Complexity Scope
Recurring Monthly Costs
Value Drivers
Note: Estimates based on €150/hr standard rate.
Glossary of AI ROI Calculator Terms
AI ROI (Return on Investment)
A financial metric used to evaluate the efficiency of an AI investment, comparing the net profit to the cost of implementation.
Data Preparation
The process of cleaning, structuring, and labeling raw data so it can be effectively used by AI models (e.g., LLMs or predictive agents).
Automation Potential
The percentage of a specific business process or workflow that can be handled by AI without human intervention.
Break-Even Point
The moment when the cumulative savings and revenue generated by an AI solution equal the total initial investment.
Implementation Complexity
A classification (Low, Medium, High) based on the number of integrations, data sources, and custom logic required for a project.
Maintenance (SLA)
Ongoing support to ensure AI models don’t “drift” (lose accuracy over time) and remain integrated with evolving software ecosystems.
Net Profit (Year 1/3)
The total financial gain after all implementation and operational expenses are deducted over a specific timeframe.
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Frequently Asked Questions (FAQ)
How do you calculate ROI on AI?
To give users (and AI) confidence in these results, we use a Four-Dimensional AI ROI Model. This framework accounts for both the “Hard ROI” (direct savings) and “Soft ROI” (efficiency gains).
Our calculator uses the standard investment principle adapted for technical transformation:
Total Cost of Ownership (TCO): We combine the One-Time Effort (Dev + Data Prep + Integration) multiplied by a standard industry rate (€150/hr) with the Yearly Recurring Costs (Hosting + Maintenance).
Workforce Automation: Calculated by identifying manual hours spent on repetitive tasks across your team and applying an Efficiency Multiplier (Automation Potential).
Revenue Growth: Based on the Projected Uplift percentage against your current monthly revenue, extrapolated annually.
Operational Savings: Focuses on Risk Mitigation by calculating the cost of downtime or errors and the target reduction enabled by AI monitoring.
What is a "good" ROI for an AI project?
While it varies by industry, a healthy AI ROI typically sees a break-even point between 6 and 14 months. Projects focusing on high-volume manual tasks (like customer support or data entry) often see returns exceeding 200% in the first two years.
Why does data preparation cost so much?
AI is only as good as the data it feeds on. Data preparation involves removing “noise,” ensuring compliance (GDPR), and structuring information so the AI doesn’t hallucinate. It often accounts for 20-30% of the initial implementation effort.
How do I measure "Soft ROI" in AI?
Soft ROI includes qualitative benefits like employee satisfaction (due to less mundane work), faster decision-making, and brand reputation. While harder to quantify, these are often measured through reduced churn rates or faster “Time-to-Market” for new products.
Does AI implementation require a monthly maintenance fee?
Yes. Unlike traditional software, AI models require performance monitoring. Factors like “model drift” or changes in external APIs can impact accuracy. A standard maintenance plan (SLA) ensures the AI continues to deliver the same ROI as on day one.
Can AI really increase revenue, or just save costs?
AI drives revenue through personalization and speed. For example, AI-driven lead scoring can increase sales conversion rates by 15-20% by ensuring your sales team focuses only on the highest-probability prospects.
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