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市场调查报告书
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糖尿病管理市场中的人工智慧（按设备类型、技术、最终用户、部署模式、类型和组件）—2025-2032 年全球预测

Artificial Intelligence in Diabetes Management Market by Device Type, Technology, End User, Deployment Mode, Type, Component - Global Forecast 2025-2032
出版日期: | 出版商: 360iResearch | 英文 183 Pages | 商品交期: 最快1-2个工作天内

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预计到 2032 年，糖尿病管理人工智慧市场规模将成长至 90.4 亿美元，复合年增长率为 31.57%。

主要市场统计数据
基准年2024年 10亿美元
预计2025年 13.2亿美元
预测年份：2032年 90.4亿美元
复合年增长率（%） 31.57%

一篇引人入胜的介绍，将人工智慧作为重塑糖尿病照护提供途径中的临床实践和病人参与的战略力量

人工智慧、数位健康整合和新型设备架构正在迅速改变糖尿病管理的临床和商业性格局。本介绍将帮助您了解人工智慧工具如何从试点阶段发展到主流临床工作流程，进而影响护理路径、病人参与和系统级效能。此外，本介绍也展示了技术成熟度、法规演变和相关人员期望变化的相互作用如何塑造短期应用动态。

相关人员阅读本报告时会发现，报告的结构旨在强调实际意义，而非纯粹的理论进展。临床医生和医疗服务提供者必须评估预测分析和决策支援系统将如何改变照护现场决策，而支付方和管理者则必须考虑远端监控和闭合迴路解决方案对营运和资金筹措的影响。同时，患者越来越期待无缝的、智慧型手机主导的体验，以减轻日常管理负担并提供切实可行的洞察。因此，本导言将人工智慧定位为一个跨装置、软体和护理模式的乘数效应，而非一项独立的创新，这为后续章节设定了明确的预期，这些章节将分析变革性转变、细分市场、区域动态和实用建议。

对人工智慧和互联护理系统转变的权威分析，这些转变正在重新定义糖尿病管理中的临床实践模式、报销设计和患者期望

近年来，随着人工智慧和连网型设备的融合，糖尿病管理格局发生了显着变化，创造了新的护理标准。临床团队越来越多地采用持续监测和演算法主导的胰岛素剂量，以减少差异性并实现个人化治疗。同时，汇总生理和行为数据的软体平台正在实现更具预防性和主动性的干预措施。这些转变反映了一个新兴的生态系统，在这个生态系统中，硬体进步、即时分析和云端工作流程相互作用，从而对血糖控制和风险轨迹产生更高解析度的洞察。

此外，法律规范和报销政策正在根据临床效益和营运价值的证据进行调整。因此，供应商的策略正在从销售独立设备转向整合感测器、演算法和护理协调服务的整合解决方案。患者的期望也在不断演变：便利性、与消费性设备的互通性以及透明的数据共用方法如今影响着产品的采用。总而言之，这些动态正在加速糖尿病管理从以门诊为中心的偶发性护理转向强调预防、个人化和系统级效率的持续性数据主导护理的转变。

严格检验自 2025 年起生效的美国累积关税如何改变整个糖尿病生态系统的供应链筹资策略和产品开发重点

美国将于2025年加征累积关税，这给整个糖尿病护理设备和软体供应链带来了明显的压力，也促使製造商制定了相应的战略应对措施。目前，关税增加了进口零件和成品的投入成本，促使製造商重新评估筹资策略，并尽可能加快供应链本地化进程。这促使他们仔细审查供应商关係和合约条款，采购团队强调双重采购、更长的交货期规划和前置作业时间弹性，以减轻持续贸易政策波动的风险。

同时，由于成本上限和利润预期的变化，产品开发和商业化时间表也面临压力。一些供应商为了保持竞争力而消化了成本上涨，而另一些供应商则重新评估了价格或推迟了非关键投资。对于以软体为中心的产品，云端託管和跨境资料传输安排需要重新进行法律和合规审查，以确保与不断变化的贸易和资料政策保持一致。从中期来看，关税成为国内製造产能和战略伙伴关係关係投资的催化剂，这些投资优先考虑近岸外包，加强区域供应链，并为本地供应商和委託製造创造有条件的机会，使其能够根据需求扩大业务规模。

深度细分洞察，整合设备外形规格、技术堆迭、最终用户配置、部署方式、疾病亚型和组件优先级，以揭示可行的采用潜力

细分洞察需要详细了解设备外形规格、支援技术、使用者偏好、部署模型、疾病类型和组件优先顺序如何相互作用，从而影响其采用和临床效果。从设备角度来看，血糖仪仍然适用于自我监测和非侵入式用例，而更先进的连续血糖监测系统和胰岛素输送机制则支援闭合迴路自动化，以减轻日常负担。间歇扫描监测器和即时连续监测器、贴片帮浦和管式帮浦之间的差异，导致了不同的使用者体验和整合要求，而全闭合迴路系统比混合配置需要更高的互通性和监管保证。

