Nanny Agency JobsTo find out whether AI saves your agency money, measure the complete task and separate staff capacity from cash expenditure. A draft produced in seconds may still require preparation, checking, correction and storage. Time recovered can be useful without reducing payroll, and a subscription can be worthwhile without producing an immediate financial return.
This guide offers an original measurement worksheet and fictional calculation. The numbers are invented to make the arithmetic inspectable. They are not product prices, wage recommendations, agency benchmarks or a forecast of what your business will earn.
Choose one task and define its finished state
Pick a repeatable task with a clear endpoint, such as producing an accurate candidate update ready for approved sending. Do not compare “AI generated text” with “recruiter completed and checked message.” Both methods must reach the same standard of completion.
List the included work: finding the facts, preparing inputs, drafting, reviewing, correcting and recording the result. If failed attempts return to the ordinary process, include that time too. Keep unrelated waiting time separate from active staff time so the calculation answers the intended question.
Australia's National AI Centre recommends examining full costs, rework and whether saved time is redirected usefully. Its guidance is general business material, not a nanny-agency savings estimate. National AI Centre: Measure return on investment.
Measure a fair baseline before the trial
Use a sample of ordinary tasks, including incomplete or awkward cases. Record how the current method performs before deciding what the AI method should beat. A baseline built only from unusually difficult cases can make an ordinary improvement look dramatic.
During the trial, keep the task mix comparable. Note important differences such as a quieter week, a more experienced reviewer or cleaner source records. If those changes explain some of the improvement, do not attribute all of it to the tool.
Use this original task log: task identifier, method, preparation minutes, drafting minutes, review minutes, correction minutes, completion status and error category. Add a short note for abandoned attempts. You can aggregate the log without copying candidate or family details into a second dataset.
Calculate recovered time after review and rework
Fictional example: An agency completes 120 comparable updates per month. Its measured ordinary process averages 12 minutes per update. In a fictional AI trial, preparing inputs, drafting and reviewing average seven minutes. Twenty percent of updates need four additional minutes of correction.
The average correction allowance is 0.20 × 4 = 0.8 minutes per update. The complete AI-assisted average is therefore 7 + 0.8 = 7.8 minutes. The difference from the baseline is 12 − 7.8 = 4.2 minutes per update.
Across 120 updates, recovered time is 120 × 4.2 = 504 minutes, or 8.4 hours per month. This is a capacity estimate for this fictional task and volume. It is not yet a saving in the agency's bank account.
Check that correction time has not already been included in the seven-minute figure. If it has, adding it again would double-count the cost. Likewise, do not count the same recovered hours under both “faster drafting” and “reduced administration.”
Add ongoing costs and the cost of getting started
For the same fictional example, assume the agency uses $40 per hour as an internal value for staff capacity. This is an invented planning input, not a recommended wage or billing rate. The 8.4 recovered hours have a modeled value of 8.4 × $40 = $336 per month.
Assume a fictional incremental software expense of $90 per month and two hours of monthly maintenance or oversight. At the same internal value, oversight is 2 × $40 = $80. The modeled recurring net benefit is $336 − $90 − $80 = $166 per month.
Now include setup. Suppose configuration and training take ten staff hours, valued at $400. Under these assumptions, modeled recovery of that setup value takes $400 ÷ $166, approximately 2.4 months. This calculation assumes the same volume, quality and costs continue. It is not a guaranteed payback period or an accounting determination.
Keep a separate cash view. If staffing expenditure does not change, the agency has not saved $336 in cash. It has recovered capacity while taking on $90 of additional monthly software expenditure. The benefit depends on what useful work that capacity enables.
Test a less favorable case before claiming success
Change an assumption that could realistically vary. If only 60 comparable updates are completed monthly, the same 4.2-minute improvement yields 252 minutes, or 4.2 hours. At the fictional $40 internal value, that is $168 of capacity.
If software remains $90 and monthly oversight remains $80, the modeled recurring result becomes $168 − $90 − $80 = negative $2. The original setup value is not recovered through this modeled recurring benefit. Lower volume has changed the decision without any change in writing speed.
Also inspect quality. Count incorrect status statements, missing facts and messages requiring later correction. A financial-looking result does not justify a process that creates unacceptable errors or mishandles information. Set those quality conditions before the trial, rather than relaxing them after seeing an attractive number.
Decide what to keep, change or stop
Finish with three separate findings: observed task-time difference, modeled capacity value and actual cash change. State the sample size, period and assumptions. If the trial is too small or unusual to support a reliable estimate, say what additional observation is needed.
Then identify how recovered time was used. More completed candidate calls, fewer overdue tasks or less overtime are different outcomes; verify whichever you claim. Do not add speculative placement revenue to the calculation just because staff could theoretically make more introductions.
Keep the tool if the measured result and quality support the decision. Narrow its use if only certain tasks benefit. Stop or redesign the trial if review and rework consume the apparent gain. Repeating the same worksheet after a meaningful workflow change is more useful than preserving an impressive first-month percentage.
Sources
National AI Centre: Measure return on investment, checked October 27, 2026. The task log, all figures, calculations and sensitivity case are original fictional NAJ examples. No actual vendor pricing or financial outcome is claimed.