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「智启健康 产业向新」AI+大健康专场私董会成功举办!| 2026文创新势力超级私董会

CBNData 2026-07-16 11:17
CBNData 2026/07/16 11:17

邦小白快读

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本文整理了AI+大健康专场私董会披露的行业核心信息和普通用户可感知的干货内容,具体如下:

1.行业整体发展明确,利好普通消费者享受更优质的健康服务:目前中国大健康产业规模2025年已达20万亿元,AI+医疗健康行业2025年规模突破千亿元,2026年预计达1500亿元,国家已将AI辅助诊断纳入医保乙类目录,政策红利推动技术落地。

2.普通消费者可享受的新型健康服务越来越多:当前大健康行业已经从以疾病为中心转向以健康为中心,轻养生、治未病成为主流,市场已经推出按年龄性别划分的简化选择的营养包,AI可以提供家庭医生预警、体检报告个性化解读、精准健康建议等服务,还有不少带医疗专业背书的日常健康产品可供选择。

本文梳理了AI+大健康领域最新的消费趋势、产品研发方向与品牌升级路径,相关干货如下:

1.消费趋势明确,可锚定新需求布局:当前大健康增长逻辑从疾病驱动转向需求驱动,三大趋势值得关注:主动健康从治病前移到治未病,精准个性化从千人一方走向一人一策,医消融合模糊了严肃医疗和健康消费的边界,全年龄段消费者都开始接受轻养生、药食同源的产品,健康成为日常需求。

2.产品研发可参考成熟实践:品牌可以和医院深度合作,基于临床反馈研发细分群体的专业产品,获取医疗背书升级品牌价值;也可以针对消费者选择困难的痛点,按年龄性别划分产品线简化决策,未来可借助AI匹配用户场景和健康痛点,推出精准营养产品。

3.品牌升级可走医消融合路径,借助专业医疗背书提升专业价值,满足消费者高品质健康需求。

本文整理了AI+大健康赛道的政策红利、市场机会、风险提示与实操方向,干货如下:

1.政策与市场环境利好:国家已经将AI辅助诊断纳入医保乙类目录,上海将生命健康列为重点新兴赛道,已经推动83个医疗AI大模型落地,上海长宁北新街道为企业提供全维度配套服务,优化营商环境,欢迎企业入驻,有明显的政策和区位优势。

2.市场增量空间充足:当前中国大健康产业规模高速增长,AI+大健康2026年市场规模预计突破1500亿元,消费需求转向主动健康、精准健康,出现大量新的增量机会。

3.实操方向与风险提示:卖家可以通过医消融合获得医疗背书提升产品信任度,借助AI工具优化用户匹配效率,可布局AI辅助诊断、家庭医生、早筛、科普干预等多个场景;需要注意通用大模型未来可能对垂直领域专业模型形成降维打击,要提前提升专业内容辨别能力。

本文结合AI+大健康产业的发展变化,给工厂提供了产品方向、商业机会与数字化转型的相关干货,具体如下:

1.产品生产和设计需求已经发生转变:当前消费者需求从治疗疾病转向日常健康管理,青睐轻养生、精准化的健康产品,工厂需要开发适配不同年龄、性别、场景、健康痛点的细分产品,可布局药食同源相关品类;同时消费者越来越认可专业医疗背书,工厂可以对接医疗机构合作开发产品,提升产品专业度和认可度。

2.有明确的商业拓展机会:AI+大健康产业规模保持15%左右的年复合增长率,政策支持力度大,上海长宁已经形成AI+大健康产业集聚,提供完善的营商服务和产业生态,工厂可以落地这类产业集聚区,对接优质资源获得发展机会。

3.数字化转型启示:工厂可以接入AI技术优化产品研发,开发AI结合早筛这类创新产品,也可以借助AI挖掘用户需求,提升产品匹配精准度。

本文梳理了AI+大健康领域的行业趋势、客户核心痛点和可落地的解决方案方向,干货内容如下:

1.行业发展趋势清晰:AI+大健康已经从概念走向实战,政策红利和技术突破双重推动,市场规模快速增长,产业增长逻辑从疾病驱动转向需求驱动,医消融合成为行业主流方向,全产业链都在探索AI落地路径。

