Free Risk Assessment Tool

Shadow AI Risk Calculator

47% of employees use personal AI accounts for work. Estimate how much sensitive data is leaving your organization and calculate the real financial exposure in under 30 seconds.

47% Employees using personal AI Netskope 2025 Report
22% Uploads contain sensitive data Harmonic Security 2025
$670K Added breach cost via Shadow AI IBM Cost of a Breach 2025
247 Days to detect Shadow AI data leak IBM Cost of a Breach 2025

Your Organization

Full-time employees with access to computers
Includes "summarize this," contract reviews, report analysis. Range: 1 - 10,000
Manual text inputs to AI tools containing work context. Range: 1 - 5,000
Used to estimate maximum regulatory fine exposure (GDPR/EU AI Act: up to 4%)
Sector-specific risk multiplier based on data sensitivity

Your Risk Profile

Enter your organization details and hit calculate to see your risk profile.

Sensitive Assets Exfiltrated / Year
--
Documents and prompts containing sensitive data leaving your perimeter annually
Estimated Annual Financial Risk
--
Expected annual loss: breach probability × estimated breach cost (IBM 2025)
Maximum Regulatory Fine Exposure
--
GDPR / EU AI Act maximum penalty (4% of annual revenue)
Total Maximum Exposure
--
Combined expected breach cost + regulatory fine ceiling
Average Detection Gap
247 Days
Average time before organizations discover Shadow AI-related data leaks
Breakdown
Shadow AI users (47%) --
Sensitive docs/month --
Sensitive prompts/month --
Breach probability --
Est. breach cost (if occurs) --
Industry multiplier --
Cost per record (IBM 2025) $159
Shadow AI breach penalty $670,000

EPH4 eliminates Shadow AI risk with on-premise ephemeral AI workspaces. No data ever leaves your building.

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How This Calculator Works

Formula A: Monthly Sensitive Data Points

We calculate the number of sensitive data units leaving your organization each month:

Exposures = (Employees x 0.47) x [(Docs x 0.22) + (Prompts x 0.042)]

Only the 47% of employees using unauthorized AI are counted. Document uploads are weighted at 22% sensitivity, manual prompts at 4.2%.

Formula B: Breach Cost If Occurs (IBM-Bounded)

We estimate the cost of a Shadow AI-driven breach using IBM per-record costs, bounded by the IBM study's actual data range (2,960 – 113,620 records):

Capped Records = min(Annual Exposures, 113,620)

Breach Cost = min((Capped Records x $159) + $670K, $10.22M x Industry Multiplier)

$159 is the weighted average cost per leaked record (IBM 2025). $670K is the added breach cost for Shadow AI. The $10.22M cap is the highest average breach cost observed in the IBM 2025 study (United States). Per-record costs are not extrapolated beyond the study's range, consistent with IBM's own methodology guidance.

Formula C: Breach Probability

The annual probability of a Shadow AI-related breach, based on exposure intensity per user:

Probability = 5% + (min(Exposure Per User / 500, 1) x 20%)

Range: 5% (minimal exposure) to 25% (heavy exposure). IBM 2025 found 20% of breached organizations suffered a Shadow AI incident, informing this range.

Formula D: Expected Annual Financial Risk

The probability-weighted expected annual loss from a Shadow AI breach, capped at annual revenue (a company's expected breach loss cannot exceed its revenue):

Annual Risk = min(Breach Probability x Breach Cost (If Occurs), Annual Revenue)

Formula E: Total Exposure (Including Fines)

EU AI Act and GDPR impose fines up to 4% of global annual revenue:

Total Exposure = Annual Risk + (Revenue x 0.04)

Industry Multipliers

Risk is adjusted by sector to reflect data sensitivity and regulatory burden:

Data Sources

Don't Let Shadow AI Define Your Risk Profile

EPH4 secure Workpsace creates access keys for full data privacy. Documents are analyzed on-premise, in ephemeral workspaces that vanish after processing. Zero data exposure. Zero AI model training

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