By Hinda Haned and Maeve Hosea

Have you been experimenting with chatbots, writing code, pulling research reports together, or summarising documents using ChatGPT, Gemini or Claude? Maybe you have a curiosity and appetite for understanding what AI can do for you, or maybe you feel like if you fail to engage with it, you’ll be left behind.

In either case, you have probably been asking yourself how to improve your skills so you can use these tools more effectively. Chances are, you turned to online resources to improve your AI literacy skills, but despite the abundance of these resources and training programmes focused on AI literacy, it can still be hard to identify which offerings best align with your specific needs, role or background.

In fact, many available courses and tools are designed with broad audiences in mind, lacking customisation for particular industries, job functions or levels of prior knowledge. This makes it difficult for learners to pinpoint content that is directly relevant to their daily responsibilities or career goals. In addition, the rapid pace of AI advancement, combined with extensive media coverage, creates a disconnect between research breakthroughs and practical workplace applications.

Individual contributors may feel overwhelmed by constant AI discussions and conclude that keeping up with the rapid pace of change is almost impossible, potentially reducing their engagement with these technologies.

What is AI literacy and why do we all need it?

If we define literacy as the ability to read, write, speak and listen effectively in order to communicate and engage with the world around us, AI literacy is the ability to understand, use, monitor and critically reflect on artificial intelligence applications and how they are changing our lives.

It has become a vital skill for individuals across different roles and industries. In the EU, under the AI Act, which seeks to foster responsible AI use alongside supporting AI innovation, it is now a regulatory requirement, compelling organisations to ensure their workforce is adequately trained to use AI tools and understand their risks and limitations.

While it’s unrealistic to try to keep up with all state-of-the-art AI-driven technologies that might be relevant to your role, understanding how to best learn about AI, where to look, how to evaluate sources, and how to ask the right questions, is a far more valuable and sustainable skill.

In a rapidly evolving landscape, developing this kind of adaptive learning mindset, where you frame challenges as opportunities rather than obstacles, enables you to make informed decisions, engage meaningfully with AI developments, and collaborate effectively with technical experts, without needing to become one yourself.

A practical three-step approach to boosting your AI literacy

1. Get the fundamentals right

Start with a solid understanding of what AI is and, just as importantly, what it is not. Much of the hype surrounding AI conflates it with general intelligence or assumes it is a magic solution to every problem. In reality, many so-called AI solutions are simply advanced data-driven decision-making tools.

To make AI meaningful in your context, reflect on how your team or organisation currently uses data. Are decisions based on intuition, spreadsheets or dashboards? For example, could enhancing existing dashboards through automation or predictive analytics deliver greater value? Framing AI as an enhancement to existing workflows makes its use more practical and grounded.

2. Prioritise productivity over technical proficiency

You don’t need to become a machine learning engineer to benefit from AI. In most roles, understanding how AI tools can make your work more efficient is more valuable than learning to build them. Focus on real-world applications such as drafting content, summarising reports and automating repetitive tasks, rather than coding or model training.

3. Develop critical thinking around AI

Critical thinking is, arguably, one of our most valuable human strengths. One essential skill everyone should build is the ability to ask thoughtful, critical questions about AI and its impacts, especially around responsible AI, fairness and ethics.

As AI becomes more embedded in decision-making, it’s important to reflect on how systems are built, what data they rely on, and what outcomes they produce.

A simple three-month learning path

From our combined experience in supporting the development and design of AI literacy courses for clients across different industries, we understand that the most effective AI literacy programmes focus on clear, simple and actionable steps for individuals and organisations.

In practice, here is what this could look like for you:

Month 1: Get the fundamentals right

Essential skills to develop

  • Ability to explain key AI concepts such as machine learning, natural language processing and generative AI, and identify their relevance in different fields.
  • Core understanding of what constitutes AI versus what is merely data-driven technology.
  • Differentiation between various machine learning types, including supervised, unsupervised and reinforcement learning, and their applications.
  • Skills to critically evaluate misinformation about AI capabilities and applications.

Resources we like and recommend

  • The Elements of AI by MinnaLearn and the University of Helsinki, a free online course offering accessible AI fundamentals without requiring complex maths or programming skills.

Month 2: Prioritise productivity over technical proficiency

Essential skills to develop

  • Skills to identify repetitive tasks that can be handled by AI, freeing time for more strategic work.
  • Techniques for crafting effective prompts to maximise results from generative AI tools.
  • Understanding how to incorporate AI tools into existing workflows and organisational systems.

Resources we like and recommend

  • Motion, which has tested 50 productivity tools and provides a comprehensive overview of their features, strengths and ideal use cases.
  • LinkedIn Learning’s Career Essentials in Generative AI, a training path covering practical applications from AI ethics to Microsoft Copilot integration.

Month 3: Develop critical thinking around AI

Essential skills to develop

  • Understanding of AI ethics principles including fairness, accountability, transparency and human rights considerations.
  • Learning about the harmful impact of AI and understanding what algorithmic bias is.
  • Learning to critically reflect on the broader implications of AI deployment on society, privacy and human labour.

Resources we like and recommend

  • Ethics of AI, a free online course from the University of Helsinki covering responsible AI principles and ethical frameworks.
  • Critical Thinking for the ChatGPT Era, a neuroscience-based approach to strengthening critical thinking skills specifically for AI interactions.

Going further

Where are you in your AI literacy journey? Are you just getting started, experimenting with tools, or looking to deepen your understanding? What’s the biggest challenge you face: finding time, knowing what to learn, or figuring out what’s actually relevant to your role?