From cloud computing to biotech, all sectors are being repositioned as "AI-driven," bringing about a genuine productivity revolution beyond mere marketing strategies. The most notable achievement is in drug discovery. Drug development platforms utilizing AI algorithms are demonstrating over 300% productivity improvement compared to traditional methods. AI plays a crucial role throughout the entire process, from molecular design to clinical trial patient recruitment. Protein structure prediction AI, such as DeepMind's AlphaFold3, is fundamentally changing the paradigm of drug development. Protein structure analysis, which previously took years, can now be completed within hours, allowing for accurate prediction of interactions between target proteins and drug molecules. Innovation is also accelerating in the field of bioinformatics. The application of machine learning and deep learning technologies to analyze large-scale genomic data is significantly enhancing the precision of personalized treatments. In particular, AI systems that integrate and analyze multi-omics data (genomics, transcriptomics, proteomics, metabolomics) have reached a level where they can propose optimal treatment methods for individual patients. AI's influence is expanding in clinical trial optimization as well. AI plays a key role in patient stratification, clinical trial design, and safety monitoring, significantly increasing clinical trial success rates. Some biotech companies have achieved a 30-50% reduction in development time through AI-based clinical trial design. The convergence of digital healthcare and biotech is also accelerating. Systems that analyze real-time health data collected from wearable devices using AI to enable early disease diagnosis and prediction are being commercialized. This is showing innovative results, especially in the areas of cardiovascular disease, diabetes, and neurodegenerative diseases. Venture capital investment patterns are also shifting. In the first half of 2025, over 65% of biotech investments were concentrated in companies incorporating AI elements, with drug discovery platforms utilizing generative AI attracting significant investments. Notably, the IPO success rate of AI biotech companies is 40% higher than that of traditional biotech companies. This is because investors highly value the risk reduction and efficiency gains achieved through AI technology. However, challenges remain. Issues such as the explainability of AI models, regulatory guidelines for AI-based therapeutic approvals, and data quality and bias need to be addressed. The FDA is preparing a new regulatory framework for AI-based medical devices and therapeutics in 2025, which is expected to bring significant changes across the industry. In conclusion, 2025 marks a turning point where the convergence of AI and biotech is driving a fundamental transformation across the entire industry, beyond mere technological advancement. This change is expected to enable the development of faster, more accurate, and personalized treatments, ultimately providing better patient outcomes.