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Know what AI is running in your environment
Your organization is adopting AI faster than it can inventory, validate, or govern it. This assessment gives you a documented baseline of every AI tool, agent, and integration in use: who is using them, what they can access, and where the real exposure is.
Measured against your own policy, not a generic benchmark.
Leadership is being asked AI questions it cannot yet answer
AI adoption inside most organizations is already ahead of policy. Tools arrive through browsers, plugins, integrations, and individual accounts long before anyone builds an inventory. Until that inventory exists, any AI policy is guesswork.
Common questions organizations cannot answer:
Which AI tools, platforms, and agents are in use, and by whom
What systems and data those tools and agents can reach
Whether Shadow AI is spreading, and how fast
Whether Copilot or ChatGPT Enterprise rollouts have widened access beyond what was intended
Whether you could defend your AI oversight to a regulator, auditor, insurer, or customer
Shadow AI is measured, not guessed.
What the assessment covers
Five areas of analysis, delivered by SecurIT360 analysts. Automated collection provides the telemetry; analysts provide the interpretation.
01 AI service & usage discovery
Inventory the AI platforms and tools in use, attribute adoption to individual users, and identify Shadow AI. Each service is classified against your own policy.
02 Agent, integration & MCP review
Identify deployed AI agents, MCP servers, plugins, and browser extensions, including how each one retrieves data and invokes actions.
03 Permission & access analysis
Map identity, role, token, API, and connected-app exposure, surfacing excessive privilege and weak control boundaries around high-privilege accounts.
04 Sensitive data exposure review
Determine where AI workflows can reach confidential, regulated, or business-critical systems. High-risk pathways are flagged with recommended controls.
05 Findings & remediation roadmap
Severity-ranked findings, an executive summary, and a prioritized path your teams can actually execute.
How the engagement works
Fixed fee and fixed scope, delivered by SecurIT360 analysts in five phases. Collection is read-only, with nothing blocked or enforced.
1 · Governance intent
We capture your intended policy posture: what is sanctioned, what is prohibited, and how sensitive data should be handled.
2 · Deployment & collection
Read-only collection deploys at a network choke point or on endpoints, whichever fits your environment.
3 · Discovery & analysis
Telemetry is consolidated, de-duplicated, and classified, activity is correlated to users, and analysts review what automated collection cannot see.
4 · Findings & gap analysis
Observed activity is compared against your governance intent to separate sanctioned use, Shadow AI, and material risk exposures.
5 · Baseline & transition
The completed assessment becomes your AI usage baseline, with a recommended re-measurement cadence.
Engagement tiers
Each tier is additive. Begin at a baseline and extend the engagement as your AI governance matures. Tier 3 moves you from a point-in-time assessment to continuous measurement.
Tier 1 · Discovery / baseline
Which AI agents, services, and MCP servers exist, which employees use them, and what those services access.
Tier 2 · AI user / data risk
Everything in Tier 1, plus interview-led review of agent permissions and sensitive data exposure.
Tier 3 · Recurring AI risk analysis
Everything in Tier 2, plus ongoing monitoring and alerting to measure Shadow AI growth against the baseline, delivered with recurring SOC monitoring.
What you receive
Every engagement produces the same core set of deliverables:
AI service and usage inventory, with user-level adoption mapping and Shadow AI classified against your policy
Agent, integration, and MCP inventory, including what each one retrieves and what it can invoke
Permission and access findings across identity, role, token, API, and connected apps, prioritized around high-privilege accounts
Sensitive data exposure review of high-risk pathways between AI workflows and regulated systems, with recommended controls
Executive summary and findings ranked by severity, written for leadership and the board
Remediation roadmap of prioritized next actions your teams can execute
Your AI usage baseline, a documented point-in-time reference with a recommended re-measurement cadence
Built by analysts, not a scanner with an AI label
Automated collection can tell you which domains were reached. It cannot tell you whether an agent’s permissions are appropriate, whether a workflow puts regulated data within reach, or whether a given tool is sanctioned under your policy. Those judgments require analysts.
We deliver this assessment the way we deliver the rest of our advisory work: read-only collection, human analysis, findings tied to your environment and your policy, and recommendations your teams can execute without added complexity.
Typical sponsors are CIOs, CISOs, CTOs, and senior IT leaders.
Frequently asked questions
Will this disrupt users or block AI tools?
No. Collection is read-only, with no blocking or enforcement at any point in the engagement. The assessment measures what is happening; enforcement decisions come afterward, informed by what we find.
What if we do not have an AI policy yet?
That is common, and it is not a blocker. The first phase captures your intended posture: what you would sanction, what you would prohibit, and how sensitive data should be handled. That intent becomes the standard your observed activity is measured against.
How long does the assessment take?
Scope and duration are fixed at the start of the engagement and confirmed before work begins. Timelines vary with environment size and the tier selected.
How does this relate to our existing security assessment?
A traditional security assessment evaluates your broader control environment. This engagement focuses specifically on AI services, agents, integrations, and the access they inherit. Most assessment frameworks do not yet cover that area in depth.