In the context of global knowledge economy competition and accelerated technological revolution, artificial intelligence (AI) technology is profoundly reshaping the education ecosystem and driving a paradigm shift in the cultivation model for top-tier innovative talents. This paper systematically analyzes the practical challenges in cultivating elite innovative talents during the AI era from dual perspectives of national education strategy and global competition for scientific and technological talent, proposing innovative pathways for talent development. The research identifies six major challenges: disciplinary barriers and fragmented development of competencies, segmented education stages and diminished innovation potential, rigid cultivation systems conflicting with talent characteristics, data silos and distorted competency profiling, role fixation undermining human-AI collaboration, and local limitations creating global competency gaps. The paper proposes innovative pathways in six dimensions: interdisciplinary integration with hierarchical classification, stepwise growth channels, flexible academic systems, intelligent evaluation with industry-education integration, collaborative educational paradigms, and international cultivation platforms. This study provides theoretical foundations and practical references for addressing inherent contradictions in traditional education models and securing competitive advantages in global talent competition.