Large biopharmaceutical companies have unique advantages in drug development strategies. The enormous scale of these industry giants allows them to adopt portfolio approaches, a luxury that small companies cannot enjoy. Large pharmaceutical companies such as Johnson & Johnson (J&J) or Roche, with market capitalizations of hundreds of billions of dollars, are able to absorb the inherent setbacks that often occur in the drug development process. The cost calculations of these companies go beyond the expenses of successful projects and include the accumulated costs of multiple setbacks. A key characteristic of large biopharmaceutical companies is their extensive expertise in various fields. From chemistry and statistics to clinical development and marketing, their massive scale allows for the cultivation of deep knowledge and capabilities. This expertise puts them in a favorable position to precisely execute the numerous steps involved in drug development. Another notable aspect of large pharmaceutical companies is their broad focus on technological innovation. The emphasis is not on elevating individual innovators, but on enhancing the entire research and development organization. This collective approach aims to leverage emerging technologies to enhance the capabilities of the entire facility, emphasizing the organizational belief that overall improvement of capabilities surpasses isolated advancements. The promise of AI and the productivity paradox Both large and small companies have no clear advantage in the drug development process. Seasoned drug developers express skepticism towards overvaluing research and development strategies, emphasizing that success often depends on agile responses to challenges rather than pre-determined strategies. In this skepticism, attention has shifted to the flexibility and focus of small biotech companies. While startups and small biotech companies may have flat organizational structures conducive to quick decision-making, their vulnerability in a sluggish market is widely recognized. The challenges of harnessing the biopharmaceutical field extend to emerging sciences and the pursuit of promising molecules. Here, particularly well-funded startups and small biotech companies demonstrate exceptional focus and flexibility. The organizational consistency within these small entities enables them to rapidly respond and adapt to unforeseen challenges, a feat difficult to replicate in large biopharmaceutical companies with complex hierarchical systems and decision-making processes. The impact of AI on biopharmaceutical efficiency Discussions led by Microsoft's Peter Lee on GPT-4 have propelled the development in this field. It highlights the inherent prospects and risks of generative artificial intelligence, emphasizing its potential to reform treatment evaluation and accelerate approvals. Vivid examples from Harvard professor Zak Kohane vividly depict the potential impact of AI on timely provision of life-saving interventions. Against the backdrop of the "productivity paradox" in biopharmaceuticals, there is optimism about AI's ability to rapidly improve productivity. Although experts assert that digital tools have made significant progress and emphasize the need for companies to "fundamentally restructure" their operations, caution is urged in managing expectations of AI's impact on biopharmaceutical productivity, citing historical perspectives on technological lag effects. Balancing biopharmaceuticals with AI in drug development As the biopharmaceutical industry faces dynamic challenges in both large and small scales, and integrates AI into drug development, the pressing question is: Can AI not only make us fail more efficiently but also increase our chances of success? In shaping the future of biopharmaceuticals, specific examples of AI's impact on drug discovery and delivery become crucial. In the pursuit of revolutionizing drug development, can AI truly be a catalyst that not only improves failure efficiency but also significantly enhances the success rate, fundamentally changing the way the biopharmaceutical industry identifies, evaluates, and approves treatment methods?