AI literacy and the EU AI Act: What you need to know

Over the past few years, data and AI have become essential components of decision-making, innovation and competition. AI models are often complex and not easy to interpret by users and regulators. How do we ensure that AI is used in an ethical, transparent and responsible way?

The EU AI Act is an important step in the regulation of AI within Europe. It sets clear frameworks for organizations and professionals developing or basing decisions on AI. One of those frameworks is that users are required to have some degree of AI literacy. This makes AI literacy not only a strategic advantage, but also a necessary competence.

Yet at the same time, AI literacy extends beyond regulation. It requires understanding of how data and AI intersect, how to effectively deploy and analyze data, and how to develop responsible applications. The Data Science & AI Essentials program at JADS offers professionals the opportunity to develop these skills in an academically based and practically applicable framework.

The EU AI Act: What does it mean for professionals and organizations?

The EU AI Act is the world’s first large-scale legislation to regulate the development and use of AI. It has implications for companies, government agencies and professionals working with or using AI systems in their decision-making.

The legislation takes a risk-based approach, classifying AI systems into four categories:

• Unacceptable risk – AI applications that violate fundamental rights, such as social scoring by governments, are banned.
• High risk – AI systems in critical sectors (such as healthcare, finance and HR) must meet strict transparency and accountability requirements.
• Limited risk – AI systems such as chatbots and deepfake technology must meet certain transparency requirements.
• Minimal risk – AI applications with no major impact on rights and freedoms, such as recommendation systems on streaming services, remain largely unaffected.

Risk piramid (source: European Commission)

For organizations, this requires, among other things, critically evaluating their AI systems for aspects like interpretability and possibly adjusting processes to comply with the legislation. As of Feb. 2, 2025, organizations that develop or use AI systems are required by law to ensure an adequate level of AI literacy among their employees and other individuals using AI systems on their behalf. This means that employees must have sufficient skills, knowledge and understanding of both the technical operation of AI systems and its social, ethical and practical aspects.

For professionals, it means that basic knowledge of AI and data science becomes a necessity to understand where the risks and opportunities lie.

AI literacy: more than just regulations

AI literacy is not just about compliance with new legislation. It is about understanding data, algorithms and the impact of AI on decision-making. This is crucial in sectors such as healthcare, logistics, finance and public services, where AI and data science are increasingly being used.

A professional understanding of AI and data science includes:

• Data-driven decision-making – How do you harness data to generate valuable insights?
• Algorithmic transparency and ethics – How do AI models work, and what biases and risks can occur?
• The relationship between data and AI – AI is only as good as the data it works with; how do you ensure reliable and representative data sets?
• AI in practice – How do you integrate AI tools into existing processes, and how do you analyze their effectiveness?

For professionals working with AI on a strategic level, or just dealing with technical implementation, a broad foundation in both AI and data science is indispensable.

How the Data Science & AI Essentials program at JADS contributes to AI literacy

The Data Science & AI Essentials program is an academically based, hands-on program that helps professionals integrate AI and data science into their professional fields. In five days, it provides a thorough introduction to the principles, techniques and applications of data science and AI.

The format of the program is broad and in-depth:

• Day 1: Introduction to Data Science & AI What does it mean to be a data-driven organization? We begin with a broad exploration of the field of data science and AI.
• Day 2: Digital Business Models We look at the latest developments and innovative business models
• Day 3: Data Engineering This day focuses on the practical side: how do you organize and structure data?
• Day 4: Data-driven decision-making We cover the basics of data analysis and models.
• Day 5: Generative AI You will learn how to integrate this technology into your business. We also discuss the ethical and legal risks.
• Day 6: Implementing Data and AI Solutions Participants present their plans and define the next steps for successfully applying data science and AI

Through a combination of interactive lectures, practical cases and group discussions, you will not only gain theoretical knowledge, but also concrete tools to apply AI and data science within your own organization.

Looking ahead: What does AI literacy mean for the future?

Looking ahead: What does AI literacy mean for the future?

As the implementation of AI in organizations grows, so does the demand for professionals who can understand and use this technology responsibly. The EU AI Act marks a shift: AI is no longer a free zone, but a technology subject to strict regulations and ethical guidelines.

This requires not only compliance, but more importantly, a broader awareness of AI and data science within organizations. Whether you work in strategy, IT, legal, marketing or operations, AI literacy is becoming increasingly important.

The Data Science & AI Essentials program at JADS offers an academic, hands-on route to building this knowledge. Do you want to better understand how data and AI affect your work? Do you want to be able to make sense of the impact of AI regulations? Then this program is a valuable investment in your professional development.

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