Introduction
"Add AI to our product" sounds like a small feature request, but the real cost spans development time, ongoing API usage, and infrastructure most founders don't budget for upfront.
API Costs at Different Scales
LLM API costs are usage-based and scale with both the number of requests and the size of the context sent with each one. A feature with light usage (a few thousand calls a month) might cost a few hundred dollars monthly; a feature embedded in every user session at scale can run into thousands. Always model cost per active user, not just a flat estimate.
Development Time
A simple, single-turn AI feature (summarization, classification) is typically a 1–2 week build for an experienced team. A RAG-based feature requiring a vector database and retrieval pipeline is closer to 3–4 weeks. Anything agentic, with multiple tool calls and guardrails, should be budgeted at 4–8 weeks minimum for a production-ready version.
Hidden Ongoing Costs
Beyond the API bill, budget for a vector database subscription if using RAG, monitoring/logging tools to catch bad outputs in production, and ongoing prompt maintenance as models get updated or deprecated. These recurring costs are often larger over a year than the initial build.
Budgeting Realistically
Start with the narrowest version of the feature that delivers real value, measure actual usage and cost per user in production, and expand scope only once the unit economics are proven. Committing to a broad AI feature roadmap before validating cost-per-user is a common way to blow past budget.
Conclusion
AI features are usage-based cost centers, not one-time development expenses. Model cost per active user from day one, and expand scope only once real usage data confirms the economics work.
Frequently Asked Questions
How much do AI API costs typically run per month?+
It varies widely with usage — a lightly-used feature might cost a few hundred dollars monthly, while a feature embedded in every user session at scale can run into the thousands. Always model cost per active user rather than relying on a single flat estimate.
How long does it take to build a basic AI feature?+
A simple, single-turn feature like summarization or classification is typically a 1–2 week build. RAG-based features usually take 3–4 weeks, and agentic features with multiple tool calls need 4–8 weeks or more.
What ongoing costs beyond the API bill should I budget for?+
A vector database subscription if using RAG, monitoring and logging tools to catch bad outputs in production, and ongoing prompt maintenance as underlying models get updated — these recurring costs often exceed the initial build cost over a year.