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1965305

人工智慧在糖尿病管理领域的市场－全球产业规模、份额、趋势、机会、预测：按设备、技术、地区和竞争格局划分，2021-2031年

Artificial Intelligence in Diabetes Management Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Device, By Technique, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3个工作天内

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简介目录

全球糖尿病管理人工智慧市场预计将从 2025 年的 147.3 亿美元成长到 2031 年的 243.3 亿美元，复合年增长率为 8.72%。

在该领域，机器学习和预测分析被用于分析生理数据，以支持精准的血糖管理和临床决策。关键的成长要素包括全球慢性代谢疾病发病率的不断上升，这需要可扩展的医疗保健基础设施。此外，控制与长期併发症相关的医疗成本的需求以及对个人化治疗方案日益增长的需求，也推动了这些自动化系统的应用。

市场概览
预测期 2027-2031
市场规模：2025年 147.3亿美元
市场规模：2031年 243.3亿美元
复合年增长率：2026-2031年 8.72%
成长最快的细分市场 血糖值监测设备
最大的市场 北美洲

另一方面，严格的法规结构限制了演算法决策的检验和课责，从而阻碍了市场成长。资料隐私和敏感病患记录保护等问题也对演算法的广泛应用构成了重大障碍。国际糖尿病联盟（IDF）报告称，到2024年，全球约有5.89亿20至79岁的成年人将患有糖尿病，凸显了有效管理方案的迫切需求。

市场驱动因素

全球糖尿病病例的激增是推动人工智慧应用的主要动力，因为医疗保健系统正努力应对糖尿病日益增长的经济和临床负担。患者数量的激增需要扩充性、经济高效的解决方案，以优化医疗服务并透过自动化监测降低长期成本。这项挑战的经济规模正在推动人工智慧整合干预技术的市场发展，这些技术可以减少併发症和住院。例如，美国糖尿病协会 (ADA) 在 2024 年 8 月发布的报告《美国各州确诊糖尿病的经济成本》中指出，确诊糖尿病的总估计费用达 6,400 亿美元。因此，医疗保健提供者越来越依赖人工智慧驱动的平台来提高资源分配效率，并大规模改善患者的治疗效果。

同时，穿戴式装置和持续血糖监测（CGM）系统的日益普及，正在产生大量资料集，这些资料集对于训练和优化复杂的机器学习演算法至关重要。这些设备作为关键的数据输入点，使人工智慧模型能够提供以前无法实现的即时个人化洞察。该领域的商业性发展速度显而易见。根据雅培公司2024年10月发布的2024年第三季财报，该公司持续血糖监测系统的全球整体销售额超过16亿美元。随着硬体的普及，能够高精度解读这些数据的软体功能也不断增强。例如，Know Labs公司2024年7月发布的临床研究报告显示，其专有的人工智慧演算法在血糖状态分类方面达到了93.37%的准确率，这表明其非侵入式预测技术已相当成熟。

市场挑战

资料隐私和敏感患者资讯的安全问题是人工智慧在全球糖尿病管理领域扩张的重大障碍。人工智慧驱动的糖尿病管理工具需要持续存取详细的生理数据，例如即时血糖值和胰岛素注射历史，这些数据通常透过连网设备（例如连续血糖监测仪）传输。集中管理此类高度个人化的健康资讯对网路犯罪分子极具吸引力，并引发了患者和医疗服务提供者的严重担忧。因此，由于身分盗窃和医疗诈骗风险的增加，相关人员往往对采用基于云端的人工智慧解决方案犹豫不决，从而延缓了这些技术融入标准医疗保健体系的进程。

这种犹豫不决源自于该领域网路安全事件频传的惊人频率，这些事件破坏了演算法部署所必需的信任。据美国医院协会称，到2024年，2.59亿美国人的部分或全部医疗记录可能已被窃取。如此大规模的安全漏洞直接阻碍了市场成长，因为对资料外洩的担忧降低了人们共用敏感资讯的意愿，而这些资讯对于人工智慧系统的有效运作和全球扩张至关重要。

