The increasing integration of artificial intelligence (AI) into education is often presented as a means of modernization, efficiency, and improvement. At the same time, criticism of AI in education frequently focuses on the limitations of specific tools, with problems such as hallucinations and related deficiencies treated mainly as signs of technological immaturity. However, in postdigital educational conditions, where digital and non-digital practices are closely intertwined, such approaches may obscure a more fundamental methodological question: what exactly is being optimized, and at what cost to the educational process? This chapter offers a conceptual and reflective analysis of AI in education that moves beyond the evaluation of tools or performance indicators. It examines an underexplored dynamic in contemporary educational discourse: the gradual reorganization of educational practice around procedural success, measurable outcomes, and automated decision-making. Rather than approaching education as a system of delivery, control, or service optimization, the chapter interprets it as a knowledge-generating structure in which learning depends on participation in epistemically productive processes. To clarify this dynamic, the analysis draws on an engineering metaphor of education as a bridge between existing knowledge and future human potential. On this basis, it identifies two systemic mechanisms through which AI may reshape educational systems: the redistribution of load and the reorganization of knowledge-generating processes. Within this framework, knowledge substitution describes situations in which epistemically productive processes are displaced by technologically optimized procedures that imitate their results while reducing the learner’s engagement in the formation of understanding, judgment, and meaning. The argument is not that AI inevitably harms education, but that certain modes of implementation may weaken the epistemic integrity of learning when optimization targets the very processes through which educational development takes place. By foregrounding epistemological and methodological considerations, the chapter offers a conceptual framework for analyzing how AI reshapes educational processes, identifies key mechanisms of structural transformation, and clarifies the conditions under which technological support may shift into substitution.