2.客户核心痛点明确:当前消费者存在健康产品选择困难、健康管理缺乏持续性、优质医疗资源不足的问题,产业端存在AI落地价值边界不清晰、效率提升不足的痛点,全行业都需要适配不同场景的AI服务解决方案。

3.可拓展的解决方案方向:服务商可以针对医院开发临床辅助AI工具,抓取病历关键信息提升问诊效率;针对C端用户开发AI家庭医生、AI体检报告解读闭环服务,优化分诊随访,实现从解读到干预跟踪的完整服务;需要明确AI的定位是效率助手,核心要围绕用户健康需求开发服务,不能过度神化技术。

本次私董会汇集了AI+大健康全产业链的需求,给平台商的招商、运营和风险规避提供了参考,干货内容如下:

1.产业对平台的核心需求清晰:AI+大健康产业目前需要能够对接资源、推动协同的平台,产业端需要打通不同主体的数据藩篱,推动专业医疗和健康消费的产业协同,落地AI应用场景。

2.平台运营和招商方向明确:平台可以重点布局AI+大健康这条高增长赛道,聚焦主动健康、精准医疗、医消融合等细分方向,对接医疗机构、健康品牌、技术企业等不同主体,搭建资源对接交流的渠道;也可以依托区位优势打造产业集聚区,配套工商办理、政策申报、人才服务等全维度企业服务,吸引相关企业入驻。

3.需要规避的发展风险:当前AI落地还存在价值边界不清晰的问题,通用大模型可能对垂直专业模型形成降维打击,平台要引导企业回归服务用户健康的初心,避免概念炒作,推动AI真实落地。

本次私董会分享了AI+大健康领域的最新产业动向、核心问题与创新商业模式,干货内容适合研究参考,具体如下:

1.产业出现多个新动向:当前大健康产业增长逻辑已经从疾病驱动转向需求驱动,三大核心趋势值得研究:主动健康关口前移到治未病,个性化服务从千人一方转向一人一策,医消融合模糊了严肃医疗和健康消费的边界;AI已经落地临床辅助、家庭健康、早筛、科普干预等多个场景,正式从概念走向实战,政策也已经放开AI辅助诊断进医保,产业进入落地期。

2.行业出现值得研究的新问题:当前AI落地存在价值边界不清的问题,AI只能作为提效助手不能替代专业判断;通用大模型未来可能对垂直领域专业模型形成降维打击,行业需要提升专业知识辨别能力;此外AI落地还存在数据藩篱未打通的问题。

3.诞生了多个创新商业模式:包括消费品牌+医疗机构合作的医消融合模式,高端医疗的严肃医疗+消费医疗双引擎模式,AI赋能的体检报告解读-科普-干预-跟踪的闭环健康管理模式等,都具备研究价值。

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Quick Summary

This article compiles core industry insights and practical takeaways shared at a private CEO forum focused on AI-enabled healthcare. Key points are as follows:

1. Clear industry growth will ultimately bring higher-quality health services to consumers: China's overall big health industry is projected to reach 20 trillion yuan by 2025, while the AI healthcare market will exceed 100 billion yuan that year and hit 150 billion yuan in 2026. Policy tailwinds are accelerating technology adoption, with AI-assisted diagnosis already included in China's National Reimbursement Drug List (Class B).

2. Consumers now have access to a growing range of innovative health services: The big health industry has shifted its focus from disease treatment to proactive health management, with preventive care and light wellness becoming mainstream. New products include pre-formulated nutrition packs sorted by age and gender to simplify consumer choice. AI now enables services such as at-home preventive alerts from AI-powered general practitioners, personalized interpretation of physical exam reports, and tailored health recommendations. Consumers also have access to a growing selection of daily wellness products endorsed by medical professionals.

