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人工智慧在糖尿病管理領域的市場－全球產業規模、佔有率、趨勢、機會、預測：按設備、技術、地區和競爭格局分類，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個工作天內

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簡介目錄

全球糖尿病管理人工智慧市場預計將從 2025 年的 147.3 億美元成長到 2031 年的 243.3 億美元，複合年成長率為 8.72%。

在該領域，機器學習和預測分析被用於分析生理數據，以支持精準的血糖管理和臨床決策。關鍵的成長要素包括全球慢性代謝疾病發病率的不斷上升，這需要可擴展的醫療保健基礎設施。此外，控制與長期併發症相關的醫療成本的需求以及對個人化治療方案日益成長的需求，也推動了這些自動化系統的應用。

市場概覽
預測期 2027-2031
市場規模：2025年 147.3億美元
市場規模：2031年 243.3億美元
複合年成長率：2026-2031年 8.72%
成長最快的細分市場 血糖值監測設備
最大的市場 北美洲

另一方面，嚴格的法規結構限制了演算法決策的檢驗和課責，從而阻礙了市場成長。資料隱私和敏感病患記錄保護等問題也對演算法的廣泛應用構成了重大障礙。國際糖尿病聯盟（IDF）報告稱，到2024年，全球約有5.89億20至79歲的成年人將患有糖尿病，凸顯了有效管理方案的迫切需求。

市場促進因素

全球糖尿病病例的激增是推動人工智慧應用的主要動力，因為醫療保健系統正努力應對糖尿病日益成長的經濟和臨床負擔。患者數量的激增需要擴充性、經濟高效的解決方案，以最佳化醫療服務並透過自動化監測降低長期成本。這項挑戰的經濟規模正在推動人工智慧整合干預技術的市場發展，這些技術可以減少併發症和住院。例如，美國糖尿病協會 (ADA) 在 2024 年 8 月發布的報告《美國各州確診糖尿病的經濟成本》中指出，確診糖尿病的總估計費用達 6,400 億美元。因此，醫療保健提供者越來越依賴人工智慧驅動的平台來提高資源分配效率，並大規模改善患者的治療效果。

同時，穿戴式裝置和持續血糖監測（CGM）系統的日益普及，正在產生大量資料集，這些資料集對於訓練和最佳化複雜的機器學習演算法至關重要。這些設備作為關鍵的數據輸入點，使人工智慧模型能夠提供以前無法實現的即時個人化洞察。該領域的商業性發展速度顯而易見。根據雅培公司2024年10月發布的2024年第三季財報，該公司持續血糖監測系統的全球整體銷售額超過16億美元。隨著硬體的普及，能夠高精度解讀這些數據的軟體功能也不斷增強。例如，Know Labs公司2024年7月發布的臨床研究報告顯示，其專有的人工智慧演算法在血糖狀態分類方面達到了93.37%的準確率，這表明其非侵入式預測技術已相當成熟。

市場挑戰

資料隱私和敏感患者資訊的安全問題是人工智慧在全球糖尿病管理領域擴張的重大障礙。人工智慧驅動的糖尿病管理工具需要持續存取詳細的生理數據，例如即時血糖值和胰島素注射歷史，這些數據通常透過連網設備（例如連續血糖監測儀）傳輸。集中管理此類高度個人化的健康資訊對網路犯罪分子極具吸引力，並引發了患者和醫療服務提供者的嚴重擔憂。因此，由於身分盜竊和醫療詐騙風險的增加，相關人員往往對採用基於雲端的人工智慧解決方案猶豫不決，從而延緩了這些技術融入標準醫療保健體系的進程。

這種猶豫不決源自於該領域網路安全事件頻傳的驚人頻率，這些事件破壞了演算法部署所必需的信任。據美國醫院協會稱，到2024年，2.59億美國人的部分或全部醫療記錄可能已被竊取。如此大規模的安全漏洞直接阻礙了市場成長，因為對資料外洩的擔憂降低了人們共用敏感資訊的意願，而這些資訊對於人工智慧系統的有效運作和全球擴張至關重要。

市場趨勢

人工智慧驅動的閉合迴路胰島素輸注系統的出現，標誌著治療方式從被動監測轉向自主治療性介入的變革性轉變。這些平台也被稱為人工胰臟系統，它們利用複雜的演算法，根據持續的回饋即時調整胰島素劑量，顯著減輕了患者手動計算的認知負擔。透過預測和自動控制血糖波動，這些系統能夠延長血糖達標時間，最大限度地降低低血糖風險，並推動其快速商業性化應用。這種加速普及的趨勢在領先創新者的財務表現中得到了明確的體現。根據 Tandem Diabetes Care 公司 2025 年 2 月發布的“2024 年第四季度及全年財務業績”，其全球 GAAP 銷售額成長 44% 至 2.826 億美元，證實了市場正積極轉向自動化演算法輸注技術。

同時，數位雙胞胎技術的應用正透過動態虛擬化個體獨特的生理功能，重新定義精準代謝照護的概念。這些人工智慧模型將來自感測器的詳細數據與臨床病史相結合，模擬個體對各種生活方式干涉的代謝反應，使醫療服務提供者能夠制定高度個人化的治療方案，旨在逆轉疾病，而不僅僅是控制病情。隨著相關人員認知到該方法在減少長期藥物依賴和改善臨床療效方面的潛力，這種方法正吸引著大量的資本投資。例如，根據2025年8月MobiHealthNews的報導《數位雙胞胎Start-UpsTwin Health融資5,300萬美元，估值接近10億美元》，Twin Health融資5,300萬美元用於擴展其「全身數位雙胞胎」服務。這凸顯了該產業對個人化、數據驅動的緩解策略的策略承諾。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：人工智慧在糖尿病管理領域的全球市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 依設備分類（診斷設備、血糖監測設備、胰島素輸注設備）
    • 透過科技（基於案例的推理、智慧數據分析）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美糖尿病管理人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲糖尿病管理人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區糖尿病管理人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲糖尿病管理人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：人工智慧在南美糖尿病管理領域的市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球糖尿病管理人工智慧市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

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

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
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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