The problem con la mayoría de análisis de ROI en IA

When a company evaluates whether to automate with AI agents, it typically makes two opposite mistakes. The first is overestimating the implementation cost, imagining months-long projects with engineering teams. The second is underestimating the cost of doing nothing, as if the status quo were free.

Neither is correct. Here we present an honest calculation framework, with the real numbers we see in our projects.

Step 1: quantify the current cost of the process

Before calculating the ROI of automation, you need to know how much the process costs as it exists today. These are the components to measure:

"The real cost of a manual process includes errors, lost opportunities and the inability to scale without hiring. Added together, it is usually 2-3 times the visible staffing cost."

Step 2: calculate the cost of the agent solution

The cost of operating AI agents has three main components:

Step 3: calculate the net monthly saving

With the above numbers, the calculation is straightforward:

In the projects we have deployed, the average payback is between 6 and 10 weeks. Not months: weeks.

Real example: order management in a manufacturing company

What the numbers don't capture

The financial ROI is the rational justification for the investment. But there are benefits that a spreadsheet does not easily capture:

When we add these factors together, the real ROI of automating with AI agents in 2025 is, in most business cases, one of the best available.