技术选择至关重要，因为云端运算选项、决策支援模组、机器学习方法、行动应用平台和预测分析功能决定了扩充性和临床效用。公共云端和私有云端架构决定资料管治和延迟特征，决策支援功能涵盖从警报产生到药物推荐等各个面向。使用监督、非监督或强化方法的机器学习实施会导致不同的检验需求和临床医生采用路径。诊所和糖尿病中心优先考虑工作流程整合和专家支持，医院强调住院和门诊的连续性，居家医疗优先考虑远端和自我监控的便利性，研究机构寻求灵活的资料存取以进行假设检验。云端基础的部署与本地部署在扩充性和控制之间产生权衡，混合部署越来越普遍。疾病类型细分，例如具有特殊需求的产前护理、成人与早发性 1 型或胰岛素依赖型与非胰岛素依赖型 2 型队列，可为临床方案和设备选择提供资讯。最后，泵浦和感测器等硬体元素与演算法和使用者介面等软体功能之间的组件级划分凸显了投资和监管监督的重点。

全面的区域见解，详细说明美洲、欧洲、中东和非洲以及亚太地区的动态将如何影响糖尿病解决方案所采用的监管和商业策略

区域动态正在从根本上塑造糖尿病管理的采用途径、报销方式和供应链架构。在美洲，医疗系统对基于价值的模型和远端监控功能表现出强烈的需求，推动了支付方对以结果为导向的伙伴关係关係和能够带来可衡量的患者层面改善的产品的兴趣。在北美，医疗设备软体监管的明确性正在鼓励在综合医疗服务网路中进行试点部署，而商业性支付方的动态正在影响解决方案的打包和报销方式。

在欧洲、中东和非洲，异质的法规环境和多样化的医疗服务交付环境需要製定适应性打入市场策略，以应对各国报销模式、隐私标准和基础设施的差异。寻求在该地区渗透的製造商必须优化互通性和本地化，在集中式云端架构与本地部署或边缘运算之间取得平衡，因为频宽和资料主权是这些领域的主要关注点。在亚太地区，技术的快速采用、智慧型手机的高普及率以及公共对数位医疗的不断投资，为可扩展的人工智慧解决方案创造了肥沃的土壤。这些地区差异加在一起，需要差异化的商业性模式、策略伙伴关係和监管合作计画。

公司层面的策略洞察揭示了竞争定位、伙伴关係模式、投资重点和能力，这些决定了人工智慧糖尿病护理领域的长期领导地位。

竞争格局由多种因素构成：成熟的医疗设备製造商正在向软体赋能医疗领域扩张；科技公司提供分析和平台服务；以及新兴参与企业专注于细分市场的病患体验和演算法创新。市场领导企业强调融合感测硬体、云端基础分析和临床医生决策支援的整合产品组合，而中介软体供应商则专注于连接不同设备和电子健康记录的互通性层。同时，软体优先型公司则透过演算法的复杂性和使用者介面设计实现差异化，旨在提升消费者参与度并增强临床医生的工作流程。

投资者和策略合作伙伴也透过优先考虑那些拥有可靠临床证据、可扩展部署模式和清晰报销路径的公司来影响创新轨迹。设备原始设备製造商 (OEM) 与云端或分析供应商之间的合作仍然是加快上市时间和拓展服务范围的领先策略。评估其竞争定位的公司应专注于产品模组化、资料管治实践、监管准备以及展示有意义的真实世界临床结果的能力。

为行业领导者提供行动建议，以建立有弹性的商业模式，加速采用、建立信任并推动可衡量的临床结果

产业领导者应采取一系列切实可行的行动，将技术前景转化为可衡量的临床和商业性成果。首先，优先考虑互通性和开放标准，以便设备和分析技术能够整合到多样化的临床工作流程和电子健康记录中。这种方法将促进多供应商生态系统的发展，减少供应商采用过程中的摩擦，并扩大患者的选择范围。其次，投资严格的临床检验，将演算法输出与临床医生判定和患者报告的结果相结合，以建立信任并支持报销讨论。这些证据对于将试点计画纳入标准护理路径至关重要。

第三，采取策略提升供应链韧性，例如双重采购、在适当情况下进行近岸外包，以及灵活调整合约以适应贸易政策的变化。第四，设计定价和报销模式，使医疗服务提供者、付款人和患者的奖励机制保持一致，优先考虑与控制改善和急性事件减少相关的基于价值的安排。第五，发展以使用者为中心的介面和行动体验，以减轻患者和临床医生的认知负担，并确保依从性和持续参与。最后，在硬体、软体和临床领域建立策略伙伴关係关係，以加速创新，同时降低执行风险。

