Core Insights - The "Artificial Intelligence +" action plan aims to accelerate the deployment of specialized AI agents in the healthcare sector by November 2025, prompting leading pharmaceutical companies to implement digital employees such as "bidding assistants" and "patient follow-up AI agents," achieving over a 40% reduction in labor costs for certain processes [1][12] - The real challenge for managers in the medical device industry lies not in the adoption of AI but in leading the transformation rather than passively adapting to it [1][12] - The necessity for AI agents is emphasized due to the accelerated operational pace in the medical device sector, driven by normalized centralized procurement and reforms in payment systems [1][12] Industry Trends - The introduction of AI agents is seen as a significant organizational capability restructuring rather than just a technological upgrade [1][12] - Managers face daily challenges such as immediate retrieval of clinical value and economic evidence during insurance negotiations, rapid interpretation of changing bidding policies, and compliance-related tasks that require high accuracy [1][12] - The shift in mindset is crucial, as low-code platforms and specialized large models enable more non-technical managers to engage in the configuration and iteration of AI agents [1][12] Managerial Implications - Simply introducing digital employees does not equate to achieving intelligence; the key differentiator is the organization's ability to convert business logic into AI-executable processes, which becomes a new competitive advantage for professional managers [2][13] - In the next three years, managers who can transform frontline business pain points into automated solutions will gain greater influence in resource-constrained environments, while teams that remain in manual process modes may become marginalized [2][13] - AI is not expected to replace managers but will reshape their roles, emphasizing the importance of proactively mastering the ability to direct AI agents [2][13] Training and Development - Training programs are designed to equip participants with the skills to build and deploy AI systems tailored to pharmaceutical scenarios, focusing on compliance and practical applications [15][18] - The training targets various roles within pharmaceutical companies, including medical managers, compliance reviewers, market managers, and digital teams [15][16] - The curriculum includes hands-on experience with AI tools, case studies, and practical applications to ensure participants can effectively implement AI agents in real-world scenarios [19][20]