Innovation management in AI advancement: Revolutionizing health system and biopharma

The integration of advanced technologies is reshaping the healthcare and biopharma industries and requires effective innovation management frameworks to leverage their potential while fully addressing associated risks. This literature review explores the global landscape of AI-driven innovation in the healthcare and biopharma, examining strategies, challenges and future directions. Technological applications are revolutionizing the pharmaceutical value chain by accelerating drug discovery and development, optimizing manufacturing processes and enhancing patient care delivery. For instance, AI-assisted drug development has reduced the time for candidate identification from years to just a few months, as demonstrated by the DSP-1181 project. Healthcare organizations employ statistical and symbolic methods to improve operational efficiency and patient outcomes. Despite promising advancements, significant challenges persist, including regulatory approval complexities, transparency and validation of algorithms, intellectual property protection, and ethical concerns such as data accuracy and bias. The responsibility for autonomous systems introduces additional difficulties in ownership and accountability. Successful adoption requires strategic planning for technology deployment alongside compliance with evolving regulatory and international standards. This review synthesizes current trends while identifying gaps in implementation. It provides structured insights for researchers, practitioners and policymakers.