Building the Business Case for AI Code Scanning

The Risk the Business Case Must Quantify

BrassCoders’s benchmark gives the business case a concrete foundation: in controlled testing of 15 AI-generated Python files, BrassCoders caught 11 of 12 AI-generated bug categories — including credential exposure, phantom imports, and privacy/PII patterns that the most widely deployed Python static analysis tool missed.

That number is the starting point. Eleven of twelve categories caught means the tool covers the risk in controlled conditions. Translating coverage into a business case requires one additional step: what does it cost to find a credential exposure bug or an injection bug before it ships, versus after?

The answer to that question doesn’t require industry averages or vendor-provided ROI calculators. It requires an honest description of your organization’s actual remediation steps for a HIGH-severity finding in production.

The Cost Comparison: CI Detection vs Production Discovery

BrassCoders Paid’s per-developer monthly cost gives you the cost side of the comparison — the reference point is what it costs to find the same class of bug in production versus in CI.

A HIGH-severity credential exposure bug caught in CI costs:

• One CI job runtime (under 60 seconds for BrassCoders on a typical Python project)
• A developer reading the finding and removing the hardcoded secret
• A line edit and a new commit

A HIGH-severity credential exposure bug caught after it ships to a production branch costs:

• Developer time to identify and remove the credential
• Rotation of every exposed credential that appeared in the commit history
• Review of access logs to determine whether the credential was used externally before discovery
• Potentially: incident response, breach notification, customer communication

The cost difference is not marginal. The business case writes itself once you describe the actual remediation steps — and those steps are the same regardless of whether the bug was introduced by a developer or an AI assistant.

Building the Comparison From Your Own Data

BrassCoders eliminates the detection cost for the patterns it covers — it runs automatically in CI, flags findings before code ships, and produces .brass/ai_instructions.yaml — a structured finding list that an AI assistant can triage in minutes. The remediation cost remains, but it applies to confirmed real bugs, not to the search for them.

To build a defensible business case from your own codebase:

Step 1 — Run the pilot: install BrassCoders’s OSS core and scan your team’s current AI-generated code. The OSS core is free; the pilot costs nothing but time.

Step 2 — Triage the findings: paste the .brass/ai_instructions.yaml output into Claude Code or Cursor and ask it to triage the findings. Confirmed HIGH and CRITICAL bugs are the business case input.

Step 3 — Estimate remediation cost: for each confirmed HIGH or CRITICAL finding, estimate what remediation would cost if discovered in production instead of in CI. Use your team’s actual hourly rates and your organization’s actual incident response overhead.

Step 4 — Calculate the comparison: one confirmed HIGH-severity production incident, with full remediation costs, almost always exceeds the annual cost of running BrassCoders Paid across the team that shipped it. The comparison is specific to your codebase and your cost structure, not to an industry average.

Making the Case Without Numbers You Can’t Defend

BrassCoders provides the measurement layer that converts “AI code risk” from a concept into something concrete — the finding rate, by severity and category, against your team’s actual code.

Three things the leadership presentation needs to include:

The coverage gap: your current static analysis covers some of the 12 AI-generated bug categories. BrassCoders’s benchmark provides the reference point for how many. The gap between your current coverage and 11 of 12 is the exposure you’re quantifying — not a hypothetical, but a measured gap in your specific toolchain.

The directional cost case: one confirmed HIGH-severity finding that ships to production, with the full remediation and incident response overhead factored in, will cost more than a year of running BrassCoders Paid for the team that shipped it. You don’t need a precise number for this to be true — you need an honest description of your remediation process.

Pilot data from your own codebase: the OSS core scan results from your own code are more persuasive than any benchmark. Show what BrassCoders found in your team’s AI-generated Python, not what it found in a published test corpus. The confirmed findings are the proof.

Install BrassCoders with pip install brasscoders and run brasscoders scan . from your project root. The OSS core is free and Apache 2.0 licensed. BrassCoders Paid adds semantic deduplication for teams where finding volume makes manual triage impractical.