The ROI of AI trainings: calculate value

At a time when companies invest heavily in artificial intelligence, CFOs and managing directors face a crucial question. Is this really worth it?

In specific, investment in continuing training of employees raises the question of return on investment (ROI). How can the financial benefits of AI training be measured?

This article provides a practical guide to calculate the ROI of your AI training initiatives and to show the true value for your company.

Why the ROI of AI training is crucial

Calculate the ROI of AI trainings: Practical guide with example calculation for the return on investment of your AI further education.

For The ROI of AI trainings: calculate value, Cost Calculator: AI Development, Our Development Process sowie Custom Software Development help you align rollout, scope and budget before you commit.

The introduction of AI is more than just a technical upgrade. It is a strategic corporate decision with far-reaching financial implications.

ROI review is essential to ensure that investments made not only cause costs but generate measurable added value.

A clear business case, supported by a solid ROI calculation, helps not only with budget release.

However, also to anchor the strategic importance of employee qualification across the company.

A model for calculating the ROI of AI trainings

The calculation of the ROI for continuing training can be complex, as not all the benefits can be measured at once in Euro and Cent.

A pragmatic approach combines quantitative and qualitative factors.

The basic formula is: ROI (%) = (net profit - cost) / cost) × 100

Entering costs of investment

First, all costs incurred must be covered transparently:

• Direct training costs: Fees for external trainers, online courses or certifications

• Internal costs: Employee working hours during training (living costs)

• Technology and infrastructure costs:

• Organization effort: Time for planning, planning and follow-up

quantify 2. Net profit of investment

This is the most demanding part of the calculation. The profit consists of different factors:

• Increase in efficiency: Time savings in processes, multiplied by personnel costs

• Savings through automation and error reduction

• Increase in sales: Extra income from AI-based activities

• Quality improvement: Reduction of labour costs

Example calculation for a team of 10 employees

Cost overview

Costs	Amount	Basis of calculation
Training fees	€ 10,000	10 employees × € 1,000
Personnel costs (waste time)	€ 5,000	10 MA × 16h × € 31,25/h

Total cost € 15,000

Overview of benefits (per year)

Position Value (p.a.) Basis of calculation

Efficiency gain € 30,000 10 MA × 2h/week × 50 weeks × € 30/h

Error reduction € 15,000 Reduction of rework by 50 %

Total benefits € 45,000

Calculated result:

Net profit: € 45,000 - € 15,000 = € 3

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Clarity: Where no primary source is named in the text, figures are illustrative; compare Bitkom and Destatis. Project-related statements: Groenewold IT, 2026.

References and further reading

The following separate references complement the topics in this article:

• Bitkom – German digital industry association.
• German Federal Office for Information Security (BSI).
• European Commission – Digital strategy.
• MDN Web Docs (Mozilla)
• W3C – World Wide Web Consortium.

"Cloud-native only pays off when operations, security, and cost model match the architecture—otherwise you ship complexity faster."

— Björn Groenewold, Managing Director, Groenewold IT Solutions

Frequently Asked Questions (FAQ)

What is this article about: “The ROI of AI trainings: calculate value”?

This post explores The ROI of AI trainings. Calculate value from the perspective of needs, typical pitfalls, and sensible next steps. In short.

Calculate the ROI of AI trainings. Practical guide with example calculation for the return on investment of your AI further education.

Who benefits most from the content described here?

Useful for project leads and product owners in AI training who must choose between standard software, custom development, and integration.

How does this topic fit into an IT or digital strategy?

Technically and organizationally, alignment with experienced partners pays off — from requirements to operations; start with the [services overview](/en/services/artificial-intelligence). For multi-system landscapes, [IT consulting and architecture](/en/services/it-consulting) helps align vendors and internal teams.

What are sensible next steps if we need support?

A practical next step: book a consultation and clarify which MVP or pilot fits your team and landscape.