Background
Generative AI has become a continuous source of change in our society. Inevitably, this has an enormous impact on teaching and learning, with adoption happening at a diverging pace. While some excitedly rush to embrace opportunities, others warn of threats and challenges related to unequal access, model hallucinations, biases in models, environmental cost, etc. In the rapidly evolving technological landscape, both innovative approaches and reflections on the state of affairs are needed to foster an adaptive, inclusive, and future-ready educational ecosystem. Generative AI has grown far beyond the traditional boundaries of computer and data sciences and has become relevant to all of our society. This is why an interdisciplinary and holistic approach towards developing AI literacy is crucial for sustainable education and learning. This is particularly so considering the broad spectrum of methodologies in education from formal sciences to humanities, from cognitive to physical, from coaching to self-directed learning.