The essentials
The documented median ROI of an automation or AI agent project in an SME is +159.8% at 12 months, with a break-even point reached within 3 to 6 months for 78% of businesses. This return is measured in hours of work recovered, errors avoided and a faster business cycle, not marketing promises.
What an AI project’s ROI actually measures
An automation ROI is calculated simply: (gains generated - total project cost) / total project cost, over a given period. The difficulty isn’t the calculation, it’s identifying all the gains, including those not immediately visible in a spreadsheet.
Direct gains, easy to quantify: eliminated manual data entry hours, reduced processing time, more volume handled with the same headcount.
Indirect gains, just as real: a lower error rate (and therefore lower correction cost), improved customer satisfaction linked to faster responses, reduced turnover on low-value tasks nobody wants to do.
Costs to factor into the calculation: the initial deployment, the monthly subscription, but also the internal time spent on change management, often underestimated.
The break-even point in practice
For 78% of SMEs that ran a serious automation project (prior scoping, targeted use case, before/after measurement), the break-even point is reached between 3 and 6 months after deployment. This figure isn’t magic: it depends directly on the quality of the initial scoping. A project that automates an already optimized process pays off faster than one that tries to automate a broken process, which just amplifies its own flaws.
Measured example: the Samsung testing platform
ROI isn’t limited to SMEs. Samsung Mobile brought in Neodigit to automate functional and regression testing for its devices, a process that used to consume weeks of repeated manual testing across dozens of models, several firmwares and several languages.
Results measured after deployment:
- 80% reduction in test time
- 60% increase in test coverage
- Early detection of critical bugs (before they reach production)
- Positive ROI within 3 months
“This application transformed the way we work. We catch problems much earlier in the development cycle.” - Tech Lead, Samsung Mobile. See the full case study.
How to measure the ROI of your own project
Before deployment: time the process you’re targeting over two to three representative weeks, not a single isolated day. Also note the error rate and the number of exceptions handled manually.
After deployment: repeat the same measurements over an equivalent period. Compare time spent, error rate, number of exceptions requiring human intervention, and satisfaction of the teams involved (a tool rejected by users produces no ROI, regardless of its technical quality).
At 3, 6 and 12 months: track the trend. An automation project’s ROI is never static: it generally improves as rules get adjusted and the automated scope gradually expands.
FAQ
What’s the real return on investment of an AI agent for a business? The documented median ROI is +159.8% at 12 months, with a break-even point reached within 3 to 6 months for 78% of SMEs that ran a seriously scoped project. The return depends directly on the quality of the initial audit: an already-optimized process pays off faster than a broken process automated as-is.
How much does an AI agent cost for an SME in France in 2026? Between €3,000 and €25,000 to deploy depending on complexity, plus a monthly subscription of €80 to €600. Full details on the pricing page.
How can I be sure of getting this level of ROI instead of a project that drags on? By measuring before deploying (not after), by targeting a single high-volume, highly repetitive process for the first project, and by involving the teams involved from the scoping stage. Our practical SME guide details this method step by step.
Let’s estimate the potential ROI of your project together. A 30-minute conversation is enough to identify whether the targeted process has fast-return potential.