Benchmark Risk Snapshot
See your AI risk exposure in under a minute
Estimate benchmark exposure using EU AI Act statutory maximums and IBM breach-cost benchmarks. This is an orientation tool for security and operations teams, not legal advice.
Live benchmark
EUR 10M · 51–250 · Informal use
Total benchmark exposure
€871,725
EUR/USD conversion rate: 0.92
Estimated EU AI Act exposure
€525,000
Estimated Shadow AI breach uplift
$376,875
Benchmark inputs
Risk context from statutory and breach-cost benchmarks
EU AI Act reference
Uses statutory maximum orientation up to EUR 35M or 7% of global turnover.
Breach-cost benchmark
Uses IBM 2024 breach-cost research as a directional exposure baseline.
Decision support
Designed to frame governance conversations, not replace legal or compliance advice.
Calculator
Set your exposure profile
Adjust three inputs. Results update in real time.
Exposure profile
Move from rough assumptions to a board-ready benchmark in three inputs.
We apply the selected revenue tier to EU AI Act statutory maximum fine benchmarks.
Company size
Used to scale breach-cost benchmark exposure by operating footprint.
AI governance maturity
What to do with the number
Turn the snapshot into a control plan
Identify the exposure drivers
Use the split between statutory exposure and breach uplift to see where governance maturity changes the risk profile.
Scope runtime controls
Map the benchmark to policies, prompt controls, approval gates, and audit evidence across your AI surfaces.
Prepare the rollout
Use the result to prioritize which teams, tools, and data categories should move into governed AI usage first.
Methodology
How we calculate this
EU AI Act exposure. We estimate exposure by applying the selected revenue tier to the 7% turnover threshold and capping at EUR 35 million, then weighting by governance maturity. This is a benchmark orientation model, not a legal determination.
Shadow AI breach uplift. We apply company-size and governance multipliers to IBM's 2024 benchmark data and present the resulting uplift as a directional risk estimate.
The AI risk exposure figures shown are benchmark-based estimates for orientation purposes only. EU AI Act fine ranges are statutory maximums under Regulation (EU) 2024/1689 and do not represent expected or average penalties. Breach-cost benchmarks are sourced from the IBM Cost of a Data Breach Report 2024. Results are not legal advice, compliance assessments, or guarantees of any outcome. Consult qualified legal and compliance counsel for advice specific to your organization.
Common questions
Understanding your risk numbers
Understanding your risk numbers
Common questions
It combines your revenue band, company size and AI governance maturity with the EU AI Act fine framework and published breach-cost benchmarks. The result is a benchmark exposure range you can use to prioritise governance work — not a quote and not a forecast.
No. Actual penalties depend on the specific violation, the authority, cooperation and many case-specific factors. The calculator is an orientation tool for security and operations teams, not legal advice.
The EU AI Act sets administrative fines of up to EUR 35 million or 7% of global annual turnover, whichever is higher. We apply the 7% threshold to your selected revenue band, cap it at EUR 35 million and weight it by your governance maturity.
From published breach-cost research such as IBM's Cost of a Data Breach report, which quantifies the additional cost when unmanaged AI is involved in an incident. We scale that benchmark by company size and governance maturity.
No. The calculator runs entirely in your browser. Your selections are reflected in the URL so you can share a scenario deliberately, but nothing is submitted to or stored on our servers.
Visibility, enforced policies and audit-ready documentation. Moving from no policy to managed AI governance is the biggest lever in the model — and exactly what Qadar AI Shield operationalises: discover AI usage, enforce guardrails and document controls.
From benchmark exposure to a scoped AI governance rollout
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