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🤖Interactive Tool

AI Feature ROI Calculator

Calculate whether adding an AI feature is worth the investment. Model development costs, API expenses, time savings, and revenue impact.

Investment Inputs

Total cost to build the AI feature (engineering, design, PM)
LLM API calls, GPU hosting, or inference costs per month
Hours saved per user per month (valued at $50/hr)
Users who will interact with the AI feature monthly
Additional revenue per user from upsell, retention, or conversion
Months until the feature is live and generating value

ROI Analysis

Positive ROI
Monthly Net Benefit
$258.0K
after API costs
Break-even Timeline
3.6 months
including build time
Annual Net Value
$2.9M
year 1 after launch
ROI Percentage
1888%
first year return on investment
Cost per AI Interaction
$0.1000
estimated ~20 queries/user/month

Value Breakdown

Time Savings Value$250.0K/mo
1,000 users x 5h x $50/hr
Revenue Increase$10.0K/mo
1,000 users x $10/mo
Monthly API Cost-$2.0K/mo

12-Month Projection

$-50.0K
M1
$-100.0K
M2
$-150.0K
M3
+$108.0K
M4
+$366.0K
M5
+$624.0K
M6
+$882.0K
M7
+$1.1M
M8
+$1.4M
M9
+$1.7M
M10
+$1.9M
M11
+$2.2M
M12
Building
Recouping
Profitable

LLM Cost Estimator

Estimate and compare LLM API costs across models before committing to a provider.

AI Build vs Buy Analyzer

Decide whether to build custom AI, fine-tune, or use APIs for your use case.

What is an AI ROI Calculator?

This calculator helps product teams build a business case for AI features before committing engineering resources. Enter your estimated development cost, ongoing infrastructure spend, and the revenue or time-savings the feature is expected to generate. The tool calculates monthly ROI, break-even timeline, and annual net value so you can present a clear financial picture to stakeholders. For a broader view of AI investment decisions, see the AI build vs. buy framework.

How to Use This Calculator

  1. Enter development costs. Include engineering hours, external APIs, data labeling, and any one-time setup costs.
  2. Add ongoing costs. Estimate monthly infrastructure, API calls, model hosting, and maintenance. The LLM cost estimator can help you forecast API spend.
  3. Estimate the benefits. Quantify expected revenue uplift (new customers, upsell, retention) and cost savings (automation, reduced support tickets, faster workflows).
  4. Review the results. The calculator shows your monthly ROI percentage, how many months until you break even, and the projected annual net value of the feature.

FAQ

What counts as "revenue from AI" in this calculation?

Include direct revenue (customers who pay more for the AI feature or a higher tier), retained revenue (churn prevented by the feature), and indirect revenue (efficiency gains that let your team ship faster). Be conservative with indirect numbers. The AI unit economics framework provides a structured way to categorize these benefits.

How do I estimate costs if I have not built an AI feature before?

Start with a proof-of-concept budget. Most AI features cost between $5K and $50K to prototype, depending on complexity. Use vendor API pricing as a baseline for ongoing costs, and add 20-30% for iteration and edge cases. Check the AI risk assessment framework for a checklist of costs teams commonly overlook.

What is a good ROI target for an AI feature?

Aim for a break-even timeline under 6 months and a monthly ROI above 50% at steady state. Features with longer payback periods can still be worth it if they create a durable competitive advantage or open a new market segment. The key is making sure you can sustain the investment through the payback period.

Present these numbers to stakeholders with confidence. Deck Doctor reviews your presentation and suggests improvements before the meeting.

Compare This Tool

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