Artificial intelligence has long since made its way into many companies. It drafts emails, summarizes documents, assists programmers, creates presentations, and prepares decisions. Often, however, it wasn’t officially introduced. It was simply there one morning and already had a user account.
Professional AI training, therefore, provides more than just basic technical knowledge. It teaches employees how to use AI systems effectively, evaluate results critically, and adhere to legal and organizational boundaries. At the same time, it helps companies fulfill their obligations to promote AI literacy under the AI Act.
In short: Good AI training combines practical skills, risk awareness, and company policies. It explains not only what an AI system can do, but also when it’s better to keep a close eye on it.
AI training is a structured training program for individuals who develop, select, operate, or use AI systems in their professional work. The content should be tailored to the applications used, the participants’ job responsibilities, and the associated risks.
For marketing professionals, for example, copyright law, labeling, and the handling of user-generated content are particularly relevant. Human resources departments also need knowledge of discrimination risks and automated applicant assessments. Those who use AI to analyze confidential company data, on the other hand, should know what information is permitted to be entered into an external system.
A single presentation for all departments is therefore rarely sufficient. Having the same slides does not necessarily mean having the same level of expertise.
Article 4 of the AI Act has been in effect since February 2, 2025. However, the provision was revised by the Digital Omnibus, which took effect in July 2026.
Providers and operators of AI systems must take measures to support the development of AI literacy among their employees and other individuals who work with such systems on their behalf. In doing so, they must take into account, in particular, prior technical knowledge, experience, training, the context of use, and the individuals affected by the application.
The current version expressly does not require companies to guarantee a specific level of competence for each individual. Similarly, the AI Act does not prescribe a specific training duration or external certification. The European Commission points out that there is no one-size-fits-all training solution for all companies and AI systems.
However, this does not mean that companies can forego training. The obligation to take appropriate measures to develop AI expertise remains in effect. Starting in August 2026, compliance with this obligation may, in principle, also be monitored by the relevant market surveillance authorities.
A documented, application-oriented AI training program is therefore a particularly obvious way to put this requirement into practice. A certificate of participation can serve as evidence of this. However, it is not the training itself, and it certainly does not replace a robust competency framework.
The specific content depends on the company and its AI applications. However, a solid introductory training course should cover at least the following topics:
The key factor is the connection to the actual work. Someone who uses AI exclusively for drafting text needs different skills than someone who evaluates job applications, manages production processes, or processes medical data.
Effective AI training starts with real-world scenarios. Are employees allowed to upload a customer contract to a publicly accessible chatbot? Who reviews an automatically generated market analysis? Does an AI-generated image need to be labeled? And what happens if a system comes up with a very convincing answer?
Cases like these make it clear that AI proficiency isn't just about prompt techniques. Good prompts are helpful. Good decisions are more important.
For many companies, a tiered training program is a good option:
To this end, K11 offers practical AI training for businesses in the form of in-person sessions, remote training, customized corporate training, or e-learning. The content can be tailored to the industry, target audience, and existing AI applications.
A training certificate is useful because it documents who received training on which topics and when. However, it does not automatically answer the question of whether the content covered was appropriate for the actual risk.
A company should therefore also document the following:
The statement “Everyone has a certificate” is encouraging. Still, if we were to examine this further, the next question would likely be: “And what have they learned?”
The AI Act does not generally require companies to appoint an AI officer. Nevertheless, as a practical governance function, this role can provide significant benefits.
An internal or external AI Officer can identify training needs based on the AI inventory and the respective risk assessments. The AI Officer coordinates training sessions, aligns content with data protection, information security, legal, and business departments, and ensures that documentation and updates are not scattered across different email inboxes.
Typical tasks include:
The AI Officer does not replace either management or the subject matter experts. Instead, he connects the various stakeholders and ensures that individual training sessions evolve into a sustainable system.
Before selecting a training format, companies should first assess their use of AI. This includes not only officially procured systems, but also AI capabilities in existing software and applications that employees use on their own.
Next, you can define target audiences and content. A practical process consists of five steps:
The result is an AI training program that doesn't just fill a slot on the calendar, but actually improves the safe use of AI.
Are all employees required to complete AI training?
Article 4 applies to employees and other individuals who work with AI systems on behalf of a provider or operator. Which individuals should receive training and how comprehensive that training must be depends on their duties, prior knowledge, and the systems used. There is no requirement for the entire workforce to receive the same standardized training.
Is a certificate required for the AI training?
The AI Act does not require external training or a specific certification. Nevertheless, proof of participation or competence is useful for documenting the measures taken in a transparent manner.
How often should AI training be repeated?
Article 4 does not specify a fixed statutory review period. An update is particularly advisable when new AI systems are introduced, tasks are modified, risks are identified, or legal requirements are amended. Regular refresher training ensures that the knowledge gained in training does not become outdated faster than the software itself.
Is general ChatGPT training sufficient?
Not necessarily. Training focused solely on how to use the application often does not provide sufficient knowledge about data protection, confidentiality, copyright, human oversight, labeling, or internal approval processes. It is crucial that the content is tailored to the specific context of use.
Can an AI Officer coordinate AI training sessions?
Yes. An AI Officer can centrally coordinate training needs, content, documentation, and updates. While this role is not required by law for every company, it can be an important part of effective AI governance.
AI training is effective when it translates knowledge into confident action. It should neither leave employees to grapple with legal provisions on their own nor lead them to believe that AI is merely a particularly polite search engine.
Companies need a training strategy that aligns with their applications, roles, and risks. When this strategy is combined with an AI inventory, clear guidelines, and a responsible governance function, the result is more than just documentation for the record: it creates the ability to use AI in a controlled and productive manner.