Unapproved tools are in use
Employees are accessing AI services through browsers or desktop applications outside the approved company approach.
Shadow AI Assessment & Controls
Expose shadow AI.
Establish control.
Identify AI activity outside your approved approach, understand the information at risk, and implement practical controls across the managed environment.
When to engage IO
An AI policy needs
operational controls.
For security and IT teams concerned about unmanaged AI use, sensitive information sharing, or gaps in ongoing oversight.
Data sharing is difficult to assess
You need a clearer view of activity and potential exposure in the systems you manage.
Restrictions are inconsistent
You want controls aligned to an approved AI policy, with clear coverage, exceptions, and operating ownership.
What the engagement delivers
Concrete outputs.
A usable next step.
The final scope is agreed around your environment, priorities, and responsibilities.
Discovery and coverage findings
Identify observed AI use and document the systems, telemetry, and visibility limitations in the assessment.
Data exposure review
Evaluate the types of information being shared where the configured evidence and access support that analysis.
Approved-use control design
Define the treatment of approved and unapproved services, relevant exceptions, and responsibilities for operating the controls.
Restrictions and monitoring implementation
Implement the agreed blocking, access restrictions, and monitoring capabilities across supported parts of the managed environment.
Validation and operational handoff
Review the agreed scenarios, document the implemented coverage, and transfer monitoring responsibilities to your team or provider.
Control and monitoring coverage depends on your devices, browsers, services, integrations, and licenses. We define those boundaries explicitly. Ongoing monitoring ownership is agreed during the engagement; a staffed managed monitoring service is not implied.
How we work
A coordinated path
from plan to handoff.
01
Discover the activity
Establish what is observable and identify relevant AI use and exposure in the agreed environment.
02
Define and implement controls
Translate approved-use decisions into the supported restrictions, exceptions, and monitoring configuration.
03
Validate and operationalize
Check the intended behavior and give your team the context to review activity and maintain the controls.
Large enterprise / Ongoing AI oversight
Approved Copilot use.
Visibility into what comes next.
As part of a large enterprise AI engagement, IO implemented blocking and access restrictions for unapproved AI services within the managed environment and established ongoing Shadow AI monitoring alongside the approved Copilot deployment.
Explore the engagementBefore we begin
Good questions.
Clear expectations.
Can you block every AI tool everywhere?
Coverage depends on the systems and controls in scope. We define what can be observed and enforced within your managed environment and document the remaining boundaries.
Will this prevent employees from using our approved AI platform?
The control design is aligned to your approved-use decisions. The aim is to support the permitted environment while addressing unapproved activity, with exceptions agreed before implementation.
Is ongoing monitoring included as a managed service?
This engagement can establish the monitoring capability and operating handoff. Responsibility for reviewing and responding to future activity is agreed explicitly during scoping.
Start with a conversation
Make approved AI use
an operating reality.
Tell us what your policy permits, what activity concerns you, and which environments your team manages.
Discuss Shadow AI controlsPrefer to book directly? Book a consultation.