一种透明的混合方法研究途径，将专家访谈与文献综合和严格检验相结合，以产生可操作、可复製的见解

支撑本分析的调查方法结合了定性和定量分析，以确保研究的稳健性、三角测量和实用性。主要研究包括对临床医生、产品负责人、采购负责人和监管专家的深入访谈，以及专家圆桌讨论，探讨临床应用和商业性途径的障碍。次要研究则考察了同行评审文献、监管指南、临床试验註册中心和公司资讯披露，以整合主要研究的发现，并确定常见的技术趋势和检验方法。

资料合成采用主题分析法进行定性输入，并采用结构化架构评估技术就绪性、互通性和经营模式可行性。在适用的情况下，访谈结果与已备案的监管文件和公开的临床证据进行交叉引用。伦理考量是调查方法的核心，并已获得访谈参与者的知情同意，并在需要时进行仔细的去身分识别处理。研究结果强调可重复的推理、透明的假设和基于证据的结论，从而为战略决策提供信息，而无需依赖私人专有数据集。

简洁的结论强调了在临床检验互通性和商业设计方面采取协作行动的迫切需要，以实现人工智慧糖尿病护理的益处。

总而言之，人工智慧和连网型设备的创新正在融合，创造出一种截然不同的糖尿病护理模式，该模式强调持续监测、个人化胰岛素给药和数据主导的决策支援。积极主动地将产品设计、临床检验和商业模式与不断变化的监管和报销格局相结合的相关人员，很可能获得先发优势。相反，将人工智慧视为护理路径中一项功能而非不可或缺的组成部分的机构，则可能面临应用受限和影响零散的风险。

未来发展需要设备製造商、软体供应商、临床医生、支付者和政策制定者之间的通力合作，确保技术进步转化为真正的临床效益。透过利用互通性、优先生成可靠的证据以及设计永续的经营模式，糖尿病行业可以加速从被动管理向主动个性化糖尿病护理的转变，从而改善治疗效果并减轻系统负担。

目录

第一章：前言

第二章调查方法

第三章执行摘要

第四章 市场概况

第五章 市场洞察

  • 将持续血糖监测数据与人工智慧预测演算法结合，根据即时生活方式模式个人化胰岛素剂量
  • 将机器学习模型应用于穿戴式设备，以便早期发现高风险糖尿病患者的低血糖事件
  • 在虚拟健康助理中使用自然语言处理为糖尿病患者提供量身定制的饮食和药物建议
  • 发展联邦学习框架，用于跨多个机构训练 AI 糖尿病管理模型，同时保护病患资料隐私
  • 推出一款人工智慧智慧型手机应用程序，利用电脑视觉技术自动识别膳食并推荐胰岛素Bolus
  • 製药和科技公司合作在大规模临床试验中检验人工智慧闭合迴路胰岛素输送系统

第六章：2025年美国关税的累积影响

第七章：人工智慧的累积影响，2025年

8. 糖尿病管理市场中的人工智慧（按设备类型）

  • 血糖仪
    • 无创血糖仪
    • SMBG
  • 封闭回路型系统
    • 全闭环
    • 混合闭合迴路
  • 连续血糖监测仪
    • 间歇扫描CGM
    • 即时CGM
  • 胰岛素帮浦
    • 贴片帮浦
    • 管泵

9. 糖尿病管理市场中的人工智慧（按技术）

  • 云端运算
    • 私有云端
    • 公共云端
  • 决策支援系统
    • 警报生成
    • 建议剂量
  • 机器学习
    • 强化学习
    • 监督学习
    • 无监督学习
  • 行动应用程式
    • Android
    • iOS
  • 预测分析
    • 血糖值趋势预测
    • 风险预测

第 10 章糖尿病管理市场中的人工智慧（按最终用户划分）

  • 诊所
    • 糖尿病中心
    • 一般医学
  • 居家护理
    • 远端监控
    • 自我监控
  • 医院
    • 住院病人
    • 门诊
  • 研究所
    • 学术的
    • 私人的

第 11 章糖尿病管理市场中的人工智慧（按部署模式）

  • 云端基础
    • 混合云端
    • 公共云端
  • 本地部署
    • 边缘运算
    • 基于伺服器

第 12 章糖尿病管理市场中的人工智慧（按类型）

  • 怀孕
    • 妊娠早期
    • 第二个三个月
    • 妊娠晚期
  • 类型 1
    • 成人发病
    • 早发
  • 类型 2
    • 胰岛素依赖型
    • 胰岛素依赖型

13. 糖尿病管理市场中的人工智慧（按组成部分）

  • 硬体
    • 泵浦
    • 感应器
    • 穿戴式装置
  • 软体
    • 演算法
    • 资料管理
    • 使用者介面

14. 糖尿病管理人工智慧市场（按地区）

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 欧洲、中东和非洲
    • 欧洲
    • 中东
    • 非洲
  • 亚太地区