市场趋势

人工智慧驱动的闭合迴路胰岛素输注系统的出现，标誌着治疗方式从被动监测转向自主治疗性介入的变革性转变。这些平台也被称为人工胰臟系统，它们利用复杂的演算法，根据持续的回馈即时调整胰岛素剂量，显着减轻了患者手动计算的认知负担。透过预测和自动控制血糖波动，这些系统能够延长血糖达标时间，最大限度地降低低血糖风险，并推动其快速商业性化应用。这种加速普及的趋势在领先创新者的财务表现中得到了明确的体现。根据 Tandem Diabetes Care 公司 2025 年 2 月发布的“2024 年第四季度及全年财务业绩”，其全球 GAAP 销售额增长 44% 至 2.826 亿美元，证实了市场正积极转向自动化演算法输注技术。

同时，数位双胞胎技术的应用正透过动态虚拟化个体独特的生理功能，重新定义精准代谢照护的概念。这些人工智慧模型将来自感测器的详细数据与临床病史相结合，模拟个体对各种生活方式干预的代谢反应，使医疗服务提供者能够制定高度个人化的治疗方案，旨在逆转疾病，而不仅仅是控制病情。随着相关人员认识到该方法在减少长期药物依赖和改善临床疗效方面的潜力，这种方法正吸引着大量的资本投资。例如，根据2025年8月MobiHealthNews的报导《数位双胞胎Start-UpsTwin Health融资5,300万美元，估值接近10亿美元》，Twin Health融资5,300万美元用于扩展其「全身数位双胞胎」服务。这凸显了该产业对个人化、数据驱动的缓解策略的策略承诺。

目录

第一章概述

第二章：调查方法

第三章执行摘要

第四章：客户心声

第五章：人工智慧在糖尿病管理领域的全球市场展望

  • 市场规模及预测
    • 按金额
  • 市占率及预测
    • 依设备分类（诊断设备、血糖监测设备、胰岛素输注设备）
    • 透过科技（基于案例的推理、智慧数据分析）
    • 按地区
    • 按公司（2025 年）
  • 市场地图

第六章：北美糖尿病管理人工智慧市场展望

  • 市场规模及预测
  • 市占率及预测
  • 北美洲：国别分析
    • 我们
    • 加拿大
    • 墨西哥

第七章：欧洲糖尿病管理人工智慧市场展望

  • 市场规模及预测
  • 市占率及预测
  • 欧洲：国别分析
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙

第八章：亚太地区糖尿病管理人工智慧市场展望

  • 市场规模及预测
  • 市占率及预测
  • 亚太地区：国别分析
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳洲

第九章：中东和非洲糖尿病管理人工智慧市场展望

  • 市场规模及预测
  • 市占率及预测
  • 中东与非洲：国别分析
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 南非

第十章：人工智慧在南美糖尿病管理领域的市场展望

  • 市场规模及预测
  • 市占率及预测
  • 南美洲：国别分析
    • 巴西
    • 哥伦比亚
    • 阿根廷

第十一章 市场动态

  • 促进因素
  • 任务

第十二章 市场趋势与发展

  • 併购
  • 产品发布
  • 近期趋势

第十三章：全球糖尿病管理人工智慧市场：SWOT分析

第十四章：波特五力分析

  • 产业竞争
  • 新进入者的潜力
  • 供应商的议价能力
  • 顾客权力
  • 替代品的威胁

第十五章 竞争格局

  • Vodafone Group PLC
  • Apple Inc
  • Google Inc
  • International Business Machines Corporation（IBM）
  • Glooko Inc
  • Tidepool Inc

第十六章 策略建议

第十七章：关于研究公司及免责声明

简介目录
Product Code: 18850

The Global Artificial Intelligence in Diabetes Management Market is projected to expand from USD 14.73 Billion in 2025 to USD 24.33 Billion by 2031, registering a CAGR of 8.72%. This sector utilizes machine learning and predictive analytics to analyze physiological data, facilitating precise glycemic management and clinical decision-making. Key growth factors include the increasing global incidence of chronic metabolic diseases, which demands scalable healthcare frameworks. Furthermore, the necessity to curtail healthcare costs linked to long-term complications, alongside the drive for personalized treatment plans, fuels the integration of these automated systems.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 14.73 Billion
Market Size 2031USD 24.33 Billion
CAGR 2026-20318.72%
Fastest Growing SegmentGlucose Monitoring Devices
Largest MarketNorth America

Conversely, market growth faces obstacles from strict regulatory frameworks concerning the validation and accountability of algorithmic decisions. Issues related to data privacy and the protection of sensitive patient records also pose significant hurdles to widespread adoption. Highlighting the magnitude of the issue, the International Diabetes Federation reported in 2024 that approximately 589 million adults between the ages of 20 and 79 were living with diabetes worldwide, emphasizing the critical need for effective management solutions.

