Group 1 - The article emphasizes that sustainable development has become the core logic and inevitable direction for transformation and innovation across various sectors in the context of advancing "dual carbon" goals and the comprehensive implementation of the "Healthy China" strategy [1][4] - During the 2025 China International Import Expo, two thematic forums will focus on sustainable development: one on "Zero Carbon Park China Solution" to explore financial empowerment paths and business model breakthroughs for industrial park green and low-carbon transformation [1][10] - The Zero Carbon Park Forum aims to gather government, enterprises, and academic institutions to discuss implementation paths, innovative technologies, and collaborative mechanisms for zero carbon park construction, sharing advanced experiences and typical cases from both domestic and international contexts [4][16] Group 2 - The "Medical and Health Industry Sustainable Innovation" forum will discuss how the medical health industry can deeply practice sustainable concepts amid technological iterations and industrial upgrades [10][11] - The forum will feature discussions on the challenges and opportunities for multinational corporations (MNCs) in navigating the new landscape, particularly in addressing issues related to the accessibility of innovative drugs and medical devices [11][14] - Both forums aim to create a platform for intellectual exchange and resource linkage among elites from government, industry, academia, and research, facilitating higher quality growth in the relevant fields during the new development stage [16][17]

Core Viewpoint - The integration of AI technology into the healthcare industry is essential for addressing challenges such as global aging, chronic disease burdens, and uneven distribution of medical resources, positioning AI as a systemic solution for sustainable healthcare development [1][3][4]. Group 1: AI Empowerment in Healthcare - AI has transitioned from pilot scenarios to ecosystem restructuring, enhancing efficiency and accessibility in healthcare services [8][11]. - The forum highlighted the need for a new medical data infrastructure to achieve breakthroughs in efficiency, value, and equity [9][11]. - AI applications in healthcare are rapidly evolving, with significant advancements in areas such as pediatric AI pre-consultation, digital imaging in dentistry, and remote dermatology consultations [11][15]. Group 2: Sustainable Innovation in Healthcare - The "2025 Sustainable Innovation Case Recommendation List" was released, showcasing 37 cases from 36 well-known domestic and foreign companies, focusing on urgent industry needs and aligning with the Healthy China 2030 strategy [6][18]. - The list categorizes cases into "International Innovation Localization," "Local Innovation Globalization," and "ESG Innovation Practices," aiming to promote experience sharing and resource integration within the industry [6][18][35]. Group 3: Globalization and Localization Strategies - Multinational companies are deepening localization strategies, evolving from local production to local R&D innovation, while leveraging their technological and resource advantages to foster local innovation [35][41]. - Chinese pharmaceutical companies are increasingly exploring international markets, integrating into the global innovation ecosystem, and ensuring that local innovations benefit a global audience [35][41]. Group 4: ESG and AI in Healthcare - ESG has become a core issue for sustainable development, with a growing focus on integrating AI technology ethics into ESG evaluation dimensions [48]. - Companies are encouraged to disclose AI model training data sources and bias correction mechanisms, ensuring compliance and ethical standards in AI applications [48]. Group 5: Future Directions and Challenges - The healthcare industry faces challenges in high-quality data sample supply and the translation of clinical research into practical applications [11][13]. - The need for a robust AI infrastructure that supports effective business models and enhances traditional services is emphasized, with a focus on data-driven decision-making [50][51].