第 15 章糖尿病管理市场中的人工智慧（按群体）

  • ASEAN
  • GCC
  • EU
  • BRICS
  • G7
  • NATO

16. 糖尿病管理人工智慧市场（按国家）

  • 美国
  • 加拿大
  • 墨西哥
  • 巴西
  • 英国
  • 德国
  • 法国
  • 俄罗斯
  • 义大利
  • 西班牙
  • 中国
  • 印度
  • 日本
  • 澳洲
  • 韩国

第十七章竞争格局

  • 2024年市占率分析
  • 2024年FPNV定位矩阵
  • 竞争分析
    • Medtronic plc
    • Abbott Laboratories
    • Dexcom, Inc.
    • F. Hoffmann-La Roche Ltd
    • Insulet Corporation
    • Tandem Diabetes Care, Inc.
    • Teladoc Health, Inc.
    • Omada Health, Inc.
    • Bigfoot Biomedical, Inc.
    • Glooko Inc.
Product Code: MRR-4369010656EF

The Artificial Intelligence in Diabetes Management Market is projected to grow by USD 9.04 billion at a CAGR of 31.57% by 2032.

KEY MARKET STATISTICS
Base Year [2024] USD 1.00 billion
Estimated Year [2025] USD 1.32 billion
Forecast Year [2032] USD 9.04 billion
CAGR (%) 31.57%

A compelling introduction that contextualizes artificial intelligence as a strategic force reshaping diabetes care delivery pathways clinical practice and patient engagement

The clinical and commercial landscape for diabetes management is undergoing a rapid transformation driven by artificial intelligence, digital health integration, and novel device architectures. This introduction sets the stage for understanding how AI-enabled tools are moving from experimental pilots to mainstream clinical workflows, influencing care pathways, patient engagement, and system-level performance. It also frames the interplay between technology maturation, regulatory evolution, and shifting stakeholder expectations that together are shaping near-term adoption dynamics.

As stakeholders read on, they will find the report structured to highlight practical implications rather than purely theoretical advances. Clinicians and provider organizations must now evaluate how predictive analytics and decision support systems change point-of-care decision-making, while payers and administrators weigh the operational and financing implications of remote monitoring and closed loop solutions. Meanwhile, patients increasingly expect seamless, smartphone-driven experiences that reduce daily management burden and provide actionable insights. This introduction therefore positions AI not as a standalone innovation but as a force multiplier acting across devices, software, and care models, setting clear expectations for the subsequent sections that analyze transformative shifts, segmentation, regional dynamics, and actionable recommendations.

An authoritative analysis of the systemic shifts driven by AI and connected care that are redefining clinical practice models reimbursement design and patient expectations in diabetes management

The last few years have revealed transformative shifts in the diabetes management landscape as AI and connected devices converge to create new standards of care. Clinical teams are increasingly adopting continuous monitoring and algorithm-driven insulin delivery to reduce variability and personalize therapy; concomitantly, software platforms that aggregate physiological and behavioral data enable more proactive, preventive interventions. These shifts reflect an emergent ecosystem in which hardware advances, real-time analytics, and cloud-enabled workflows interact to produce higher-resolution insight into glycemic control and risk trajectories.

Moreover, regulatory frameworks and reimbursement policies are beginning to adapt to evidence of clinical benefit and operational value. As a result, vendor strategies have pivoted from selling standalone devices toward integrated solutions that combine sensors, algorithms, and care coordination services. Patient expectations are also evolving: convenience, interoperability with consumer devices, and transparent data-sharing modalities now influence product adoption. Collectively, these dynamics are accelerating the migration of diabetes management from episodic, clinic-centric care to continuous, data-driven modalities that emphasize prevention, personalization, and system-level efficiency.

A rigorous examination of how cumulative United States tariffs enacted in 2025 reshaped supply chains procurement strategies and product development priorities across the diabetes ecosystem

The imposition of cumulative United States tariffs in 2025 created a distinct set of stresses and strategic responses across the diabetes device and software supply chain. In the immediate term, tariffs increased input costs for imported components and finished devices, prompting manufacturers to re-evaluate sourcing strategies and to accelerate supply chain localization where feasible. The result has been a deliberate reassessment of supplier relationships and contractual terms, with procurement teams emphasizing dual sourcing, longer lead-time planning, and inventory resilience to mitigate exposure to ongoing trade policy volatility.

In parallel, product development and commercialization timelines experienced pressure as cost ceilings and margin expectations shifted. Some vendors absorbed incremental costs to preserve competitiveness, while others recalibrated pricing or deferred noncritical investments. For software-centric offerings, cloud hosting and cross-border data transfer arrangements required renewed legal and compliance scrutiny to ensure alignment with evolving trade and data policies. Over the medium term, tariffs acted as a catalyst for investment in domestic manufacturing capacity and for strategic partnerships that prioritize nearshoring, thereby strengthening regional supply networks and creating conditional opportunities for local suppliers and contract manufacturers to scale operations in response to demand.

