path.

For IT, security, privacy and business leaders seeking a scoped evidence-based assessment.

  • Create a scoped AI inventory
  • Prioritize material risk
  • Define the next actions

Start an AI Exposure Discussion

From scattered signals to action.
01DiscoverApproved inventories, telemetry and interviews
02QualifySources, confidence and visibility gaps
03PrioritizeOwnership, sensitivity and business impact
04ActApproved alternatives and remediation roadmap
Coverage boundary: telemetry · permissions · integrations · agreed scope

Illustrative discovery framework. Actual visibility depends on available sources; access signals do not prove data disclosure.

Assessment first. Delivery shaped around an agreed scope.Explore the service ↓Assessment options ↓
Where organizations struggle

AI use is spreading.
Your inventory may not show it.

01

Unknown tools & features

Unapproved assistants, embedded SaaS AI and agents bypass normal intake.

02

Unclear data exposure

Tool access signals do not explain what information was shared.

03

Blind spots without a plan

Missing logs, personal accounts and incomplete ownership complicate decisions.

Shadow AI Assessment

What Inforedge helps improve.

Discovery establishes evidence. Remediation follows only with approved scope.

01 / CAPABILITY

Authorize & scope discovery

Agree business units, sources, time period, permissions and privacy boundaries.

02 / CAPABILITY

Build an evidence-based inventory

Combine permitted telemetry, procurement, identity records and stakeholder interviews.

03 / CAPABILITY

Classify exposure & confidence

Distinguish confirmed use, indications and unverified reports; assess ownership and potential impact.

04 / CAPABILITY

Prioritize remediation

Recommend approved alternatives, intake changes and a sequenced action backlog.

Specific products, integrations and implementation depend on validated capability, customer entitlements and the agreed engagement scope.

How the engagement progresses

Evidence before enforcement.

01

Authorize

Agree purpose, source access and data-handling boundaries.

02

Discover

Gather approved signals and interview evidence.

03

Review

Validate findings, risk priorities and coverage limits.

04

Plan

Assign owners and sequence customer-approved actions.

Inforedge AI Exposure Delivery Pod

Senior-led expertise.
Shared delivery accountability.

An optional team can maintain a discovery and remediation backlog across approved sources, with senior-led risk review and built-in delivery management.

Built-in delivery managementFlexible capacitySpecialists as needed

A prioritized backlog, decision cadence and risk register keep progress reviewable. Handover and sustainable ownership are part of the agreed plan.

Illustrative team · tailored to the engagement

Delivery Manager / LeadCadence · risks · decisions · acceptance
Discovery / Risk LeadEvidence quality & prioritization
Telemetry SpecialistApproved sources & coverage
Optional specialists
Identity · Endpoint · Network · Privacy · Data

Composition and capacity are agreed per engagement; no fixed staffing commitment is implied.

01 / ESTABLISHAssessment & Advisory
02 / DELIVERImplementation
03 / EVOLVEEnhancement
04 / SUSTAINManaged Services

One engagement option, with separately scoped stages. Ongoing coverage, responsibilities and exit/handover terms must be agreed before transition.

What the customer receives

Concrete outputs.
Matched to the contracted phase.

01

Scoped AI inventory

Evidence source, owner and confidence.

02

Coverage statement

Reviewed sources, period and blind spots.

03

Risk-ranked findings

Potential exposure and review rationale.

04

Executive briefing

Priority decisions and ownership gaps.

05

Remediation roadmap

Approved alternatives and action owners.

06

Inventory maintenance template

Update and exception-review process.

Who this is for

Bring the right decision owners.

IT leadershipSecurity / PrivacyProcurementData ownersBusiness-unit leaders
A practical starting point

Start with an assessment.

Agree the business question, evidence boundary and expected outputs before committing to broader delivery.

PRIMARY ENTRY POINT

Inforedge Shadow AI & AI Exposure Assessment

A defined discovery boundary, risk-ranked findings and a remediation roadmap. Visibility depends on approved telemetry, permissions, integrations and scope.

RELATED SERVICE OPTION

Inforedge AI Exposure Executive Assessment

A leadership-focused review of observable exposure and material decisions. It does not replace technical discovery or prove sensitive-data disclosure.

Relevant Inforedge perspectives

Thinking that informs the work.

INFOREDGE INSIGHT

Shadow AI Is Already in Your Enterprise

A perspective on visibility, exposure and governance.

Explore the perspective ↗

CAPABILITY HUB

AI & Data

The broader context for responsible AI adoption.

Explore the perspective ↗

Editorial perspectives provide context; they are not evidence of a specific customer implementation or achieved result.

Engagement essentials

The detail,
when you need it.

Scope, prerequisites and responsibilities before you commit.

Can the assessment find every AI interaction?

No. Personal devices, personal accounts, encrypted traffic, offline tools, embedded features and unavailable logs create blind spots. The report states sources, scope, time period and confidence.

Does tool access prove sensitive data was submitted?

No. A usage or access signal is an indication for review, not automatic evidence of sensitive-data disclosure. Findings distinguish evidence from inference.

Do we need new agents or tooling?

Not necessarily. Begin with available approved exports and records. New tooling, endpoint agents or expanded permissions require separate scope and authorization.

Will discovery block employee access?

No. Recommendations and enforcement are separate. Any control change needs customer authorization, testing and communication; covert employee surveillance is excluded.

How is Shadow AI assessment different from readiness?

Shadow AI focuses on current unmanaged use and observable exposure. Readiness evaluates the business, data, controls and operating support needed for a future AI use case.

What happens after the assessment?

Customer owners review findings and approve the backlog. Remediation, refreshed discovery or ongoing governance can follow under separately agreed scope; continuous monitoring is not automatically included.

Your next step

Turn AI visibility gaps into a practical action plan.

Discuss your priorities, current environment and decision owners. Define the right first engagement together.

Start an AI Exposure Discussion