Prompt ROI Calculator

Before you roll out AI tools to a team, you need a number a finance lead will believe. This calculator turns the time AI saves on repetitive tasks into monthly hours saved, a salary-equivalent value, and a projected annual ROI — using inputs you can measure rather than vendor marketing.

How it works

For every task you add, the tool computes the minutes saved per run as manual minutes − AI minutes, then multiplies by how often the task runs each month. That gives monthly minutes saved, converted to hours. Multiplying by your hourly staff cost produces the salary-equivalent value, and multiplying that by twelve gives the annual figure.

It also expresses total savings as full-time-equivalents — dividing monthly hours saved by about 160 productive hours per person — because “frees up 1.4 FTEs” lands harder in a budget meeting than “saves 224 hours.”

Worked example: drafting support responses

Consider a support team of five people, each spending an average of 3 hours a day drafting responses from scratch. With AI assistance (suggested draft plus review and edit), that drops to about 1 hour a day:

Manual time per person per day:   3 hours
AI-assisted time per person:      1 hour
Daily saving per person:          2 hours
Monthly saving (22 working days): 2 × 22 = 44 hours per person
Total for 5 people:               220 hours/month

At a fully-loaded hourly cost of £35/person, that is 220 × £35 = £7,700 per month in salary-equivalent value, or £92,400 annualised. Against an AI tool cost of perhaps £500/month for the team, the net ROI is strongly positive. The calculator builds this table for multiple tasks simultaneously, so you can stack several workflows and see the cumulative picture.

Tasks that tend to show large savings

The highest-ROI tasks share a pattern: they are frequent, structured, and currently done by expensive people. Common examples:

• First-draft generation for emails, proposals, reports, or documentation — the draft quality may need review, but going from blank page to 80% draft is a significant time saver
• Summarisation of long documents — meetings, contracts, research papers, support backlogs
• Data extraction and classification — pulling structured fields from unstructured text, tagging tickets, categorising feedback
• Code review boilerplate — generating initial review comments, docstrings, test scaffolding

Tasks with low savings are those requiring high human judgment throughout: strategic decisions, client relationship management, complex negotiations, and creative work requiring strong personal voice.

Common mistakes in AI ROI calculations

Counting only generation time, not the full cycle. The time to generate a draft is typically seconds. The time to prompt effectively, review, correct errors, and apply judgment is often 10–30 minutes. The real saving is that last mile, not the generation itself. Overestimating here is the most common way AI ROI calculations get discredited.

Ignoring the learning curve. Staff productivity with AI tools is lower in the first weeks. A realistic model holds back 20–30% of projected savings for the first three months to account for ramp-up.

Not accounting for quality differences. If AI output requires extensive correction to meet quality standards, the savings can disappear. Track correction time explicitly when measuring real tasks.

Using salary instead of fully-loaded cost. The salary-equivalent value in a business case should use the total cost to the company, not the take-home pay or even the gross salary. Benefits, employer NI (UK), equipment, software, and management overhead often add 40–60% on top.

Build an honest business case

• Use fully-loaded hourly cost, not raw salary. Benefits, tax, tooling, and management overhead typically add 30–50% on top of base pay.
• Be strict on AI minutes. Count prompting, reviewing, and fixing — not just the seconds the model takes to respond. Output that needs heavy editing saves far less than it looks.
• Measure, don’t guess. Time three or four real instances of a task with and without AI before trusting the projection.
• Subtract tool cost from the monthly value to get net ROI; the gap is usually large in AI’s favour, which is exactly the point you want to make.