ROI and cost
AI agent breach cost calculator
Put a defensible number on the risk your AI agents carry. Move the inputs and watch the estimated annual exposure, and what AxioRank could prevent, update live.
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The estimate
Move the inputs. The number is yours.
An AI agent that can call tools and touch production systems is a new path to a breach. This calculator turns your deployment into a transparent, range-based estimate of the annual cost exposure, then shows how much a control plane on the tool boundary could avoid.
Your deployment
Adjust the inputs to match your setup. The estimate updates as you go.
Agents act on production systems
They can write or delete, not just read.
Agents handle customer or personal data
Estimated annual exposure
$2.0M to $6.6M
$3.6M expected, from 0.75 expected agent-attributable incidents a year at $4.8M each.
With AxioRank on the tool boundary
$1.5M to $2.6M
Modeled to reduce expected exposure by 40% to 70% a year. Illustrative, not a guarantee.
What moved this estimate
- 8 agents and 250K monthly callsset the exposure surface (diminishing returns at scale)
- Technology and SaaS+10% per-incident cost
- Regulated (PII, PHI, PCI)baseline per-incident cost
- Agents act on production systems+40% expected frequency
- Agents handle customer or personal data+50% expected frequency
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Every number here is a modeled estimate with its assumptions on the page. It is a starting point for a conversation, not a quote.
Assumptions and sources
Every coefficient, on the page.
The estimate multiplies an expected annual incident frequency, modeled from your own exposure surface, by a per-incident cost drawn from public breach-cost benchmarks. Frequency uses a saturating (log) curve so more scale raises risk with diminishing returns, never linearly. The result is shown as a range because every input is an assumption you can adjust.
Per-incident cost anchor: $4.4M
Public breach-cost studies of the IBM Cost of a Data Breach type put the average breach in the low-to-mid seven figures, with a premium when security automation is absent. We anchor conservatively and report a range.
Industry and sensitivity multipliers
Relative bands reflecting the documented spread in those same studies (healthcare and financial highest; regulated and high-value data above low-sensitivity data). Dimensionless and paraphrased.
Base incident frequency: 0.12 per year, scaled by exposure
Modeled from your fleet size, call volume, and access, not a measured industry rate. Production write access and customer-data handling raise expected frequency.
Mitigation band: 40% to 70%
AxioRank scores every tool call before it runs, so it reduces expected frequency rather than erasing cost. The band is illustrative, not a guarantee.
FAQ
Questions about the model.
How is this calculated?
Estimated annual exposure is an expected incident frequency multiplied by a per-incident cost. Frequency is modeled from your fleet size, monthly call volume, and whether agents touch production or customer data, on a saturating curve. Per-incident cost starts from a public breach-cost anchor and is adjusted by industry and data sensitivity. The output is a low, expected, and high range.
Where do the numbers come from?
The per-incident anchor and the industry and sensitivity spreads are paraphrased from public breach-cost research of the IBM Cost of a Data Breach type. The incident frequency is modeled from your own inputs, not from a vendor incident-rate claim. Every coefficient is listed in the assumptions section above.
Is this a guarantee of cost or savings?
No. It is an estimate to frame the size of the risk, not a quote, an audit, or a guarantee. AxioRank's modeled mitigation is shown as a range and reduces expected incident frequency by catching risky tool calls before they run.
How does AxioRank reduce this exposure?
AxioRank scores every tool call on the hot path for leaked secrets, PII, destructive operations, and prompt injection, checks it against your policy, and records it in a tamper-evident audit log. Catching a prompt-injected or mistaken action at the tool boundary is what lowers the expected frequency in this model.
Keep exploring
From estimate to enforcement.
Govern your agents, not just estimate the risk
AxioRank scores every tool call your agents make for leaked secrets, PII, destructive operations, and prompt injection, then proves it in a tamper-evident audit log. Start free, no card.