Market Driver

The escalating global prevalence of diabetes acts as a primary catalyst for the adoption of artificial intelligence, as healthcare systems struggle to manage the growing economic and clinical burden of the disease. This surge in patient volume necessitates scalable, cost-effective solutions that can optimize care delivery and reduce long-term expenses through automated monitoring. The financial magnitude of this challenge is driving the market toward AI-integrated interventions that can mitigate complications and hospitalizations. Illustrating this significant economic strain, according to the American Diabetes Association, August 2024, in the 'Economic Costs Attributed to Diagnosed Diabetes in Each U.S. State' report, the total estimated cost of diagnosed diabetes reached $640 billion. Consequently, providers are increasingly relying on AI-driven platforms to enhance resource allocation and improve patient outcomes at scale.

Simultaneously, the rising adoption of wearable devices and continuous glucose monitoring (CGM) systems is generating the massive datasets required to train and refine sophisticated machine learning algorithms. These devices act as critical data entry points, enabling AI models to provide real-time, personalized insights that were previously unattainable. The commercial velocity of this sector is evident; according to Abbott, October 2024, in its 'Third-Quarter 2024 Financial Results', sales of its continuous glucose monitoring systems exceeded $1.6 billion globally. As hardware penetration grows, the software capabilities are advancing in tandem to interpret this data with high precision. For instance, according to Know Labs, July 2024, in a report on its clinical research, its proprietary AI algorithms achieved a 93.37% accuracy rate in classifying glycemic status, demonstrating the maturing capability of non-invasive predictive technologies.

Market Challenge

Concerns surrounding data privacy and the security of sensitive patient information serve as a critical barrier to the expansion of the Global Artificial Intelligence in Diabetes Management Market. AI-driven diabetes tools require continuous access to granular physiological data, such as real-time glucose levels and insulin dosage history, often transmitted via connected devices like continuous glucose monitors. This centralization of highly personal health information creates attractive targets for cybercriminals, fostering significant apprehension among patients and healthcare providers. Consequently, stakeholders frequently hesitate to adopt cloud-based AI solutions due to the elevated risk of identity theft and medical fraud, thereby slowing the integration of these technologies into standard care.

This hesitation is substantiated by the alarming frequency of cyber incidents within the sector which undermines the trust necessary for algorithmic adoption. According to the American Hospital Association, in 2024, 259 million Americans' health care records had been stolen in part or full. Such massive vulnerabilities directly impede market growth, as the fear of data breaches restricts the willingness of users to share the sensitive information required for these AI systems to function effectively and scale globally.

Market Trends

The emergence of AI-driven closed-loop insulin delivery systems represents a transformative shift from passive monitoring to autonomous therapeutic intervention. These platforms, often termed artificial pancreas systems, utilize advanced algorithms to modulate insulin dosing in real-time based on continuous feedback, significantly reducing the cognitive burden of manual calculations for patients. By predicting glucose fluctuations and automating corrections, these solutions improve time-in-range and minimize the risks of hypoglycemia, leading to rapid commercial uptake. This accelerating adoption is evident in the financial performance of key innovators; according to Tandem Diabetes Care, February 2025, in its 'Fourth Quarter and Full Year 2024 Financial Results', worldwide GAAP sales grew 44 percent to $282.6 million, underscoring the market's aggressive pivot toward automated algorithmic delivery technologies.

Simultaneously, the adoption of digital twin technology is redefining precision metabolic care by creating dynamic virtual models of an individual's unique physiology. By synthesizing granular data from sensors and clinical history, these AI models simulate metabolic responses to various lifestyle interventions, enabling providers to prescribe highly personalized regimens aimed at disease reversal rather than mere management. This approach is attracting substantial capital investment as stakeholders recognize its potential to decrease long-term dependency on pharmacotherapy and improve clinical outcomes. Illustrating this momentum, according to MobiHealthNews, August 2025, in the article 'Digital twin startup Twin Health secures $53M, nears $1B valuation', Twin Health raised $53 million to scale its Whole Body Digital Twin service, validating the sector's strategic commitment to individualized, data-driven remission strategies.

