How to Build Data Privacy & AI Literacy in Organisation?
- 29/09/2025
Personal data protection is not only the task of the legal department or the Data Protection Officer (DPO). Every employee who works with personal data becomes part of the privacy ecosystem. This includes HR who know everything about employees, marketers who send email newsletters to users, and accountants who maintain their databases.
It’s impossible to build a sustainable and mature compliance system without an engaged team that understands risks, knows how to act in complex situations, make informed decisions, and sees privacy as one of the company’s key values.
But how to achieve this and equip employees with necessary knowledge? The answer is corporate training. Not the formal “reported and forgotten” kind, but systematic, adapted, regular, and engaging. It helps organizations comply with regulatory requirements, increases customer trust, reduces risks, and strengthens the internal privacy culture. This culture, in turn, gives a competitive edge and supports compliance from within, which ultimately makes life easier for the DPO.
In this article, we will discuss two main approaches to training:
1) Independent organization of training by the DPO or compliance team.
2) Delegating the task to external experts or training companies.
Each of these paths has its own advantages, risks, implementation features, and resource costs. We will examine both approaches in detail, and at the end, we will offer a comparative table and recommendations for choosing the optimal path for your situation.
The Importance of Data and AI Literacy
Reason 1: Regulatory requirements
Personal data protection laws in many jurisdictions require DPOs to conduct special training and upskill employees who have access to personal data.
In Article 39, employee training is one of the DPO’s responsibilities.
“The data protection officer shall at least have the following tasks:
<…>
to monitor compliance with this Regulation, with other Union or Member State data protection provisions and with the policies of the controller or processor in relation to the protection of personal data, including the assignment of responsibilities, awareness-raising and training of staff involved in processing operations, and the related audits;…”
This act requires that employees be familiarized with the requirements of the sections on personal data protection.
“Ensure that all individuals responsible for handling consumer inquiries about the business’s privacy practices or the business’s compliance with this title are informed of all requirements in Sections 1798.100, 1798.105, 1798.106, 1798.110, 1798.115, 1798.125, and this section, and how to direct consumers to exercise their rights under those sections.”
The EU AI Act and AI Literacy Obligations
The EU AI Act sets out a number of requirements related to employee training and development, particularly in the context of ensuring safety, regulatory compliance and using AI responsibly.
- AI Literacy
Employee training requirements are largely related to AI literacy, the importance of which is enshrined in Article 4 of the EU AI Act.
AI literacy programmes should:
- Support the development of an understanding of what ethical AI is and how it works.
- Raise awareness of the risks, benefits and ethical aspects of using Artificial Intelligence.
- Ensure informed human oversight and responsible use of systems.
These programmes should be designed for professionals, organisations or the general workforce (not limited to a technical audience). The European Commission also encourages the exchange of best practices in AI literacy.
2. Training within the Risk Management System (RMS)
For high-risk AI systems, which are subject to the most stringent regulation, providers are required to implement a Risk Management System (RMS).
Within the RMS, risk management measures must include providing necessary information and training for employees that are developing AI systems.
3. Promoting a healthy risk culture
Providers of general-purpose AI models with systemic risk (GPAI models with systemic risk) are required to promote a healthy risk culture.
This includes:
- Management setting the tone for a healthy systemic risk culture, for example by clearly communicating the Framework to staff.
- Ensuring sufficient independence for staff involved in assessing and mitigating systemic risk to encourage unbiased assessment of risks.
- Training to raise awareness of insider threat risks and how to recognise and report them.
In addition, to ensure accountability (Systemic risk responsibility allocation), management should control the allocation of appropriate resources (including human resources and access to information/knowledge) among those entrusted with systemic risk management responsibilities.
Reason 2: Risk of leaks and violations of data subjects' rights
Privacy is not just lawyers’ business. Leaks most often occur due to the lack of awareness of “ordinary” employees. The cause can be various methods of social engineering (which we have already discussed in this article), as well as simple negligence that arises from not understanding the value of privacy. We can provide a couple of examples of how this can happen. The first case is a real scenario that our colleague encountered while pursuing a second higher education degree.
During a class, their group was given drafts to complete a written assignment. Our colleague turned over the sheet and realized it was a copy of a document containing someone’s personal data. Other students also began looking at what was on the back of their drafts. Thus, the group compiled a complete portrait of a person: their identity, workplace, home address, and contact information. Would this have happened if the educational institution’s employees had undergone personal data protection training? We doubt it.
The second case is abstract but also occurs in real practice.
A client submitted a request to delete their personal data. The support department employee only deleted the profile from the CRM but didn’t initiate data deletion in other systems — archives, email, backups. As a result, the data deletion procedure wasn’t followed, and the subject’s rights were violated.
On the internet, you can find plenty of cases where large companies received fines due to leaks caused by employees. Here, for example, is one of them.
Reason 3: User trust
Corporate training is another way to show users that you carefully handle their personal data. Among news about leaks, you can stand out in the market and gain a competitive advantage. Organize training and publish content about it on your social media or blog. Or get a document confirming the completion of training from the company that conducted it for you and place it on your website. Such action will be a good PR move for the company.
