The world population is expected to surpass nine billion by 2050, necessitating a 70% rise in food production to satisfy the anticipated population growth. The Earth’s average temperature has risen by 1.2 ± 0.1 °C compared to preindustrial times, attributed to increased CO2 emissions into the atmosphere. Climate change is leading to various noticeable impacts on agriculture and food production. Occurrences of plant diseases present major risks to worldwide food security and ecological sustainability. We have reached Breeding 4.0, where the cost of genome resequencing might be lower than that of a replicated yield trial, and genome editing is anticipated to allow multiple accurate modifications at different sites. High-throughput phenotyping enables the evaluation of many characteristics with excellent spatiotemporal accuracy, while machine learning techniques permit the analysis and understanding of agricultural data beyond human capacity. The emergence of transgenic plants that are now accessible worldwide occurred afterward. Recently, CRISPR-based editing of plant genomes has been utilized to identify precise breeding goals. In the last 25 years, progress in sequencing technology has initiated a new era in plant breeding. Since the sequencing of the first plant genome (Arabidopsis thaliana) 24 years ago, numerous crop genomes of greater complexity and size have been decoded. Research on pangenomes, concentrating on species diversity via extensive genome sequencing, has uncovered genetic differences in essential traits because of deletions, insertions, and different types of chromosomal changes. Understanding of species and alleles is advancing alongside progress in pangenome research. Plant breeding is yet to adopt new “omics” techniques fully for assessing genetic worth, mainly due to their significant expense. Genetic diversity is essential for future progress in genetics, and new technologies like CRISPR provide potential in creating useful genetic diversity that consumers willingly embrace for future genetic improvements. Progress in next-generation sequencing (NGS) has opened doors to a new era of varied omics, including genomics, transcriptomics, and proteomics. However, crop science has extensively documented metabolomics, ionomics, and phenomics as well. High-throughput methods that combine various omics techniques have been crucial for understanding development, aging, productivity, and reactions to various stresses in multiple crops. Genetic diversity is crucial for cultivating plants. To improve diversity, our knowledge of the molecular genetic processes involved in crop domestication has to significantly progress with the emergence of next-generation sequencing. Speed breeding technology has emerged as a technique that modify the environmental conditions for crop plants to accelerate their breeding processes by enhancing flowering rates and seed yield with the aid of artificial intelligence (AI). The commencement of meiosis in mitotic cells provides a key benefit by greatly reducing the duration of the breeding cycle. Breeders must create thorough data-driven precision breeding programs that encompass genotype–phenotype–environment multiple factors. This approach will facilitate gene editing, synthetic biology, and numerous technological advancements, enabling precise and effective enhancements in developing new varieties while fostering accuracy, intelligence, and an industrial-focused seed transformation. In Plant Breeding 5, each phase from breeding design to phenotype prediction is executed automatically through Deep Learning (DL). Extra stages could be added if new technologies emerge in the future. Nonetheless, breeders encounter constraints regarding their comprehension of the process of plant development. Enabling crops to flourish naturally in their environment is a crucial element of research. Breeders have defined duties in the breeding process, yet they also require support from appropriate institutions and regulations.