This article summarizes the latest consumer trends, product development directions, and brand upgrading paths for brands operating in AI-enabled big health. Key takeaways are below:

1. Clear consumer trends allow brands to anchor new demand for strategic positioning: The growth driver of the big health industry has shifted from disease-based to demand-based, with three high-impact trends worth noting. First, proactive health has shifted focus from treating illness to preventing it. Second, personalized care is moving from one-size-fits-all solutions to tailored strategies for individual users. Third, the integration of medical care and consumer health has blurred the line between formal clinical care and consumer wellness products, with consumers of all ages now embracing light wellness and medicinal-food products, making health a daily consumption need.

2. Brands can leverage proven practices for product development: Brands can deepen collaboration with hospitals to develop specialized products for niche user groups based on clinical feedback, gaining medical endorsements to boost brand value. To address consumer decision fatigue, they can also segment product lines by age and gender to simplify purchasing choices. Looking ahead, brands can use AI to match user scenarios with specific health needs to launch precision nutrition products.

3. For brand upgrading, the integrated medical-consumer model is a viable path: Leveraging professional medical endorsements to enhance perceived expertise helps brands meet consumer demand for high-quality health products and services.

This article outlines policy tailwinds, market opportunities, risk alerts and actionable strategies for sellers in the AI-enabled big health space. Key insights are as follows:

1. Favorable policy and market conditions: AI-assisted diagnosis has been added to China's National Reimbursement Drug List (Class B). Shanghai has designated life and health as a priority emerging industry, and has already supported the deployment of 83 large medical AI models. The Beixin Subdistrict of Changning District in Shanghai offers full-suite supporting services to enterprises, with clear policy and location advantages for companies looking to set up operations.

2. Abundant room for market growth: China's big health industry is growing rapidly, with the AI-enabled big health market projected to exceed 150 billion yuan by 2026. Shifting consumer demand toward proactive and precision health has created massive new incremental opportunities.

3. Actionable strategies and risk alerts: Sellers can gain medical endorsements via the integrated medical-consumer model to boost consumer trust in their products, leverage AI tools to improve user matching efficiency, and explore opportunities across multiple scenarios including AI-assisted diagnosis, AI-powered family medicine, early screening, and educational intervention. Sellers should note that general large models may deliver outperformance that disrupts vertical specialized AI models in the future, so it is critical to build capacity for verifying professional content in advance.

This article shares actionable insights on product direction, business opportunities and digital transformation for factories based on recent developments in the AI-enabled big health industry. Key points are below:

1. Consumer demand for product design and manufacturing has shifted: Consumers now prioritize daily health management over disease treatment, and prefer light wellness and precision health products. Factories need to develop segmented products tailored to different ages, genders, usage scenarios and health needs, and can explore opportunities in medicinal and edible product categories. Since consumers increasingly value professional medical endorsement, factories can partner with medical institutions to co-develop products, improving product expertise and market recognition.

2. Clear business expansion opportunities: The AI-enabled big health industry maintains a compound annual growth rate of around 15%, with strong policy support. Changning District in Shanghai has already formed an AI-enabled big health industry cluster, offering complete business services and a mature industrial ecosystem. Factories can locate in such industry clusters to access high-quality resources and unlock growth opportunities.

3. Insights for digital transformation: Factories can integrate AI technology to optimize product R&D, and develop innovative AI-enabled products such as AI-connected early screening tools. They can also leverage AI to mine user demand and improve the accuracy of product-user matching.

This article summarizes industry trends, core customer pain points and actionable solution directions for service providers in the AI-enabled big health space. Key insights are as follows:

1. Clear industry development trajectory: AI-enabled big health has moved from concept to commercial implementation, driven by both policy tailwinds and technological breakthroughs, with market size expanding rapidly. The industry's growth driver has shifted from disease-based to demand-based, with the integration of medical care and consumer health becoming the mainstream direction, and players across the value chain are exploring paths to deploy AI.

2. Core customer pain points are well-defined: For consumers, key pain points include difficulty choosing suitable health products, lack of sustained health management, and insufficient access to high-quality medical resources. For industry players, key pain points include unclear value positioning for AI deployments and insufficient efficiency gains. The entire industry needs AI-powered service solutions adapted to different scenarios.