Who needs training in Data Privacy and Ethical AI?
Diverse teams require different level of AI literacy and data privacy awareness.
For example, all employees who process personal data should complete basic data privacy training even if it is simply working with customer databases, questionnaires or email newsletters as marketing or sales team.
Some specialists require deeper diving into data privacy concepts learning not only GDPR fundamentals but also Data Act principles Among them:
- Data specialists.
- Digital product managers.
- IoT (Internet of Things) professionals.
- Cloud services providers.
- Legal professionals.
- IT specialists.
- Compliance managers.
- Business leaders.
Some employees require basic AI literacy training. Usually they are:
- AI users within the company (everyone who uses AI in their work: HR, marketers, doctors, analysts).
- Outsourced teams who work with your AI systems.
- Decision-making managers who make resolutions based on AI.
- People affected by AI (for example, employees whose applications are evaluated by AI) through informing.
But also there are teams who not only leverage AI to improve productivity, but buils AI systems and make it more secure for users. They could be:
- Compliance and AI governance managers.
- Corporate lawyers working with AI.
- Employees involved in deploying AI solutions in the EU.
- AI service providers.
- Developers of AI systems.
The ideal scenarion is delivering basic training programs within all teams to build the culture of responsible AI use and data privacy awareness.
Developing Customized Data Privacy & AI Training Programs
We’ve figured out why to conduct training. Now we need to understand how to do it.
First, let’s establish this idea: quality training is not just lectures. It’s a systematic program that covers:
📎 basic concepts: what personal data and privacy are, who data subjects and controllers are;
📎 regulatory requirements: basic principles of applicable legislation, rights of subjects, obligations of employees;
📎 corporate policies: what is accepted in the company, whom to contact when there are questions on the topic;
📎 scenarios and cases: how to act in case of a leak, subject request, incident;
📎 protection against social engineering: how to recognize phishing, pretexting, vishing, and how to respond to them.
It’s important that the training is adapted to roles. The contact center, marketing, and developers all work with personal data, but in different ways. A universal program will overload some and leave gaps for others.
Training should be regular, concise, practical, and… human. People remember stories better than articles from laws.
Next, we need to understand exactly how to conduct it. To figure this out, let’s consider two approaches.
Approach 1: Independent organization of training
Why choose this path?
Companies that already have a strong DPO or compliance team may want to take training into their own hands. This solution has an advantage: people “from within” better understand business processes and corporate culture. This helps to finely tune the course to the specifics of the business.
How to independently conduct personal data protection training in a team?
Step 1. Define training objectives
The goal is not just “to create a course for compliance“. A well-formulated goal might sound like: “Reduce the number of incidents related to improper processing of personal data by 30% within 6 months” or “Train 100% of employees with access to personal data on the key principles of applicable legislation“. Such goals align with the SMART principle: they are specific, measurable, achievable, relevant, and time-bound. In addition to regulatory compliance, goals can be aimed at forming an internal culture of responsibility or preparing for entry into a new market with different legislation.
Step 2. Assess risks and roles
Here, the first step is to conduct a Data Protection Impact Assessment (DPIA) or a less formalized audit of work processes. You need to understand which employees work with which types of data in which scenarios. For example, marketing department employees should know how to obtain consent for newsletters and how to manage unsubscriptions. The IT team — how to implement access restrictions and log operations. This forms a map of roles and typical scenarios that will form the basis of training modules.
Step 3. Choose the training format
Training should combine different formats:
📎 Online modules with interactive elements and automatic testing allow you to reach a large number of employees.
📎 Live sessions allow you to analyze cases, ask questions, and involve management.
📎 Training in a gamification format — quizzes, contests, interactive simulations — ensures material memorability.
📎 Auxiliary tools, such as posters, reminders in Slack, and newsletters, help keep knowledge up to date.
Step 4. Develop the main course materials
Content should be concise, clear, and relevant. Examples are what turn theory into action. For instance, a module on “responding to a data subject request” might include: a response template, a checklist of actions, and a short video analyzing the situation. Using internal cases and mistakes (without mentioning specific individuals!) increases trust in the training. Be sure to adapt materials to your team’s language and communication style. If your team loves cats in presentations, you can add them too! When it comes to quality training, all methods are good.
Step 5. Conduct testing and engage
It’s important not just to conduct training, but to understand how well the material has been absorbed. Use:
📎 formative testing (with explanations of answers);
📎 final module tests;
📎 practical cases on incident management or risk analysis.
To motivate the team — implement a reward system: badges, points, internal leaderboard.
Step 6. Measure results and continue updating the program
Training effectiveness doesn’t end with tests. Compare statistics:
📎 how many employees completed the training;
📎 how awareness has changed (based on test results);
📎 how many incidents or complaints have decreased;
📎 how much faster data subject requests are being processed.
Use employee feedback to improve the course. Update content based on changes in legislation or internal risks that have been identified.
