Running an annual AI subscription review: a price-use-security method
A method for conducting a yearly review that consolidates all AI spending, evaluates real usage and benefit changes, and produces a keep-downgrade-rotate-cancel decision plus next year's budget ceiling before renewal notices arrive.
The purpose of an annual review is not to prove you found a discount, but to decide what to keep, downgrade, rotate, or cancel for the next year. Consolidate web, Apple, Google Play, team, API, and extra-credit invoices. Record original currency, tax, refunds, and exchange-rate effects for each. Treat an annual payment as cash spent in that year, then also calculate the effective cost per month actually used.
For each product, count active months, useful tasks completed, unique capabilities, limits reached, outages experienced, and benefit changes (credits, model access, commercial rights). Cancel low-use overlap first; reconsider an expensive tier only when limits regularly interrupt valuable work. A change in credits, model access, or commercial rights belongs in the review even when the monthly price is unchanged—these silent changes affect real value.
Finish the review by checking the next renewal date, annual exit rules, administrators and members, API keys, third-party connections, two-step verification status, data exports, and reimbursement evidence. This is the security and access audit that closes the year. Set next year's budget ceiling and quarterly review dates before the next renewal notice appears—do not wait for the charge to trigger the decision.
The result: a documented decision for each subscription, a budget ceiling that reflects real usage, and quarterly checkpoints that catch drift early. The limitation: benefit changes and pricing shifts happen mid-year and may not be captured by a single annual review; pairing it with the monthly budget method (E-13) covers the gap between annual reviews.