The interest in introducing artificial intelligence in contexts of learning and instruction is not new. Early attempts to understand the relationship between cognitive aspects of learning and artificial intelligence have been documented as early as in the 1950s. Since then, other aspects of learning and instruction in the context of AI technologies have been investigated. Many of these early tryouts did not succeed as expected and could not be implemented. However, technological leaps in the field of AI during recent decades have led to the emergence of technologies with strong capabilities when it comes to supporting communicative aspects of learning and instruction. In the early 2020s, the emergence of generative AI (Gen AI) technologies resulted in a renewed interest in these issues. Chatbots and virtual assistants entered the scene at all levels of educational systems and are widely used in non-institutional settings as well. Recent tryouts show promising results in terms of the capabilities of Gen AI technology when it comes to supporting learning and instruction in a lifelong and lifewide perspective, all the way from contexts of formal instruction in early childhood to informal learning at work and in other settings. These studies have been concerned with issues of how Gen AI technologies can support micro-level, processual aspects of learning and instruction in classroom settings, as well as their potential for addressing more macro and meso-level issues concerning institutional aspects of the functioning and organisation of educational systems.This symposium discusses some of the many issues of learning and instruction that are raised in relation to the recent developments of Gen AI. Four papers are presented by researchers collaborating in an EARLI Centre for Excellence in Research (ECER), AI in Learning and Instruction: Challenges, Opportunities, Transformations (AILI). The first paper by Justin Edwards, Márta Sobocinski, Joni Lämsä and Sanna Järvelä, Aligning with AI - Lexical Alignment Between Collaborative Learners and an AI Mediator, focuses on a tryout in a 7th-grade physical classroom setting. It takes a micro perspective and analyses the lexical alignment between AI agents and collaborative aspects of learning. Also, the second paper, Teacher CoPilot: AI-based Training and Support System in Teacher Education written by Sabine Seufert, explores Gen AI from a micro-level perspective, this time in a higher education setting. It analyses a tryout where a Gen AI teacher copilot intervened to afford the development of higher education teachers' technological, pedagogical and content-related competencies, so-called TPACK. The third paper by Marcus Sundgren, Susanne Sahlin, Rebecca Marrone, Maarten de Laat and Jimmy Jaldemark explores the institutional implications of Gen AI by focusing on issues of the organisational readiness of school principals for adopting Gen AI in their everyday practices. As is the case in the study by Seufert above, the final paper, written by Ylva Lindberg and Anders Buch, focuses on higher education institutions (HEI) and explores how HEIs respond to the requirements of providing teachers and students with guidelines for the future in the heavily contested area of what AI implies for education and learning.