AI Monthly Cost Budgeter

What it does

Track every AI subscription and API spend in one place. Tool seeds with 6 common services (ChatGPT Plus, Claude Pro, Gemini Advanced, Cursor, Perplexity Pro, GitHub Copilot) and lets you add others (Anthropic API console, OpenAI API, Replit Agent, v0.dev, Midjourney, Suno, ElevenLabs, etc.). Set a monthly budget cap and the tool flags whether you’re over, under, or on-track. Useful for individuals and small teams whose AI spend has crept up to $100-300/month across multiple services without anyone noticing.

Why AI spend creeps: AI tools are typically $20/month subscriptions, easy to add, hard to remember to cancel. A typical knowledge worker in 2025-2026 has: ChatGPT Plus ($20), Claude Pro ($20), Cursor or GitHub Copilot ($20), maybe Perplexity Pro ($20), and possibly an API key billing $20-100/month for occasional power use. Total: $80-180/month, often more if you’re also using Midjourney, Suno, ElevenLabs, or similar. Most people don’t notice because each individual line is small. Auditing the full stack often reveals 1-2 subscriptions you’ve stopped actually using.

Optimization patterns: (1) Consolidate models — if you have ChatGPT Plus AND Claude Pro AND Gemini Advanced, you’re paying $60/month for overlapping capabilities. Pick one primary ($20) and use API access ($5-15/month typical) for occasional cross-comparison. (2) API vs subscription crossover — heavy API users (50+ queries/day on long contexts) often spend $50-100/month on API alone, which covers a subscription anyway. Monitor actual usage to decide. Light users (5-10 queries/day) almost always benefit from subscription over API. (3) Audit quarterly — cancel subscriptions you haven’t used in 30 days; sign up again next time you actually need them. Most services have no penalty for stop-and-start subscriptions. (4) Team plans — for 3+ users on Cursor, ChatGPT, or Anthropic, team/business plans typically save 15-25% per seat AND provide centralized billing.

How to use it

1. Set your target monthly budget for AI tools (typical knowledge worker: $50-150; AI-heavy developer/researcher: $150-400; team budgets vary widely).
2. Add each AI service you currently subscribe to or use: name, monthly cost, optional usage notes (e.g., 'main coding tool', 'research only', 'image gen').
3. For API-billed services (Anthropic Console, OpenAI API), use trailing 30-day average from the provider's billing dashboard, not the maximum monthly number.
4. Read total monthly spend and over/under-budget flag. Common surprise: total is 30-50% higher than people remember after adding everything up.
5. Audit each line: 'have I used this in the last 30 days?' If no, cancel; sign up again later if needed. Cancellation usually keeps service through end of current billing period.
6. Re-run quarterly. AI tool churn is fast — services launch, prices change, capabilities shift. Quarterly review prevents 'set and forget' overspend.

When to use this tool

• Knowledge workers running multiple AI subscriptions — quick audit reveals double-coverage and unused services.
• Small teams scaling AI usage — when every developer signs up for their preferred tools individually, the company total balloons quickly.
• Freelancers / consultants — AI tooling is a deductible business expense; tracking it cleanly simplifies year-end accounting.
• Pre-cost-cutting reviews — if you're trying to reduce SaaS spend, AI subscriptions are often the easiest line to trim because most have month-to-month billing.

When not to use it

• Large enterprise procurement — those use formal SaaS-management platforms (Vendr, BetterCloud, Productiv) with vendor-by-vendor SOC2 review.
• Single-tool users (just ChatGPT Plus, nothing else) — the budgeter is overkill for one $20 line item.
• Pure API-only workflows — those need usage-based monitoring (Anthropic console alerts, OpenAI usage limits) not flat-budget tracking.
• Households with shared accounts — billing is on one credit card but usage is across family members; the tool doesn't model household-shared billing well.

Common use cases

• Educational use — demonstrating the underlying concept
• Onboarding a colleague who needs the same calculation/conversion
• Verifying a number or output before passing it on
• Quick use during a typical workday