AI ROI Calculator

The AI ROI Calculator lets you model the financial impact of deploying AI agents for a specific workflow. Input your baseline human cost, AI agent cost estimate, and deployment volume—the calculator returns your payback period, year-1 ROI, and sensitivity analysis.

How the calculator works

The calculator inputs are:

Baseline workflow metrics:

• Annual work items (tickets, claims, applications): e.g., 120,000
• Cost per work item with humans (fully loaded): e.g., $7.43 per ticket
• Annual baseline cost: calculated automatically (120,000 × $7.43 = $891,600)

AI agent model:

• Number of agents to deploy: e.g., 2
• Cost per work item with AI (all-in): e.g., $0.81 per ticket
• AI annual cost: calculated automatically (120,000 × $0.81 = $97,200)

Transition costs:

• Integration and deployment (one-time): e.g., $50,000
• Prompt engineering and knowledge base (one-time): e.g., $30,000
• Learning curve inefficiency (first 6 months): e.g., $15,000

Outputs:

• Cost savings year 1 (gross): baseline cost − AI cost = $891,600 − $97,200 = $794,400
• Cost savings year 1 (net of transition): gross savings − transition costs = $794,400 − $95,000 = $699,400
• Payback period: (transition costs) ÷ (monthly savings) = $95,000 ÷ ($794,400 ÷ 12) = 1.4 months
• Year-1 ROI: (net savings) ÷ (transition costs) = $699,400 ÷ $95,000 = 737%
• Year-2 ROI (run-rate): (annual AI savings with no new transition cost) = $794,400 gross

Sensitivity analysis

The calculator also runs a sensitivity analysis on key assumptions:

If human cost is 20% lower than estimated:

• New baseline: $7.43 × 0.8 = $5.94 per ticket
• New baseline annual cost: $712,800
• New gross savings: $712,800 − $97,200 = $615,600
• New payback period: $95,000 ÷ ($615,600 ÷ 12) = 1.85 months
• ROI still 647% (still compelling)

If AI cost is 30% higher than estimated (due to higher human review rate or infrastructure overhead):

• New AI cost: $0.81 × 1.3 = $1.05 per ticket
• New annual AI cost: $126,000
• New gross savings: $891,600 − $126,000 = $765,600
• New payback period: $95,000 ÷ ($765,600 ÷ 12) = 1.49 months
• ROI still 705% (still very strong)

If volume is 30% lower than projected:

• New annual items: 120,000 × 0.7 = 84,000
• New baseline cost: 84,000 × $7.43 = $624,120
• New AI cost: 84,000 × $0.81 = $68,040
• New gross savings: $624,120 − $68,040 = $556,080
• New payback period: $95,000 ÷ ($556,080 ÷ 12) = 2.05 months
• ROI still 585% (still worth it)

The calculator runs these scenarios so you can see how robust your business case is to assumption changes.

What makes a good ROI target

Payback period:

• Less than 3 months: Excellent. Deploy immediately.
• 3–6 months: Good. Execute if there are no competing priorities.
• 6–12 months: Acceptable. Make sure you're not underestimating transition costs.
• Greater than 12 months: Marginal. The ROI isn't compelling enough unless the strategic upside is high.

Year-1 ROI:

• Greater than 200%: Exceptional. This is your slam-dunk case.
• 100–200%: Excellent. This is a clear value driver.
• 50–100%: Good. Worth executing if operational priorities allow.
• Less than 50%: Marginal. You need to optimize the agent cost or find a higher-volume use case.

Most of Runrate's customers see payback periods in the 1–3 month range and year-1 ROI above 200%, because the delta between human cost ($5–$8 per unit) and AI cost ($0.80–$2.00 per unit) is so large.

Common scenarios and what the calculator shows

Scenario 1: High-volume, low-complexity support (most common)

• Annual tickets: 500,000
• Human cost per ticket: $5.50 (CSR model)
• AI cost per ticket: $1.20 (after accounting for all overhead)
• Transition costs: $80,000

Calculator result:

• Gross annual savings: (500,000 × $5.50) − (500,000 × $1.20) = $2,750,000 − $600,000 = $2,150,000
• Payback period: $80,000 ÷ ($2,150,000 ÷ 12) = 0.45 months (2 weeks)
• Year-1 ROI: $2,150,000 ÷ $80,000 = 2,687%

At this scale and complexity, AI is a no-brainer.

Scenario 2: Medium-volume, medium-complexity claims (challenging)

• Annual claims: 25,000
• Human cost per claim: $180 (adjudicator model)
• AI cost per claim: $15 (Claude API + human review + verification)
• Transition costs: $150,000

Calculator result:

• Gross annual savings: (25,000 × $180) − (25,000 × $15) = $4,500,000 − $375,000 = $4,125,000
• Payback period: $150,000 ÷ ($4,125,000 ÷ 12) = 0.44 months (2 weeks)
• Year-1 ROI: $4,125,000 ÷ $150,000 = 2,750%

Even with higher complexity and transition cost, the ROI is exceptional.

Scenario 3: Low-volume, high-complexity loan origination (marginal)

• Annual applications: 3,000
• Human cost per application: $300 (loan officer model)
• AI cost per application: $8 (Claude API + KYC verification + human escalation)
• Transition costs: $200,000

Calculator result:

• Gross annual savings: (3,000 × $300) − (3,000 × $8) = $900,000 − $24,000 = $876,000
• Payback period: $200,000 ÷ ($876,000 ÷ 12) = 2.73 months
• Year-1 ROI: $876,000 ÷ $200,000 = 438%

Still compelling, but transition cost is a larger percentage of savings. Make sure you're not underestimating the complexity of loan origination workflow integration.

How to use the calculator for vendor evaluation

When you're evaluating multiple AI vendors or multiple deployment approaches, use the calculator to compare:

1. Different models (Claude vs GPT vs open-source): Input the API cost for each. Which one has the best cost-per-outcome target? Pick the winner. The calculator shows you the financial impact of model choice.

2. Different deployment approaches (third-party API vs self-hosted): A third-party API (Claude, GPT) costs per-call. Self-hosting (running LLaMA on your GPU cluster) costs for infrastructure. The calculator lets you model both and compare.

3. Phased rollout vs big-bang: Should you deploy 2 agents first (lower transition cost, longer payback, lower risk) or 5 agents (higher transition cost, faster payback, higher risk)? The calculator shows the financial implication of pace.

Limitations and caveats

The calculator assumes:

• Human baseline cost is accurate. Many companies underestimate loaded cost (they forget benefits, overhead, manager time). If you're uncertain, use a higher number.

• AI cost estimate is conservative. We assume 12% human review rate and normal infrastructure overhead. If your use case is complex (legal documents, highly regulated), human review might be 25%+. Adjust accordingly.

• Transition costs are real. The calculator includes one-time integration, prompt engineering, and learning curve inefficiency. Don't ignore these—they're the difference between expected and actual ROI.

• No accounting for risk. If you're deploying into a high-stakes domain (healthcare, financial services, legal), there's adoption risk. The calculator assumes successful deployment. In reality, you might need additional testing, compliance reviews, or vendor evaluations that extend timeline.

What to do next

Run the numbers yourself with the AI ROI Calculator. Input your specific workflow (support, claims, underwriting, back office) and see what payback period and ROI the calculator gives you. If you see payback under 6 months and year-1 ROI over 100%, you have your business case to present to the board.

When you're ready to see what work-item-level AI cost attribution looks like in your stack, talk to Runrate — 15-minute demo.