The ROI of AI is currently one of the main obstacles to launching AI projects in companies.

Many business units and IT departments identify promising use cases, but struggle to answer a simple question: how can you concretely measure the profitability of an AI project?

The difficulty does not stem solely from the calculation itself. In most companies, the main challenge lies in identifying the right business metrics and realistically estimating potential gains.

However, you don't need to build a complex financial model to get an initial estimate. For the majority of AI projects, ROI relies on a few simple levers: time saved, error reduction, lower operational costs, or increased revenue.

In its simplest form, the ROI calculation can be expressed as follows:

ROI = (Gains generated - Project cost) / Project cost × 100

The real challenge then lies in correctly estimating the gains generated by the AI and calculating a cost that accounts for not only the software, but also the internal time allocated to managing the project.

Here are 4 concrete methods for calculating AI ROI depending on the use case.

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1. Product consulting: measuring commercial gains

In the industrial sector, sales teams often spend a significant portion of their time searching for technical information, preparing quotes, or consulting internal experts to answer specific customer questions.

A product consulting AI speeds up access to information and improves the quality of recommendations made to customers. ROI can then be evaluated through both productivity gains and the impact on sales.

Time saved

Let's assume:

• 100 sales representatives
• 2 hours saved per week
• average loaded cost: €45/hr

Annual gain:

100 × 2 × 45 × 52 = €468,000

Impact on revenue

AI also helps sales teams access the right information faster and provide better advice to customers.

For example:

• +5% conversion rate
• on €2M in revenue

Potential gain:

€100,000 in additional revenue

Another way to estimate potential gains is to calculate the impact if your bottom 10% of sales performers improved their skills to reach the median revenue.

In some projects, this sales component represents a significant portion of the overall ROI.

This calculation can be refined by applying coefficients based on how critical sales expertise is in your industry, or the technical complexity of your products.

Our dedicated sales ROI calculator can help you refine this estimate.

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2. Technical support: calculating operational gains

Technical support is often one of the first areas where the ROI of AI becomes visible.

Technicians regularly spend time searching for procedures, consulting documentation, or identifying the root cause of an incident before they can intervene effectively.

An AI support tool helps speed up diagnostics, reduce errors, and limit the time spent on certain interventions.

Time saved

• 100 technicians
• 2 hours saved per week
• average cost: €40/hr

Annual savings:

100 x 2 x 40 x 52 = €416,000

Reducing errors

Better access to information also helps limit incorrect diagnoses and unnecessary escalations.

For example:

• 300 errors and non-compliance issues per year
• Average cost of an error: €500
• 30% reduction thanks to AI

Annual savings:

(300x500)x0.3 = €45,000

Reducing time spent on interventions

Instant access to procedures, incident histories, and feedback also helps reduce the average duration of certain interventions.

Even saving a few minutes on each intervention can add up to tens of thousands of euros over the course of a year.

Once again, this calculation can be refined by taking into account the technical nature of your products, the complexity of your standards, and the time saved by internal support teams. ‍

Discover our AI ROI calculator for a complete estimate.

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3. Compliance support: measuring the cost of avoided errors

In quality, compliance, and regulatory affairs roles, gains don't just come from productivity.

One of the main benefits of AI lies in its ability to reduce errors and secure processes.

By facilitating access to procedures, standards, or regulatory documents, AI helps teams find the right information faster and limit certain operational risks.

Time saved

• 30 project managers
• 5 quality managers
• 2 hours saved per week
• average cost: €50/hr

Annual gain:

35 × 2 × 50 × 52 = 182,000

Reduction in non-compliance

Suppose AI helps avoid:

• 3 quality incidents per year
• average cost: €20,000

Annual gain:

3 × €20,000 = €60,000

In certain highly regulated sectors, risk reduction can represent a greater gain than productivity improvements themselves.

Estimate your ROI with our AI ROI calculator.

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4. Don’t have clear business KPIs yet? Start with time saved

Many companies know that an AI project could bring them value but do not yet have precise enough business indicators to build a detailed business case.

In this case, time saved is often the best starting point.

It is a simple indicator to measure, easy for decision-makers to understand, and directly linked to team productivity.

Initial AI profitability calculations in companies often rely on a few simple questions:

• how much time do employees spend searching for information?
• how much time is spent on repetitive tasks?
• how many requests can be processed each day?
• how long does it take to train a new hire?

Even without advanced business KPIs, these indicators generally allow for a credible initial ROI estimate.

Use our AI ROI calculator to get an initial estimate.

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How do you estimate the costs of an AI project?

To build a realistic AI business case, it is essential to include all project costs.

The first component concerns the platform itself: licenses, number of users, volume of usage, or deployed features.

You must then take into account the services associated with the project: scoping, integration with existing tools, deployment support, or user training.

Finally, an often underestimated item concerns the time invested by internal teams. Subject matter experts typically participate in selecting knowledge, validating content, and continuously improving the solution. This time must be included in the overall calculation.

At Ask for the moon, to ensure project success, we estimate this workload at:• 5 days for initialization, for the deployment of an initial AI assistant (including testing)• 4 to 6 hours per month for the expert in charge of the assistant once the project is in the run phaseThese estimates are generally valid for one addressed use case and vary depending on your business context.

The goal is not just to reduce costs. A high-performing AI project is, above all, a project capable of quickly generating a measurable business impact.

Use our AI ROI calculator to build your business case.

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Frequently asked questions about AI ROI

How do you calculate the ROI of an AI project?

The ROI of an AI project is calculated by comparing the gains generated by the AI (time saved, error reduction, revenue growth) against the project costs. The most common formula is: (gains - costs) / costs × 100.

What are the main benefits of an AI project?

The most frequently observed benefits include time saved by teams, reduction in errors, improved response quality, lower operational costs, and in some cases, increased revenue.

What ROI can be expected from an enterprise AI assistant?

Return on investment depends on the use case and the level of adoption. Projects related to technical support, product consulting, or information access generally generate the fastest returns.

How do you build a credible AI business case?

A credible AI business case is based on simple, measurable indicators. It is generally best to start with concrete operational gains, such as time saved or errors avoided, before incorporating more indirect benefits.