Research on Technology-enhanced Learning (TEL) has mostly considered, how certain pedagogical functions can be enhanced or supported by technological means. As technologies increasingly become inherent parts of learning and teaching practices, this functional perspective towards the role of technologies in learning is to some extent limited because it underestimates the role technologies can have in the transformation of whole work and learning practices from a systemic perspective. Through the lens of recent models of hybrid intelligent systems, we explore the impact that AI will have on the teaching profession. Through the analysis of six cases that cover a broad range of applications of AI in teaching across a set of educational contexts, we show how AI will replace, complement and augment teaching tasks and thereby affect professional knowledge, skills and attitudes of teachers. Importantly, in a hybrid intelligent system, interactions between actors (human and artificial) will be bi-directional. We propose a framework on teacher-AI complementarity that can guide future research in this area. We also identify some of the important conditions for complementarity, e.g. on how technology is designed, developed and deployed, and how teachers are prepared.