Implementation of bioinformatics in oncology has revolutionized cancer research and clinical practice via precision medicine through genomic profiling and machine learning algorithms. This narrative review addresses advances such as TCGA databases and single-cell sequencing technologies overcoming issues such as algorithmic bias and infrastructure limitations. New knowledge is brought into the identification of biomarkers and the optimization of therapy with emphasis on bioinformatics’ revolutionary role in personalized cancer treatment. Despite being as promising as it seems, the incorporation of bioinformatics in daily clinical practice is hampered by data standardization, algorithmic bias, and infrastructure limitations. Closing these gaps is the key to fully realizing the promise of bioinformatics in providing personalized and equitable cancer care.