Key Market Players

  • Vodafone Group PLC
  • Apple Inc
  • Google Inc
  • International Business Machines Corporation (IBM)
  • Glooko Inc
  • Tidepool Inc

Report Scope

In this report, the Global Artificial Intelligence in Diabetes Management Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Artificial Intelligence in Diabetes Management Market, By Device

  • Diagnostic Devices
  • Glucose Monitoring Devices
  • Insulin Delivery Devices

Artificial Intelligence in Diabetes Management Market, By Technique

  • Case-Based Reasoning
  • Intelligent Data Analysis

Artificial Intelligence in Diabetes Management Market, By Region

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Artificial Intelligence in Diabetes Management Market.

Available Customizations:

Global Artificial Intelligence in Diabetes Management Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Artificial Intelligence in Diabetes Management Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Device (Diagnostic Devices, Glucose Monitoring Devices, Insulin Delivery Devices)
    • 5.2.2. By Technique (Case-Based Reasoning, Intelligent Data Analysis)
    • 5.2.3. By Region
    • 5.2.4. By Company (2025)
  • 5.3. Market Map

6. North America Artificial Intelligence in Diabetes Management Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Device
    • 6.2.2. By Technique
    • 6.2.3. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States Artificial Intelligence in Diabetes Management Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Device
        • 6.3.1.2.2. By Technique
    • 6.3.2. Canada Artificial Intelligence in Diabetes Management Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Device
        • 6.3.2.2.2. By Technique
    • 6.3.3. Mexico Artificial Intelligence in Diabetes Management Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Device
        • 6.3.3.2.2. By Technique

7. Europe Artificial Intelligence in Diabetes Management Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Device
    • 7.2.2. By Technique
    • 7.2.3. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany Artificial Intelligence in Diabetes Management Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Device
        • 7.3.1.2.2. By Technique
    • 7.3.2. France Artificial Intelligence in Diabetes Management Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Device
        • 7.3.2.2.2. By Technique
    • 7.3.3. United Kingdom Artificial Intelligence in Diabetes Management Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Device
        • 7.3.3.2.2. By Technique
    • 7.3.4. Italy Artificial Intelligence in Diabetes Management Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Device
        • 7.3.4.2.2. By Technique
    • 7.3.5. Spain Artificial Intelligence in Diabetes Management Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Device
        • 7.3.5.2.2. By Technique

8. Asia Pacific Artificial Intelligence in Diabetes Management Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Device
    • 8.2.2. By Technique
    • 8.2.3. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China Artificial Intelligence in Diabetes Management Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Device
        • 8.3.1.2.2. By Technique
    • 8.3.2. India Artificial Intelligence in Diabetes Management Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Device
        • 8.3.2.2.2. By Technique
    • 8.3.3. Japan Artificial Intelligence in Diabetes Management Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Device
        • 8.3.3.2.2. By Technique
    • 8.3.4. South Korea Artificial Intelligence in Diabetes Management Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Device
        • 8.3.4.2.2. By Technique
    • 8.3.5. Australia Artificial Intelligence in Diabetes Management Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Device
        • 8.3.5.2.2. By Technique

9. Middle East & Africa Artificial Intelligence in Diabetes Management Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Device
    • 9.2.2. By Technique
    • 9.2.3. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia Artificial Intelligence in Diabetes Management Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Device
        • 9.3.1.2.2. By Technique
    • 9.3.2. UAE Artificial Intelligence in Diabetes Management Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Device
        • 9.3.2.2.2. By Technique
    • 9.3.3. South Africa Artificial Intelligence in Diabetes Management Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Device
        • 9.3.3.2.2. By Technique

10. South America Artificial Intelligence in Diabetes Management Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Device
    • 10.2.2. By Technique
    • 10.2.3. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Artificial Intelligence in Diabetes Management Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Device
        • 10.3.1.2.2. By Technique
    • 10.3.2. Colombia Artificial Intelligence in Diabetes Management Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Device
        • 10.3.2.2.2. By Technique
    • 10.3.3. Argentina Artificial Intelligence in Diabetes Management Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Device
        • 10.3.3.2.2. By Technique

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global Artificial Intelligence in Diabetes Management Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. Vodafone Group PLC
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. Apple Inc
  • 15.3. Google Inc
  • 15.4. International Business Machines Corporation (IBM)
  • 15.5. Glooko Inc
  • 15.6. Tidepool Inc

16. Strategic Recommendations

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