Many engineering programs initially responded to generative AI by trying to restrict student use, mainly to protect academic integrity, while work life demands AI-literate graduates across all disciplines and regulation such as the EU AI Act raises requirements for transparency, safety and accountability. Against this backdrop, Chalmers University of Technology has developed a university-wide Strategy for Digitalization and AI in Education that shifts focus from blocking AI to systematically integrating digitalization and AI into curricula, learning processes, pedagogy, faculty competence, support services and the digital infrastructure. A central feature is a three-level learning-outcome model (“for all, for many, for some”) that guarantees basic digital and AI literacy for every student, offers discipline-specific deepening for many, and provides advanced expertise for some in specialized master’s programs. Pedagogical principles stress that digital tools and AI should support rather than replace student thinking and effort, and that assessment must remain valid and fair in an AI-rich environment. The strategy, grounded in current-state and SWOT analyses, is implemented through Chalmers’ matrix governance with program-level ownership, shared guidelines, coordinated faculty development, and investments in infrastructure. The paper presents the strategy as a roadmap for aligning pedagogy, regulation and labor-market demand, and discusses implications for curriculum design, assessment and faculty competence.
