Abstract The accelerating prevalence of generative artificial intelligence in educational and professional spheres necessitates a reevaluation of when and how such technologies are introduced within pedagogical practice. The principal challenge for educators is not merely the imperative to prepare students for an AI-driven world, but rather to ensure that assessment practices remain authentic—providing an accurate measure of what students can independently achieve before leveraging the augmentation potential of intelligent systems. This article contends that the incremental introduction of AI, mapped onto a scaffolded framework aligned with a revised Bloom’s Taxonomy, constitutes a methodologically sound approach for maintaining academic integrity, fostering transferable skills, and developing true AI literacy. In this model, student abilities and conceptual knowledge occupy a privileged position; only after demonstrable independent proficiency can AI tools be used to extend, refine, and synthesize student work. This phased model is not merely a theoretical exercise, but an actionable policy framework that incorporates formative assessment, transparency, process documentation, and ethical use as core design principles. By situating AI as both a tutor and collaborator—never a surrogate for student cognition—educators can ensure that learners are equipped to navigate the epistemological, ethical, and professional challenges of a world shaped by automated intelligence. The analysis draws upon constructivist pedagogy, authentic assessment theory, Universal Design for Learning, and current research on educational technology adoption, proposing practical strategies to preserve both rigor and relevance in a rapidly evolving landscape.