Deep segmentation insights that integrate device form factors technology stacks end-user profiles deployment modalities disease subtypes and component priorities to reveal practical adoption levers

Segmentation insight requires a granular understanding of how device form factors, enabling technologies, user settings, deployment models, disease types, and component emphasis interact to influence adoption and clinical impact. From a device perspective, blood glucose meters remain relevant for self-monitoring and noninvasive use cases while more advanced continuous glucose monitoring systems and insulin delivery mechanisms support closed loop automation that reduces daily burden. Distinctions between intermittently scanned and real-time continuous monitors, and between patch and tubed pumps, drive different user experiences and integration requirements, while fully closed loop systems demand higher interoperability and regulatory assurance than hybrid configurations.

Technology choices matter because cloud computing options, decision support modules, machine learning approaches, mobile application platforms, and predictive analytics capabilities determine scalability and clinical utility. Public and private cloud architectures shape data governance and latency characteristics, while decision support functions range from alert generation to dosage recommendations. Machine learning implementations that use supervised, unsupervised, or reinforcement approaches will yield different validation needs and clinician acceptance pathways. End-user segmentation further clarifies where value accrues: clinics and diabetes centers prioritize workflow integration and specialist support, hospitals focus on inpatient and outpatient continuity, home care emphasizes remote and self-monitoring convenience, and research institutes demand flexible data access for hypothesis testing. Deployment modes-cloud-based versus on-premise-create trade-offs between scalability and control, with hybrid implementations increasingly common. Disease-type segmentation, including gestational care with trimester-specific needs, Type 1 adult and juvenile onset distinctions, and Type 2 insulin-dependent versus non-insulin-dependent cohorts, informs clinical protocols and device selection. Finally, the component-level split between hardware elements such as pumps and sensors and software capabilities like algorithms and user interfaces underscores where investment and regulatory oversight concentrate.

Comprehensive regional insights detailing how Americas Europe Middle East & Africa and Asia-Pacific dynamics influence adoption regulatory engagement and commercial strategy for diabetes solutions

Regional dynamics fundamentally shape adoption pathways, reimbursement approaches, and supply chain architecture across the diabetes management landscape. In the Americas, health systems demonstrate a strong appetite for value-based models and remote monitoring capabilities, driving payer interest in outcomes-oriented partnerships and in products that can demonstrate measurable patient-level improvements. North American regulatory clarity around medical device software has encouraged pilot deployments within integrated delivery networks, while commercial payer dynamics influence how solutions are packaged and reimbursed.

In Europe, Middle East & Africa, heterogeneous regulatory environments and diverse care delivery contexts require adaptive market entry strategies that account for national reimbursement models, privacy standards, and infrastructure variability. Manufacturers seeking traction across this region must optimize for interoperability and localization, balancing centralized cloud architectures with on-premise or edge computing where bandwidth and data sovereignty concerns prevail. In the Asia-Pacific region, rapid technology adoption, high smartphone penetration, and increasing public investment in digital health create fertile ground for scalable AI-enabled solutions, yet market entrants must navigate varying clinical practice patterns, procurement rules, and localized expectations for affordability and after-sales support. Taken together, these regional nuances dictate differentiated commercial approaches, strategic partnerships, and regulatory engagement plans.

Strategic company-level insights that illuminate competitive positioning partnership models investment priorities and the capabilities that determine long-term leadership in AI-enabled diabetes care

The competitive landscape is defined by a mix of established medical device manufacturers expanding into software-enabled care, technology firms offering analytics and platform services, and nascent entrants focused on niche patient experiences or algorithmic innovation. Market leaders emphasize integrated portfolios that combine sensing hardware, cloud-based analytics, and clinician-facing decision support, while middleware providers concentrate on interoperability layers that connect disparate devices and electronic health records. Meanwhile, software-first companies differentiate through algorithmic sophistication and user interface design, targeting both consumer engagement and clinician workflow augmentation.

Investors and strategic partners are also influencing the trajectory of innovation by prioritizing companies that demonstrate robust clinical evidence, scalable deployment models, and clear pathways to reimbursement. Partnerships between device OEMs and cloud or analytics providers remain a dominant strategy to accelerate time-to-market and to broaden service offerings. For organizations assessing competitive positioning, attention should focus on product modularity, data governance practices, regulatory readiness, and the ability to demonstrate meaningful clinical outcomes in real-world settings.

