AI Literacy Training
A comprehensive training for both employees and management to effectively and responsibly implement AI within your organization. From practical AI applications to strategic implementation and compliance, this training provides a complete overview of everything you need to know about AI in practice.
EU AI Act compliance: From February 2, 2025, the European AI Act requires demonstrable AI literacy for anyone working with high-risk AI. Recruiters using CV screeners, bankers managing credit models, healthcare teams running triage apps: all have the same obligation — understanding what the algorithms do, what errors they can make, and how to correct them.
Our one-day training establishes exactly that foundation. We build the session in a modular way: one shared core and sector-specific deep dives in separate breakouts. This way, you get customization without having to book five separate workshops.
AI Risk Zones per Sector: EU AI Act Priorities
The table below shows which sectors have priority under the EU AI Act, and why these specific sectors need special attention for AI compliance.
| Priority | Sector / Domain | Reason (“why now?”) | Typical high-risk use-cases (Annex III) |
|---|---|---|---|
| Tier 1 | Financial services (banks, insurers, fintech) | Strong EU supervision frameworks (EBA, DORA); reputation risk | Credit scoring, transaction monitoring, biometric KYC |
| Healthcare & med-tech | MDR connection; patient safety | Diagnostic support, AI triage, robot surgery | |
| Public sector (ministries, municipalities, executive agencies) | Political pressure for transparency; procurement requirement for AI Act compliance | Risk assessments (benefits), crowd monitoring, chatbot services | |
| HR-tech / Recruitment services | Annex III explicitly mentions AI in recruitment & selection | CV screening, video analysis, performance tracking | |
| Critical infrastructure (energy, transport, air & rail) | Safety component → automatically high-risk | Predictive maintenance, traffic control | |
| Tier 2 | EduTech / Universities & colleges | Annex III education systems → high-risk | Proctoring, adaptive learning |
| Manufacturing & logistics | Rapid AI adoption; OSHA & CE requirements | Vision inspection, autonomous vehicles | |
| Tier 3 | Scale-ups building generative AI products | IP risks & brand reputation | Chat co-pilots, content generation |
HR & Recruitment – where the chain reaction begins
The Challenge
Why here specifically? The law explicitly mentions selection AI, because a faulty algorithm can literally exclude someone from the job market. Recruiters are therefore the first line of defense against bias and the first to be fined if they blindly trust their dashboard.
The Approach
What does the training look like? We start with a live bias scan on your own CV filter: twenty anonymous profiles, one ranking model, ten minutes of suspense. The outcome forms the red thread for the rest of the morning. We discuss transparency towards candidates ("You are being screened by AI") and practice human overrides – including the log texts that an auditor wants to see. Favorite take-away from previous participants: the "explain sheet" with which recruiters can explain in three sentences why candidate X was rejected anyway. According to Sanne Derksen, Head of Talent Acquisition at a fintech scale-up, "that sheet pays for itself in one day in credibility with candidates and hiring managers."
Finance – compliance is culture, AI adds a new layer
The Challenge
What's at stake? Credit scoring and anti-fraud models naturally fall into the high-risk box. Fines of up to seven percent of global revenue sound louder in boardrooms than any keynote on innovation.
The Approach
What do we do in the break-out? We introduce a fault in a fictional credit model: a bias alert on postal code 1092. The group decides live whether the model pauses, how that appears in the ISAE-3402 reporting, and what customer communication follows. In between, participants learn how to link AI Act documentation to existing risk frameworks, so there isn't yet another compliance layer on top, but one integrated story.
Healthcare & Med-tech – no algorithm may break patient trust
The Challenge
Why is the bar highest here? A triage app or decision-support tool can make the difference between treatment or not. Errors are not only paid for with money, but with reputation and sometimes lives.
The Approach
How do we make it tangible? We simulate an emergency scenario: the AI advises sending patients with mild symptoms home, but the attending physician has doubts. The group goes through a real-time decision tree: open log files, force second opinion, inform patient. Afterwards, we trace the input to concrete improvement actions: additional training data, explanation module for nurses, and an escalation button for doctors.
Public Sector – transparency is the default, not the exception
The Challenge
The tension: strict procurement rules, media sensitivity, and a critical citizen. A seemingly simple resident chatbot can make headlines if it gives legal advice it's not authorized to give.