Step 7: Deliver continuous learning practices
Here you should do anything to build culture of continuous learning and make knowledge accessible and easy to get:
- Add all materials to the knowledge base in your workspace (for example, our team prefers Notion: it is interactive and intuitive). Ensure that employees have easy access to it,
- Create a FAQ section with the questions that are most frequently asked by colleagues.
- Appoint privacy champions in teams. Not everyone will go to a lawyer, but they will go to a teammate.
Make training part of the routine.
Training works when it goes unnoticed, when it is integrated into processes. As new situations arise that require special attention, create new simple guidelines. When legislation is updated, notify your colleagues and give examples of how it affects their tasks.
You are not building a university. You are creating an environment where people know how not to break the law, even if they are not lawyers.
Sometimes simple training is the best training.
Approach 2: Delegating training to external specialists
Delegation is a rational choice if the company doesn’t have sufficient resources to create and maintain a quality training program. This is especially relevant in companies where:
📎 employees work in different jurisdictions and need to know the requirements of several laws;
📎 staff is limited, and the DPO doesn’t have the ability to allocate dozens of hours to course development;
📎 training needs to be conducted quickly, for example, before launching a new product or entering an international market.
How to organize training through a contractor?
Define training objectives
Formulate why the program is needed: to meet legal requirements, increase knowledge levels, or prepare the team for new tasks. Clear goals will help choose the right partner.
Choose a data protection expert
Look for a company that specializes specifically in privacy training. Experience working with different industries and jurisdictions is a big plus.
Share information about your company
Tell the contractor about your business processes, who works with personal data and how, in which countries you operate, and which services you use. This will help adapt the program to your needs.
Agree on the program and schedule
Approve the course content, duration, and schedule considering employee workloads. It’s important to find a comfortable solution for the team so that training doesn’t cause rejection but rather a desire for development.
Receive reports and certificates
After completing the training, employees will take tests and receive certificates confirming their knowledge and compliance with requirements.
You don’t need to worry about the technical part or constant monitoring of progress. All these responsibilities are transferred to the contractor.
How Can Our Team Help?
The Data Privacy Office Europe team offers a range of corporate courses across different areas, complexity levels, and jurisdictions. We specialize exclusively in personal data protection and AI compliance. This means our trainers’ expertise is deeper and broader than that of universal training providers.
💡We help companies:
📎 gain a basic understanding of personal data protection principles and AI literacy skills;
📎 understand new jurisdictions or compare approaches across several of them (for example, learn about the legislation of a market that is new to you and compare it with approaches from one your company has been working with for a long time);
📎 responsibly create and use generative AI tools like ChatGPT or others as well as use advanced prompt engineering techniques and get predictable and useful output.
Our team offers corporate programs that are customized to business needs and help elevate the level of privacy awareness in your team to a new level. Our training system drives innovation without making data protection complicated.
Visit our corporate training page and choose training for your team.
Which Approach Should You Choose?
The choice between in-house and outsourced training depends on context, process maturity, and resource availability. If you have a strong DPO with educational experience, documented internal policies, and a loyal, engaged team then organizing training in-house will be a good addition to your corporate culture.
If you’re limited on time, your team needs quick results, and the training needs to cover different roles and markets—bringing in experts will help shorten the path. This is especially relevant for companies entering new markets or working in sensitive areas (healthcare, fintech, educational platforms), where data handling errors are critical.
A compromise approach is combining both methods. For example, basic training can be conducted with an external contractor, while building a regular culture internally through messengers, stickers, internal initiatives, and recurring events.
To make it easier to weigh all the “pros” and “cons”, we offer you a table comparing both approaches to conducting corporate training on personal data protection.
Criterion | Independent Training by DPO | Training with External Specialists |
|---|---|---|
Content Control | Complete control — can be deeply adapted to company processes and culture. | Limited — adaptation is possible, but within the framework of ready-made solutions and contractor resources. |
Flexibility | Maximum — quickly make changes and adjustments. | Medium — changes require time and approval. |
Launch Time | Medium — requires time for development and preparation. | Quick — ready-made programs and experience allow for a fast start. |
Training Expertise | Depends on the qualifications of the DPO and team. | Professional — specialized methodologies and experience. |
Content Relevance | Depends on the team—needs regular updates. | Regularly updated by the contractor taking into account legislative changes. |
DPO Time Investment | High — significant time for preparation and delivery. | Minimal — DPO is involved only in initial organization and project support. |
Cost | Lower — no direct costs for external contractors. | Higher—service expenses. |
Engagement Level | High — DPO better understands internal specifics. | High — due to professional trainers and interactivity. |
Post-Support and Follow-up | Usually absent or limited. | Available — consultations, updates, support after training. |
Scalability | Depends on company resources. | Good — can train large teams across multiple jurisdictions. |
Conclusion
Privacy is not a project but a process. And its success depends not on a policy or DPIA template, but on the people who make decisions about personal data protection every day.
By investing in training, you’re investing in security, trust, sustainability, and competitiveness. You can do this independently or with partners — the important thing is that training actually happens and is effective.
Whichever path you choose, remember: privacy is a team sport. And every player needs to know the rules.
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