Actionable recommendations for industry leaders to accelerate adoption build trust and create resilient commercial models that drive measurable clinical outcomes

Industry leaders should pursue a set of pragmatic actions to translate technological promise into measurable clinical and commercial outcomes. First, prioritize interoperability and open standards to ensure devices and analytics can integrate into diverse clinical workflows and electronic health records. This approach reduces friction for provider adoption and facilitates multi-vendor ecosystems that enhance patient choice. Second, invest in rigorous clinical validation that pairs algorithmic outputs with clinician adjudication and patient-reported outcomes to build trust and support reimbursement discussions. Such evidence is critical for transitioning pilots into standard care pathways.

Third, adopt supply chain resilience strategies that include dual sourcing, nearshoring where appropriate, and contractual flexibility to respond to trade-policy shifts. Fourth, design pricing and reimbursement models that align incentives across providers, payers, and patients, prioritizing value-based arrangements tied to demonstrable improvements in control and reduced acute events. Fifth, develop user-centered interfaces and mobile experiences that reduce cognitive load for patients and clinicians alike, ensuring adherence and sustained engagement. Finally, cultivate strategic partnerships across hardware, software, and clinical domains to accelerate innovation while mitigating execution risk.

A transparent mixed-methods research approach combining expert interviews literature synthesis and rigorous validation to produce actionable and reproducible insights

The research methodology underpinning this analysis combined qualitative and quantitative approaches to ensure robustness, triangulation, and practical relevance. Primary research consisted of in-depth interviews with clinicians, product leaders, procurement officers, and regulatory specialists, supplemented by expert roundtables that explored clinical adoption barriers and commercial pathways. Secondary research reviewed peer-reviewed literature, regulatory guidance, clinical trial registries, and company disclosures to contextualize primary findings and to identify prevailing technology trends and validation approaches.

Data synthesis employed thematic analysis for qualitative inputs and structured frameworks to assess technology readiness, interoperability, and business model viability. Where applicable, validation steps included cross-referencing interview insights with documented regulatory filings and publicly available clinical evidence. Ethical considerations were central to the methodology, with informed consent obtained from interview participants and careful anonymization applied where requested. The outcome is a research product that emphasizes reproducible reasoning, transparent assumptions, and evidence-based conclusions designed to inform strategic decisions without relying on undisclosed proprietary datasets.

A concise conclusion highlighting the imperative for coordinated action across clinical validation interoperability and commercial design to realize AI-driven diabetes care benefits

In conclusion, artificial intelligence and connected-device innovation are converging to create a fundamentally different model of diabetes care-one that emphasizes continuous monitoring, personalized insulin delivery, and data-driven decision support. Stakeholders who move proactively to align product design, clinical validation, and commercial models with evolving regulatory and reimbursement landscapes will capture early advantage. Conversely, organizations that treat AI as a feature rather than as an integral component of care pathways risk limited adoption and fragmented impact.

The path forward requires collaboration among device manufacturers, software vendors, clinicians, payers, and policy makers to ensure that technological advances translate into real-world clinical benefits. By leveraging interoperability, prioritizing robust evidence generation, and designing sustainable business models, the industry can accelerate the shift from reactive management to proactive, personalized diabetes care that improves outcomes and reduces system burden.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Integration of continuous glucose monitoring data with AI predictive algorithms to personalize insulin dosing based on real-time lifestyle patterns
  • 5.2. Deployment of machine learning models in wearable devices for early detection of hypoglycemic events among high-risk diabetic patients
  • 5.3. Use of natural language processing in virtual health assistants to provide tailored dietary and medication advice for diabetic individuals
  • 5.4. Development of federated learning frameworks to train AI diabetes management models across multiple institutions while preserving patient data privacy
  • 5.5. Adoption of AI-driven smartphone applications for automated meal recognition and insulin bolus recommendations using computer vision techniques
  • 5.6. Collaboration between pharma companies and tech firms to validate AI-enabled closed-loop insulin delivery systems in large-scale clinical trials

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Artificial Intelligence in Diabetes Management Market, by Device Type

  • 8.1. Blood Glucose Meter
    • 8.1.1. Non Invasive Bg Meter
    • 8.1.2. Smbg
  • 8.2. Closed Loop System
    • 8.2.1. Fully Closed Loop
    • 8.2.2. Hybrid Closed Loop
  • 8.3. Continuous Glucose Monitor
    • 8.3.1. Intermittently Scanned Cgm
    • 8.3.2. Real Time Cgm
  • 8.4. Insulin Pump
    • 8.4.1. Patch Pump
    • 8.4.2. Tubed Pump

9. Artificial Intelligence in Diabetes Management Market, by Technology

  • 9.1. Cloud Computing
    • 9.1.1. Private Cloud
    • 9.1.2. Public Cloud
  • 9.2. Decision Support Systems
    • 9.2.1. Alert Generation
    • 9.2.2. Dose Recommendation
  • 9.3. Machine Learning
    • 9.3.1. Reinforcement Learning
    • 9.3.2. Supervised Learning
    • 9.3.3. Unsupervised Learning
  • 9.4. Mobile Applications
    • 9.4.1. Android
    • 9.4.2. Ios
  • 9.5. Predictive Analytics
    • 9.5.1. Glucose Trend Prediction
    • 9.5.2. Risk Prediction

