Estimate annual capacity value, hard software savings, cost per output and payback for one workflow. Compare low, base and high scenarios with every assumption and formula in view.
Choose one bounded workflow—such as weekly pipeline reporting, lead-routing review or recurring campaign production. A credible baseline makes the result useful.
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Keep cash and capacity separate. Recovered hours are useful capacity, not automatic payroll savings. Cost-per-output savings can overlap with capacity and SaaS savings, so they are not added to net benefit.
This calculator provides a planning estimate, not a guarantee, valuation, financial opinion or implementation quote. Results depend on baseline accuracy, adoption, output quality, exception handling, governance and implementation costs. Validate the case with a controlled pilot and appropriate financial, legal, privacy, security and workforce review.
Baseline annual hours = people × manual hours per person each week × working weeks. For each scenario, we multiply those hours by automation potential and then by the realization factor. The result is usable recovered capacity.
Economic payback compares one-time cost with monthly capacity value plus hard software savings, after recurring AI costs. Cash payback excludes capacity value. If recurring benefit does not exceed recurring cost, the result says “No payback.”
Compare annual benefits for one workflow with its one-time and recurring costs. Keep recovered capacity, hard savings and optional revenue effects separate so the business case remains auditable.
There is no universal percentage. Start with a range, account for human review and exceptions, and replace assumptions with measured pilot data.
No. They represent capacity. Value is realized when that capacity is redeployed to useful work or produces a verified financial outcome.
Payback months equals one-time cost divided by monthly recurring net benefit. When recurring benefit does not exceed recurring cost, there is no payback in that scenario.
Revenue effects carry more causal uncertainty and can overlap with output improvements. Keeping them separate makes the core operating case easier to defend.