AI ROI Calculator: How to Measure AI ROI
AI ROI = (annual hours saved x loaded hourly rate − annual run cost) ÷ build cost. From 5 production builds: a single-workflow AI build costs $10K-$25K, runs $200-$1,800/month in model spend, and pays back in 2-6 months when it removes 60-80% of a repetitive queue.
This page gives you the formula, a worked example, and a value matrix for ranking AI use cases — then two free tools that run the math for your numbers. No signup.
How to measure AI ROI: the formula
Three numbers decide whether an AI project is worth building: value created, cost to build, cost to run. Everything below comes from measured data across 5 production AI builds, shipped in 2-8 weeks each.
annual value = hours saved/week x 52 x loaded hourly rate (+ error cost avoided)
annual cost = build cost + (run cost/month x 12)
ROI % = (annual value − annual cost) ÷ annual cost x 100
payback (months) = build cost ÷ (monthly value − monthly run cost)
Where each number comes from
| Variable | How to get it | Worked example |
|---|---|---|
| Hours saved / week | Time the queue for one week before the build. Measured automation rates from our builds: 60-80% of tier-1 triage, 3-5x faster drafting. | 31.5 hrs |
| Loaded hourly rate | Salary + benefits + overhead, divided by working hours. Typically 1.3x base wage. | $38/hr |
| Build cost | One-time. $10K-$25K for a single workflow (2-4 weeks); $25K-$50K multi-tenant (4-8 weeks). | $18,000 |
| Run cost / month | Model spend + hosting + maintenance. Measured model spend across 5 builds: $200-$1,800/month. | $500/mo |
| Error cost avoided | Errors per month x cost per error x reduction rate. Count only if you measure errors today. | optional |
Worked example: ticket triage
- Three support staff spend 15 hrs/week each on tier-1 triage: 45 hrs/week.
- AI triage removes 70% of that (measured range on our builds: 60-80%): 31.5 hrs/week saved.
- At a $38 loaded rate: 31.5 x 52 x $38 = $62,244/year in value.
- Build cost $18,000, run cost $500/month: year-one cost = $24,000.
- ROI = ($62,244 − $24,000) ÷ $24,000 = 159% in year one. Payback = $18,000 ÷ ($5,187 − $500) = 3.8 months.
Two honest caveats from real builds. Regulated verticals add 3-5 days of compliance review per AI surface, and reviewed drafting can be slower per artifact until volume ramps — we saw this on a UK pharmacy build. And run cost is a lever, not a constant: prompt caching cut Claude input cost 60-72% on builds with static system prompts.
For build-cost baselines by project shape, see our fixed-price tiers ($10K-$50K) and the breakdown in how much AI development costs.
The AI value matrix: which use case to build first
Score each candidate use case on two axes. Impact: hours consumed per week x loaded rate. Feasibility: predictable inputs, structured data, reversible actions, output a human can review. Then act by quadrant:
Build first
Repetitive queue, predictable inputs, reviewable output. Example: tier-1 ticket triage — 80% automated on our MSP build handling 1,000+ daily operations.
Prototype before committing
Big prize, but messy data or irreversible actions. Scope a 1-2 week spike before quoting the full build. Never automate the irreversible path.
Batch as quick wins
Easy but small. Bundle several into one build so the fixed cost amortizes. Drafting tasks often live here: 3-5x faster per artifact.
Skip
Fine-tuning experiments and vector search on tiny corpora lived here in our builds. We tried both; prompt + retrieval beat fine-tuning at 5% of the cost.
The platforms behind these numbers — MSP operations, telemedicine, legal IP, digital pharmacy, enterprise multi-LLM routing — are documented in our case studies.
Run the numbers: free AI ROI tools
Both tools run in the browser. No signup, no email gate, results on-page.
AI ROI Calculator
Enter your team size, hourly rate, and manual task hours. Get annual savings, ROI percentage, and payback period for an AI automation project.
What you get:
- Payback period in months
- Annual savings estimate
- Industry-specific multipliers
- Implementation cost baseline
AI Readiness Assessment
Ten questions across technology, process, people, and data. Scores where your organization is ready for AI and where it will stall.
What you get:
- 10-question assessment
- Category-specific scoring
- Concrete next steps
- No signup, results on-page
Free templates for the business case
Once the ROI math clears, these templates carry the project through approval and implementation.
AI Implementation Checklist
Week-by-week action items for an AI build, from scoping to production handoff.
Includes:
- Week-by-week action items
- Success criteria definitions
- Risk mitigation steps
- Resource allocation guide
AI Business Case Template
The document structure for getting an AI project approved: ROI model, risks, timeline.
Includes:
- Executive summary format
- Financial modeling sections
- Risk assessment framework
- Implementation timeline
AI Governance Framework
Governance template covering review queues, audit logging, and decision rights for AI output.
Includes:
- Review-queue design
- Decision-making processes
- Compliance checklists
- Monitoring procedures
Data Readiness Audit
Spreadsheet for scoring data quality, accessibility, and AI-readiness before you build.
Includes:
- Data quality scoring
- Integration assessment
- Security compliance check
- Improvement priorities
AI ROI: frequently asked questions
How do you calculate ROI for an AI project?
AI ROI (%) = (annual value minus annual cost) divided by annual cost, times 100. Annual value = hours saved per week x 52 x loaded hourly rate, plus avoided error cost. Annual cost = build cost plus 12 months of run cost (model spend, hosting, maintenance). Payback in months = build cost divided by net monthly value. Our free AI ROI calculator runs this math for your inputs.
What does an AI build cost to build and run?
From our shipped projects: a single-workflow build runs $10K-$25K and ships in 2-4 weeks; a multi-tenant platform runs $25K-$50K over 4-8 weeks. Production model spend ran $200-$1,800/month across 5 builds, and prompt caching cut Claude input cost 60-72% where system prompts were static.
How long until an AI project pays back?
When an automation removes 60-80% of a repetitive queue, payback typically lands in 2-6 months. Regulated builds pay back slower: every AI surface adds 3-5 days of compliance review, and reviewed drafting can be slower per artifact until volume ramps.
What is an AI value matrix?
A 2x2 grid that scores each candidate AI use case on business impact (hours consumed x loaded rate) versus feasibility (predictable inputs, structured data, reversible actions, reviewable output). Build the high-impact high-feasibility quadrant first; prototype high-impact low-feasibility; batch the quick wins; skip the rest.
Which AI use cases show measurable ROI first?
From our production data: tier-1 ticket triage (60-80% automated), document and reply drafting (3-5x faster per artifact, humans edit instead of writing from blank), and support replies with well-known question shapes (50-70% sent without edit). Irreversible actions and legal output stayed human-approved in every build.
Is the AI ROI calculator free?
Yes. The ROI calculator and the readiness assessment are free, run in the browser, and require no signup. Results are yours; nothing is emailed or gated.
Want the ROI math run on your actual workflow?
Book a 15-minute intro. We scope the queue, the build cost, and the payback window against real numbers from shipped work — backed by a 100% satisfaction guarantee.