10. Artificial Intelligence in Diabetes Management Market, by End User

  • 10.1. Clinic
    • 10.1.1. Diabetes Center
    • 10.1.2. General Clinic
  • 10.2. Home Care
    • 10.2.1. Remote Monitoring
    • 10.2.2. Self Monitoring
  • 10.3. Hospital
    • 10.3.1. Inpatient
    • 10.3.2. Outpatient
  • 10.4. Research Institute
    • 10.4.1. Academic
    • 10.4.2. Private

11. Artificial Intelligence in Diabetes Management Market, by Deployment Mode

  • 11.1. Cloud Based
    • 11.1.1. Hybrid Cloud
    • 11.1.2. Public Cloud
  • 11.2. On Premise
    • 11.2.1. Edge Computing
    • 11.2.2. Server Based

12. Artificial Intelligence in Diabetes Management Market, by Type

  • 12.1. Gestational
    • 12.1.1. First Trimester
    • 12.1.2. Second Trimester
    • 12.1.3. Third Trimester
  • 12.2. Type 1
    • 12.2.1. Adult Onset
    • 12.2.2. Juvenile Onset
  • 12.3. Type 2
    • 12.3.1. Insulin Dependent
    • 12.3.2. Non Insulin Dependent

13. Artificial Intelligence in Diabetes Management Market, by Component

  • 13.1. Hardware
    • 13.1.1. Pumps
    • 13.1.2. Sensors
    • 13.1.3. Wearable Devices
  • 13.2. Software
    • 13.2.1. Algorithms
    • 13.2.2. Data Management
    • 13.2.3. User Interface

14. Artificial Intelligence in Diabetes Management Market, by Region

  • 14.1. Americas
    • 14.1.1. North America
    • 14.1.2. Latin America
  • 14.2. Europe, Middle East & Africa
    • 14.2.1. Europe
    • 14.2.2. Middle East
    • 14.2.3. Africa
  • 14.3. Asia-Pacific

15. Artificial Intelligence in Diabetes Management Market, by Group

  • 15.1. ASEAN
  • 15.2. GCC
  • 15.3. European Union
  • 15.4. BRICS
  • 15.5. G7
  • 15.6. NATO

16. Artificial Intelligence in Diabetes Management Market, by Country

  • 16.1. United States
  • 16.2. Canada
  • 16.3. Mexico
  • 16.4. Brazil
  • 16.5. United Kingdom
  • 16.6. Germany
  • 16.7. France
  • 16.8. Russia
  • 16.9. Italy
  • 16.10. Spain
  • 16.11. China
  • 16.12. India
  • 16.13. Japan
  • 16.14. Australia
  • 16.15. South Korea

17. Competitive Landscape

  • 17.1. Market Share Analysis, 2024
  • 17.2. FPNV Positioning Matrix, 2024
  • 17.3. Competitive Analysis
    • 17.3.1. Medtronic plc
    • 17.3.2. Abbott Laboratories
    • 17.3.3. Dexcom, Inc.
    • 17.3.4. F. Hoffmann-La Roche Ltd
    • 17.3.5. Insulet Corporation
    • 17.3.6. Tandem Diabetes Care, Inc.
    • 17.3.7. Teladoc Health, Inc.
    • 17.3.8. Omada Health, Inc.
    • 17.3.9. Bigfoot Biomedical, Inc.
    • 17.3.10. Glooko Inc.