3. Expandable solution directions: Service providers can develop clinical AI assistance tools for hospitals that extract key information from medical records to improve consultation efficiency. For end consumers, they can build end-to-end services including AI-powered family doctors and closed-loop AI interpretation of physical exam reports, optimizing triage and follow-up to deliver complete services from interpretation to intervention and tracking. Service providers should clarify that AI acts as an efficiency enabler, and all development must center on user health needs, rather than overhyping the technology's capabilities.

This private CEO forum gathered input from across the entire AI-enabled big health value chain, offering references for platforms on investment attraction, operations and risk mitigation. Key takeaways are as follows:

1. The core industry demand for platforms is clear: The AI-enabled big health industry currently needs platforms that can connect resources and drive cross-party collaboration. Industry players need to break down data silos between different entities to enable collaboration between formal medical care and consumer wellness, and support the deployment of AI application scenarios.

2. Clear direction for platform operation and investment attraction: Platforms can prioritize the high-growth AI-enabled big health track, focus on niche segments including proactive health, precision medicine, and medical-consumer integration, connect different stakeholders including medical institutions, wellness brands, and technology companies, and build channels for resource matching and exchange. They can also leverage location advantages to build industry clusters, offer full-suite enterprise services including business registration, policy application and talent support, to attract relevant enterprises to locate.

3. Development risks to avoid: AI deployment still faces issues of unclear value positioning today, and general large models may outperform and disrupt vertical specialized models. Platforms should guide participating enterprises to refocus on the core mission of serving user health, avoid hype around AI concepts, and drive real, practical deployment of the technology.

This private CEO forum shared the latest industry developments, core issues and innovative business models in AI-enabled big health, offering research-friendly insights as follows:

1. Multiple new industry developments have emerged: The big health industry's growth driver has shifted from disease-based to demand-based, with three core trends worth studying: proactive health shifting its focus upstream to preventive care; personalized services moving from one-size-fits-all to individual-tailored strategies; and medical-consumer integration blurring the boundary between formal clinical care and consumer wellness. AI has already been deployed in multiple scenarios including clinical assistance, family health management, early screening, and educational intervention, officially moving from concept to practical use. With policy already allowing AI-assisted diagnosis to be covered by insurance, the industry has entered a phase of large-scale deployment.

2. New industry issues have emerged that merit further research: AI deployment currently suffers from unclear value positioning: AI can only act as an efficiency enabler and cannot replace professional clinical judgment. General large models may outperform and disrupt vertical specialized models in the future, requiring the industry to improve capabilities for verifying professional content. AI deployment also faces the ongoing challenge of unbroken data silos across the industry.

3. Multiple innovative business models have emerged that are worthy of study: These include the medical-consumer integration model of consumer brands partnering with medical institutions, the dual-engine model combining formal acute care and consumer care for high-end healthcare, and the AI-powered closed-loop health management model that covers physical exam report interpretation, education, intervention and continuous tracking. All of these models offer high research value.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

近年来,随着人口老龄化加剧和健康消费升级,大健康产业已经成为全球经济竞逐的重要赛道。数据显示,中国大健康产业规模从2019年的8万亿元增长至2025年的20万亿元,2020-2024年均复合增长率稳定在15%。与此同时,AI技术正以前所未有的速度渗透进大健康的每一个环节——从精准诊断到药物研发,从健康管理到康复治疗。据行业研究机构数据,中国AI+医疗健康行业2025年市场规模已突破千亿元,预计2026年将跨越1500亿元大关。今年4月,国家医保局正式将AI辅助诊断纳入医保乙类目录,政策红利与技术突破同频共振,AI+大健康正从概念走向实战。

聚焦上海,在“十五五”规划中,上海将生命健康类服务列为重点布局的新兴赛道之一,聚焦数字医疗、脑机接口、细胞基因治疗、健康管理等前沿领域。目前,上海已系统性推动83个医疗AI大模型落地,并在全国率先发布卫生健康人工智能建设核心成果。而长宁作为AI+大健康的前沿阵地,依托大虹桥区位优势、数字经济基础和消费服务场景,正在为大健康产业提供从技术应用、产业集聚到场景转化的综合土壤。

