AI Literacy Fundamentals

Understand AI. Challenge AI. Shape AI.

At Luar Labs, we combine technical expertise with humanistic thinking because we understand all technologies are social at their core. This perspective matters deeply: the vast majority of data and AI initiatives fail not because of the technology, but due to human factors.

Our approach is grounded in over a decade of experience driving data-informed decision-making and shaping AI strategies within global organizations. It is also informed by leading frameworks and evolving regulation, including the EU AI Act.

We deliver foundational AI Literacy training for all levels of technical fluency, alongside industry-specific workshops and tailored upskilling programs designed to meet the needs of your organization.

Format: In-person (Switzerland) or remote

Languages: English, Spanish, German

Customization: By industry, team, or strategic focus

Explore our AI Literacy Fundamentals building blocks below and contact us for a custom plan.

  • Cut through the hype. Build real understanding.

    • What AI is and isn’t
      Go beyond buzzwords. Explore the spectrum of technologies under the AI umbrella and debunk common misconceptions.

    • A brief history of AI
      AI isn’t new. Learn how recent breakthroughs fit into a long history of automation and data-driven decision-making.

    • Opportunities and risks
      Understand both the potential and the pitfalls through the lens of human–AI collaboration and systemic impact.

    • Contextualized learning through real examples
      Develop an intuitive understanding through examples tailored to your industry.

  • Develop the critical mindset for responsible, high-impact use.

    • Human–AI collaboration
      What the research tells us and what experience confirms. Understand how humans and AI can think together.

    • AI is sociotechnical
      Understand the bigger picture. AI systems operate within broader systems shaped by culture, values, context, and organizational realities.

    • When AI fails
      All models are wrong, some are useful. Learn to question assumptions, spot hidden gaps, and work with uncertainty.

  • Don’t let AI just “happen” to your organization — lead its integration with intention and clarity.

    • Comprehensive AI integration

      AI adoption touches every part of your business: from governance and data infrastructure to ethics and employee culture. Build a holistic understanding of what’s required and understand the building blocks you already have.

    • AI requires dynamic organizations

      Learn how to design internal feedback loops and processes that help your organization course-correct, stay aligned with values, and remain adaptive as technologies keep evolving.

    • Empowering domain experts

      The fuzzy limits of AI are only discoverable by subject-matter experts. Learn to meaningfully and confidently manage and improve AI to fit the context of your role.