Payback period is the simplest, most persuasive way to judge an AI project: how long until it pays for itself? Calculating it honestly takes a clear formula and an honest count of costs and gains. Here’s how, and how dgm fits. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)
The formula
Payback period = total AI cost ÷ monthly savings or gains.
If a project costs $X all-in and produces $Y per month in savings or gains, it pays back in X ÷ Y months. Simple — but only as honest as the numbers you put in.
Count the full cost
On the cost side, include the full picture — implementation, model/usage costs, training, and ongoing operation — not just the license (see AI total cost of ownership). Understating cost flatters the payback and erodes trust later.
Count all the gains
On the gains side, include:
- Staff time recovered (valued at loaded cost).
- SaaS subscriptions eliminated via consolidation.
- Revenue influenced (faster response, better conversion, less churn).
- Rework reduced.
Baseline first — or you can’t prove it
The step most teams skip: baseline the metric before you start. Without the “before,” you can’t prove the “after,” and payback becomes an unverifiable guess (see how to measure AI ROI).
Which use cases pay back fastest
SaaS consolidation (eliminating subscriptions is an immediate, measurable saving) and high-volume automation (recovering many hours) pay back fastest. Diffuse, hard-to-measure benefits pay back slower and are harder to defend — another reason to start with the right use case.
How dgm helps
dgm’s fixed pricing ($399 assessment, $3,999/month) makes the cost side simple and predictable, and because dgm consolidates SaaS tools, savings — and payback — often improve. The assessment ties each use case to a measurable metric to support the calculation. If you’d rather explore the platform yourself first, go straight to osFoundry; if you want a clear payback case, that’s where dgm comes in.