ROI-First Automation: How to Implement AI with Measurable Results
We don't launch AI projects without a financial model. This page covers ROI calculation methodology, typical savings scenarios, and real case studies with before/after metrics.
Calculate savings for your processWhy calculate ROI before launch
70% of AI projects fail to deliver ROI because they launch without a baseline or target metrics. We capture current losses (operation volume, time, hourly cost) and forecast savings before writing a single line of code.
What a baseline looks like
A baseline is the measurable state of a process before implementation: daily requests, median processing time, employee hourly cost, share of manual work. Without a baseline, you cannot prove impact.
KPIs and impact metrics
Typical KPIs: TTR reduction (time-to-resolution), auto-resolved share, monthly savings in currency, payback period. Each KPI is tied to a data source and comparison period.
Typical savings scenarios
Knowledge base search: 40-60% time savings. Document verification: 70% reduction in manual operations. Feedback processing: 30-50% auto-closure rate. All figures from real implementations with evidence packs.
Calculation limitations
The ROI model is built on assumptions. We explicitly state: which data comes from real analytics, which are expert estimates, and how sensitive the model is to changes in key parameters.
FAQ
How much does an ROI assessment cost?
Included in the automation pilot cost (from 150,000 RUB). The financial model is delivered as a project artifact.
What if ROI is negative?
We will honestly say that automating this process won't pay off and suggest an alternative scenario or decline the project.
How long does a typical implementation take to pay back?
3-6 months with correct process selection and fixed before/after metrics.
Ready to discuss?
Leave a request — we'll audit your process, calculate ROI, and propose a pilot scenario.
Calculate savings for your process