Artificial intelligence (AI) is revolutionizing pharmacoeconomics by transforming drug development continuum from early discovery to market access. Through advanced machine learning, predictive analytics, and generative models, AI enhances efficiency, reduces costs, and improves success rates across pharmaceutical R&D. It accelerates compound screening, predicts bioactivity, refines ADME profiling, and forecasts toxicity—streamlining clinical trial design and optimizing therapeutic candidates. Beyond the lab, AI redefines economic evaluation by enabling dynamic, data-driven cost-effectiveness and budget impact analyses. Tools now simulate real-world adherence, model pricing strategies, and support value-based reimbursement planning. The integration of AI into pharmacoeconomics promotes precision, sustainability, and equitable access to high-value therapies. Strategic collaborations, such as Novartis and Microsoft, exemplify AI’s potential to reshape market dynamics, streamline commercialization, and amplify return on investment. This review highlights AI’s dual role in scientific innovation and economic validation, positioning it as a catalyst for next-generation, value-based healthcare systems.