The Approach
The workshop essence: We dissect an existing municipal chatbot. In teams, we rewrite the opening message ("I am an AI assistant, not a lawyer"), define trust boundaries, and consider what happens when the answer is NOT certain. Result: a concrete blueprint of transparency and fallback rules that can go live the same day.
Critical Infrastructure – when downtime is not an option
The Challenge
Why extra exciting? An incorrect prediction in a predictive maintenance model can shut down a turbine or, worse, put people at risk.
Critical infrastructure includes essential services and systems such as energy, water, transportation, telecommunications, and cybersecurity that are indispensable for the functioning of society. These sectors automatically fall into the highest risk category of the EU AI Act due to their societal impact in case of disruptions.
The Approach
What we do: We present an imaginary malfunction: sudden temperature spike, the model is uncertain. The group decides whether the asset goes offline, what the incident log looks like, and how the operator explains why the AI became confused. This immediately addresses the core question of the AI Act: how do you explain a black-box model to a human operator?
What You Will Learn
Organizational Implementation
- Develop an effective AI strategy for your organization
- Identify promising AI applications within your work processes
- Create support and overcome resistance to AI
- Create a phased implementation plan for AI adoption
Policy & Governance
- Develop an organization-wide AI policy
- Create practical guidelines for responsible AI use
- Implement effective control mechanisms
- Balance innovation and risk management
Compliance & Risk Management
- Understand the EU AI Act and its impact on your organization
- Implement privacy-by-design principles in AI use
- Identify and mitigate AI-related risks
- Ensure transparency and explainability of AI systems
What It Gives You
What You Can Expect
Preview of the AI Literacy Training
View some slides from the training to get an impression of what you can expect.
What is AI Literacy?
AI literacy is essential for every modern organization, especially with the introduction of the EU AI Act:
Definition of AI Literacy
AI literacy means that employees have sufficient understanding of:
- How AI systems work and their capabilities
- The impact of AI on daily work activities
- Responsible use of AI tools
- Recognizing opportunities and risks
- Effectively collaborating with AI systems
Benefits
- Increased productivity
- Better decision-making
- Competitive advantage
- Compliance with legislation
Legal Context
- EU AI Act requires AI literacy
- Mandatory for organizations using AI
- Part of compliance and risk management
Your Trainer
Zahed Ashkara
AI Trainer & EU AI Act Specialist
As the founder of Embed AI, Zahed combines his expertise in artificial intelligence with a passion for innovation. With his legal background and extensive knowledge of AI technology, he helps organizations with their digital transformation.
As an EU AI Act specialist and certified AI Compliance Officer (CAICO), he helps organizations implement AI systems that comply with the new European legislation.
Zahed's unique combination of legal expertise and technical AI knowledge makes him the ideal trainer for this training. His practical approach ensures that you not only understand the theory, but can also apply it directly within your organization.
Investment
Included:
- Comprehensive training materials
- Lunch and refreshments
- Certificate of participation
- Implementation plan template
- Practical guides and checklists
- Reference materials and documentation
Optional extras:
- + € 4,500,- In-company training (max. 15 participants)
- + € 250,- Additional participant for in-company training
Available discounts:
- Early-bird discount (>2 months before start) (10% discount)
- Organization discount (3+ participants) (15% discount)
Available Dates
may
june
july
august
What Participants Say
“I found the AI Literacy course really informative and easy to follow. It gave a solid overview of how AI works, where it's being used, and some of the risks and ethical issues to keep in mind. As an internal auditor, it helped me understand how AI might affect things like internal controls, data handling, and risk areas. It's definitely made me more confident when it comes to discussing AI-related topics at work. A really useful course overall, highly recommended!”
“Zahed is a professional and skilled trainer who, with his substantive knowledge and practical approach, knows how to thoroughly understand and explain complex topics. Much is still unclear about the European AI Regulation, but the masterclass provided clarity regarding the legislation and its impact on companies. I gained a better understanding of the risk categorization for AI models and the (legal) requirements associated with them. The practical approach, combined with technological insight, makes this a valuable training that I recommend every legal professional to follow.”