为更好把握行业发展趋势、链接产业资源,7月9日,在上海市文化创意产业促进会指导下,上海应帆数字科技有限公司联合上海服装集团、北新泾街道共同举办「智启健康 产业向新」AI+大健康专场私董会。上海服装集团副总经理马焱光、北新泾街道社区联合党支部书记沈纬、上海市文化创意产业促进会副秘书长、应帆科技副总裁姚贝贝出席会议。

来自专业医疗机构、健康消费品牌、行业协会等领域的企业代表齐聚一堂,共同探讨AI时代健康消费的新趋势、新场景与新增长路径,推动专业医疗与健康消费之间形成更具想象力的产业协同。

会议开场,上海服装集团副总经理马焱光发表致辞,介绍长宁区资源禀赋及上服集团服装产业、园区产业、文体产业三大板块,并对长宁生命健康产业做重点解读。生命健康产业是长宁重点培育的新兴产业与未来产业,长宁依托大虹桥生命科学创新中心持续完善产业生态、集聚优质龙头资源,已汇聚一批行业优质企业,覆盖生物医药、智慧医疗、生物科技、健康消费等多个细分领域。同时聚焦医工交叉创新,深化AI赋能医药医疗发展,推动生命健康产业与数字科技、人工智能深度融合。

趋势洞察:

从“以疾病为中心”

到“以健康为中心”

当产业边界不断被重新定义,大健康的增长逻辑已经从“疾病驱动”转向“需求驱动”。这一转变的背后,是三个趋势性变化的交汇:主动健康从“治病”前移到“治未病”,精准个性化从“千人一方”走向“一人一策”,医消融合则让“严肃医疗”与“健康消费”的边界逐渐模糊。

纯养日纪品牌主理人范冬梅从食补养生赛道切入,她观察到无论是年轻人还是父母辈,都开始更关注自身健康,消费者对“药食同源”“轻养生”的接受度增加,健康成为贯穿日常的生活方式选择。

如果说食补解决的是“怎么吃得健康”,那么健安喜面对的则是另一个难题——如何让消费者用最快和最短的链路做出购买的决策。健安喜高级销售经理孟昭表示,针对用户的“选择困难”,健安喜推出按年龄、性别划分的营养包来简化决策,未来希望借助AI工具,让用户基于具体场景与健康痛点快速匹配产品,让精准营养触达日常消费。

锦奇医疗董事长张锦霞从精准医疗的视角分享了对“有效预防”的思考,提出医疗本身就是一个严肃的事情,是一个精准干预的结果,在完整的医学链条里,核心关口是前置化的预防医疗。

当越来越多的医院下沉做健康管理、消费品牌向上寻求医疗背书,“严肃医疗”与“健康消费”的边界开始模糊。Grin公共事业部负责人刘莉玲从品牌实践出发分享,Grin通过与医院深度合作,基于临床反馈研发适配不同群体的专业口腔护理产品,用医疗背书纠正市场认知偏差,实现消费品牌的专业价值升级。

上海和睦家医院医疗总监刘英姿提出“双引擎”模式——严肃医疗的实力和消费型医疗的人文关怀。高端医疗的核心竞争力不仅在于诊疗硬实力,更在于人文关怀与情绪价值,消费型医疗的服务体验,是满足高品质健康需求的重要支撑。

场景验证:

界定AI的场景价值与应用边界

当趋势成为共识,真正的考验在于落地。当前市面上AI医疗产品层出不穷,但AI在不同场景中呈现出的赋能价值差异显著,如何界定AI在不同健康场景中的价值边界,也是行业关注的核心话题。

在临床辅助场景中,AI正成为医生的“智能效率伙伴”。上海和睦家医院医疗总监刘英姿表示,目前和睦家已经推出AI辅助诊断、语音电子病例模型,在打通全国院区数据基础上,通过AI自动抓取患者历史病历中的过敏史、手术史等关键信息,生成结构化摘要辅助医生快速问诊,既提升问诊效率,也降低了信息遗漏带来的诊疗风险。

针对AI健康工具进入家庭场景,曜影医疗CEO助理贾天宇从曜影推出AI家庭医生出发,提出AI大模型的作用在于让患者更加便捷。AI能识别危急症状并提前预警医生,同时优化分诊与随访流程,让有限医疗资源覆盖更多用户需求。

