Integration of artificial intelligence with genome editing: A new era for molecular plant breeding

The convergence of artificial intelligence (AI) and genome editing technologies marks a transformative frontier in molecular plant breeding. AI, with its capacity for data integration, pattern recognition, and predictive analytics, significantly enhances the precision and efficiency of genome editing tools like CRISPR-Cas systems. By harnessing AI algorithms, researchers can identify key genetic targets, optimize guide RNA design, and predict off-target effects, thereby accelerating trait improvement and crop development. This synergy enables the rapid development of climate-resilient, high-yield, and disease-resistant plant varieties. Moreover, AI-driven models facilitate the analysis of vast genomic, phenotypic, and environmental datasets, offering insights into complex gene-trait-environment interactions. The integration of AI with genome editing not only streamlines molecular breeding pipelines but also opens new avenues for sustainable agriculture and food security. This review explores recent advances, challenges, and future prospects at the intersection of AI and genome editing, highlighting its transformative potential in the next generation of plant breeding.