LIST OF FIGURES

  • FIGURE 1. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2018-2032 (USD MILLION)
  • FIGURE 2. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2024 VS 2032 (%)
  • FIGURE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2024 VS 2032 (%)
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2024 VS 2032 (%)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2032 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TYPE, 2024 VS 2032 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TYPE, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COMPONENT, 2024 VS 2032 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 15. AMERICAS ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 16. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 17. LATIN AMERICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 18. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUBREGION, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 19. EUROPE ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 20. MIDDLE EAST ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 21. AFRICA ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 22. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GROUP, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 24. ASEAN ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 25. GCC ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 26. EUROPEAN UNION ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 27. BRICS ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 28. G7 ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 29. NATO ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2032 (USD MILLION)
  • FIGURE 31. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 32. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2018-2024 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, 2025-2032 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2018-2024 (USD MILLION)
  • TABLE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DEVICE TYPE, 2025-2032 (USD MILLION)
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, 2018-2024 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, 2025-2032 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY BLOOD GLUCOSE METER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY NON INVASIVE BG METER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SMBG, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, 2018-2024 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, 2025-2032 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOSED LOOP SYSTEM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY FULLY CLOSED LOOP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HYBRID CLOSED LOOP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, 2018-2024 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, 2025-2032 (USD MILLION)
  • TABLE 49. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 50. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 51. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 52. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 53. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 54. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CONTINUOUS GLUCOSE MONITOR, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 55. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 56. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 57. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 58. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 59. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 60. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INTERMITTENTLY SCANNED CGM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 61. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 62. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 63. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 64. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 65. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 66. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REAL TIME CGM, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 67. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, 2018-2024 (USD MILLION)
  • TABLE 68. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, 2025-2032 (USD MILLION)
  • TABLE 69. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 70. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 71. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 72. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 73. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 74. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INSULIN PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 75. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 76. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 77. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 78. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 79. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 80. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PATCH PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 81. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 82. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 83. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 84. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 85. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 86. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TUBED PUMP, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 87. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2018-2024 (USD MILLION)
  • TABLE 88. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY TECHNOLOGY, 2025-2032 (USD MILLION)
  • TABLE 89. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, 2018-2024 (USD MILLION)
  • TABLE 90. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, 2025-2032 (USD MILLION)
  • TABLE 91. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 92. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 93. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 94. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 95. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 96. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLOUD COMPUTING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 97. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 98. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 99. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 100. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 101. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 102. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PRIVATE CLOUD, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 103. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 104. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 105. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 106. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 107. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 108. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PUBLIC CLOUD, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 109. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, 2018-2024 (USD MILLION)
  • TABLE 110. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, 2025-2032 (USD MILLION)
  • TABLE 111. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 112. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 113. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 114. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 115. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 116. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DECISION SUPPORT SYSTEMS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 117. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 118. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 119. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 120. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 121. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 122. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ALERT GENERATION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 123. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 124. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 125. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 126. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 127. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 128. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DOSE RECOMMENDATION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 129. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, 2018-2024 (USD MILLION)
  • TABLE 130. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, 2025-2032 (USD MILLION)
  • TABLE 131. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 132. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 133. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 134. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 135. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 136. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MACHINE LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 137. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 138. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 139. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 140. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 141. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 142. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REINFORCEMENT LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 143. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 144. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 145. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 146. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 147. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 148. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 149. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 150. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 151. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 152. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 153. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 154. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY UNSUPERVISED LEARNING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 155. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, 2018-2024 (USD MILLION)
  • TABLE 156. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, 2025-2032 (USD MILLION)
  • TABLE 157. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 158. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 159. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 160. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 161. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 162. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY MOBILE APPLICATIONS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 163. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 164. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 165. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 166. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 167. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 168. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY ANDROID, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 169. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 170. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 171. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 172. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 173. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 174. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY IOS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 175. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, 2018-2024 (USD MILLION)
  • TABLE 176. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, 2025-2032 (USD MILLION)
  • TABLE 177. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 178. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 179. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 180. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 181. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 182. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY PREDICTIVE ANALYTICS, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 183. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 184. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 185. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 186. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 187. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 188. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GLUCOSE TREND PREDICTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 189. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 190. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 191. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 192. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 193. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 194. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY RISK PREDICTION, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 195. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2018-2024 (USD MILLION)
  • TABLE 196. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY END USER, 2025-2032 (USD MILLION)
  • TABLE 197. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, 2018-2024 (USD MILLION)
  • TABLE 198. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, 2025-2032 (USD MILLION)
  • TABLE 199. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 200. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 201. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 202. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 203. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 204. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY CLINIC, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 205. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 206. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 207. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 208. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 209. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 210. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY DIABETES CENTER, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 211. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 212. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 213. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 214. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 215. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 216. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY GENERAL CLINIC, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 217. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, 2018-2024 (USD MILLION)
  • TABLE 218. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, 2025-2032 (USD MILLION)
  • TABLE 219. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 220. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 221. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 222. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 223. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 224. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOME CARE, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 225. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 226. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 227. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 228. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 229. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 230. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY REMOTE MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 231. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 232. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 233. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 234. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 235. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 236. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY SELF MONITORING, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 237. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, 2018-2024 (USD MILLION)
  • TABLE 238. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, 2025-2032 (USD MILLION)
  • TABLE 239. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 240. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 241. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 242. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 243. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 244. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY HOSPITAL, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 245. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY REGION, 2018-2024 (USD MILLION)
  • TABLE 246. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY REGION, 2025-2032 (USD MILLION)
  • TABLE 247. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY GROUP, 2018-2024 (USD MILLION)
  • TABLE 248. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY GROUP, 2025-2032 (USD MILLION)
  • TABLE 249. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY COUNTRY, 2018-2024 (USD MILLION)
  • TABLE 250. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET SIZE, BY INPATIENT, BY COUNTRY, 2025-2032 (USD MILLION)
  • TABLE 251. GLOBAL ARTIFICIAL INTELLIGENCE IN DIABETES MANAGEMENT MARKET