从技术视角出发,应帆科技首席智能官李一凡认为,AI的优势在于知识范畴广、效率高,但目前只能作为助手和提效的工具。关于未来发展方向,他希望能够研发随身健康助手,打通数据藩篱、自动采集数据、自主生成健康建议。

在研发与早筛场景,AI正在突破传统技术的边界。丹纳赫集团对外事务部高级经理林慧颖介绍,丹纳赫将AI与筛查技术结合,实现阿尔茨海默症的早期检测,替代传统的脑脊液检测,这意味着社区大规模早筛成为可能,更多人可以在无症状期知晓风险、提前干预。

在科普干预场景,AI则打通了健康指导的“最后一公里”。上海市文化创意产业促进会文化+医疗专委会秘书长董懿为分享,专委会通过AI解读体检报告,不仅输出结果,更配套个性化行为改变建议,精准推送科普内容与干预工具包,实现“报告解读-科普教育-工具干预-持续跟踪”的完整闭环,让健康指导真正落地为用户行动。

但AI的落地并非一帆风顺,迪辅乐生物高级科研总监庾庆华提出了一个更深层的思考,他认为面对AI带来的知识贬值,我们需要的不是获取知识的能力,而是辨别知识的能力。通用大模型凭借其庞大的数据库优势,未来可能对垂直领域的专业模型形成降维打击。

私董会尾声,北新泾街道社区联合党支部书记沈纬作总结致辞,他指出本次私董会碰撞出的产业观点与落地思路,为长宁大健康产业发展提供了鲜活的实践方向。北新泾街道产业密度高、企业活力强,始终将优化营商环境作为核心工作抓手,通过“一口受理”专员机制,为企业提供工商税务办理、政策申报辅导、人才服务等全维度配套支持,精准对接并解决企业发展中的实际诉求。面向大健康这一重点赛道,街道将持续升级服务保障,也欢迎更多大健康领域企业落户北新泾、扎根长宁,共享区域发展机遇,共同推动产业高质量发展。

上海市文化创意产业促进会副秘书长、应帆科技副总裁姚贝贝表示,AI+大健康这个赛道,大家都在用自己的方式回答一个共同的问题:AI到底怎么才能真正服务好人的健康?无论是AI辅助诊断的提效、精准个性化的健康管理方案,还是医消融合的边界重塑,都在提醒我们:技术是手段,而非目的。AI能解决效率,但解决不了“人”的问题——对健康的认知、对生命的关怀、对尊严的守护,始终是大健康产业不变的初心。

注:文/CBNData,文章来源:第一财经商业数据中心(公众号ID:CBNData),本文为作者独立观点,不代表亿邦动力立场。

文章来源:第一财经商业数据中心

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FAQ回顾

当前AI大健康行业的发展趋势有哪些?

当前大健康产业增长逻辑已从“疾病驱动”转向“需求驱动”,呈现三大核心趋势:主动健康从“治病”前移到“治未病”,精准个性化从“千人一方”走向“一人一策”,医消融合让严肃医疗与健康消费的边界逐渐模糊。

AI在大健康领域有哪些常见应用场景?

AI在大健康领域可覆盖多类场景:临床辅助场景可提升医生问诊效率、降低诊疗风险;家庭场景可提供AI家庭医生服务优化分诊随访;早筛场景可实现阿尔茨海默症等疾病早期检测;科普场景可完成体检报告解读并推送健康指导。

中国AI医疗健康行业的市场规模情况如何?

中国AI医疗健康行业2025年市场规模已突破千亿元,预计2026年将跨越1500亿元大关。配套的大健康产业整体规模2025年达20万亿元,2020-2024年均复合增长率稳定在15%。

上海长宁区发展AI大健康产业有哪些优势?

长宁作为AI大健康前沿阵地,依托大虹桥区位优势、数字经济基础和消费服务场景,已集聚一批覆盖生物医药、智慧医疗等细分领域的优质企业,还可为入驻企业提供工商办理、政策申报等全维度配套服务。

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