Physical Security AI ROI Calculator & Payback Planner

Sample scenario · replace with measured data

Build the operating case

Use ordinary workload and cost figures. Do not enter incident details, employee information, system locations, vulnerabilities, or vendor-confidential pricing.

Runs in this browser Inputs are not transmitted Assumptions remain visible

Alerts handled per month Use the same alert class and a representative period. Current minutes per alert Include verification and documentation time consistently. Alerts suitable for assistance (%) Exclude events that policy requires staff to handle without AI assistance. Expected time reduction (%) Use observed pilot performance, not a vendor maximum. Loaded labor cost per hour (USD) Use an approved finance or HR assumption. Annual service cost (USD) Include recurring licenses, support, hosting, and required maintenance. One-time implementation cost (USD) Include integration, configuration, testing, training, and change management.

Calculating the sample scenario…

This is a planning scenario, not financial advice or a savings guarantee. Labor-capacity value becomes cash savings only when the organization can actually avoid cost, reduce spend, or redeploy capacity to measured work.

Transparent formula register

How the scenario is calculated

Modeled annual hours saved

alerts/month × 12 × addressable share × minutes/alert ÷ 60 × time reduction

Gross capacity value

modeled hours saved × loaded hourly labor cost

First-year ROI

(gross capacity value − annual service − implementation) ÷ (annual service + implementation)

Simple payback

implementation cost ÷ (gross monthly capacity value − monthly recurring service cost)

Run a defensible sensitivity check

Calculate a conservative case using the lowest observed addressable share.
Change only the time-reduction assumption and record the result.
Restore that value, then change only the loaded labor cost.
Compare which single assumption changes the decision and document its evidence.
Replace every estimate with 30- to 90-day pilot observations before approval.

This approach aligns with GAO guidance to document assumptions and vary one factor at a time, and with NIST guidance to select context-appropriate AI measures and monitor performance over time.

GAO Cost Estimating and Assessment Guide
NIST AI RMF Measure playbook
Portal methodology and limitations

Next action

Turn the scenario into a controlled pilot

Define the alert class, baseline period, inclusion rules, and human-review requirement.
Measure false positives, false negatives, handling time, escalations, and operator overrides.
Test degraded operation and document what happens when the model or integration is unavailable.
Ask finance to approve the labor-cost assumption and procurement to validate full lifecycle cost.
Approve expansion only when observed benefits and safety measures remain inside agreed limits.

Run the readiness check Build a procurement shortlist