Artificial intelligence, powered by exponential growth in computing, algorithms and data, is pushing higher education to a tipping-point “where social and technological evolutions occur in sync”. The five laws of ecology—adaptability, diversity, balance, dynamism and co-evolution—now serve as “survival rules” for university teachers facing this disruption. Adaptability forces instructors to let syllabi mutate in real time with disciplinary frontiers and social needs. Diversity demands that they carve out differentiated niches for students of varying cognitive styles; balance reminds them to keep human-AI collaboration in equilibrium between algorithmic decisions and value judgments. Dynamism converts learning-behavior data into energy flows that fuel continuous innovation; co-evolution turns teachers into “ecosystem engineers” who, together with students and intelligent agents, form a tripartite, mutually enhancing organism. These laws converge into a six-dimensional symbiotic ecosystem: “digital textbooks, resources, methods, environments, assessment and relationships”. At the textbook level, living, cross-disciplinary, course-clustered digital texts evolve continuously; at the resource level, generative large models maintain “a cloud repository” that updates in real time, is context-rich and customisable. At the method level, human-AI “dual-teacher” instruction meets multi-time-zone, multi-campus and multicultural demands. At the environment level, multi-modal, data-driven, context-aware “smart brains” turn “every scene into curriculum and every space into a learning companion”. At the assessment level, an “evidence-algorithm-ethics” balanced loop integrates multi-source data, multiple stakeholders and multi-stage feedback. At the relationship level, “the teacher-student-AI” triad co-evolves: teachers become learning designers and value guardians, students self-construct knowledge, and machines act as cognitive partners and ethical mediators. Amid simultaneous shifts in social and educational ecosystems, university teachers must urgently upgrade their AI literacy, data ethics and lifelong learning capacity; universities should accelerate the intelligent upgrading of infrastructure, governance and culture; education authorities must formulate forward-looking standards, regulations and incentives to steer higher education toward greater inclusivity, innovation and sustainability in the age of artificial intelligence.