Artificial Intelligence in Diabetes Management Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Device (Diagnostic Devices, Glucose Monitoring Devices, Insulin Delivery Devices), By Technique (Case-Based Reasoning, Intelligent Data Analysis), By Region and Competition, 2021-2031F

Forecast Period	2027-2031
Market Size (2025)	USD 14.73 Billion
CAGR (2026-2031)	8.72%
Fastest Growing Segment	Glucose Monitoring Devices
Largest Market	North America
Market Size (2031)	USD 24.33 Billion

Market Overview

The Global Artificial Intelligence in Diabetes Management Market will grow from USD 14.73 Billion in 2025 to USD 24.33 Billion by 2031 at a 8.72% CAGR. Artificial intelligence in diabetes management encompasses the deployment of machine learning and predictive analytics to interpret physiological data for accurate glycemic control and clinical decision support. The primary drivers propelling this market include the rising global prevalence of chronic metabolic conditions, which creates an urgent need for scalable care systems. Additionally, the imperative to minimize healthcare expenditures associated with long-term complications and the push for personalized therapeutic regimens support the adoption of these automated solutions.

Conversely, market expansion may be impeded by stringent regulatory requirements regarding the validation and liability of algorithmic decision-making. Concerns surrounding data privacy and the security of sensitive patient information also present substantial barriers to broad implementation. According to the International Diabetes Federation, in 2024, an estimated 589 million adults aged 20 to 79 years were living with diabetes globally, underscoring the massive scale of the condition requiring efficient management tools.

Key Market Drivers

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.

Download Free Sample Report

Key Market Challenges

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.

Key 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.

Segmental Insights

The Glucose Monitoring Devices segment represents the fastest-growing category within the global artificial intelligence in diabetes management market. This expansion is primarily driven by the integration of machine learning algorithms into continuous glucose monitoring systems, which enables predictive analysis of blood sugar levels. Recent approvals by regulatory bodies such as the U.S. Food and Drug Administration for AI-enabled sensors have further accelerated the adoption of these technologies. These advancements allow patients and healthcare providers to interpret complex glycemic patterns accurately, facilitating timely interventions and significantly improving long-term disease outcomes.

Regional Insights

North America leads the Global Artificial Intelligence in Diabetes Management Market primarily due to the high adoption of digital health technologies and a well-established healthcare infrastructure. The region faces a substantial demand for automated monitoring tools driven by the rising prevalence of diabetes. Furthermore, growth is accelerated by supportive policies from the U.S. Food and Drug Administration, which actively regulates and clears AI-based medical devices for patient use. This favorable regulatory environment encourages major technology companies to invest in and deploy artificial intelligence solutions for chronic disease management throughout the United States and Canada.

Recent Developments

• In July 2025, Samsung Electronics announced the launch of a beta version of its AI-powered health coach in the United States, following its strategic acquisition of the digital health platform Xealth. This new service, integrated into the Samsung Health application, utilizes artificial intelligence to analyze health records, medication schedules, and daily glucose intake data collected from wearable devices. The initiative aims to facilitate seamless connectivity between patients and healthcare providers by assisting users in adhering to medical advice and prescriptions. This development underscores the tech giant's expanding footprint in the diabetes management sector, leveraging AI to deliver personalized chronic disease management and proactive health monitoring solutions.
• In June 2025, Roche and IBM unveiled an AI-enabled solution resulting from their collaboration to enhance daily diabetes management. The companies introduced the Accu-Chek SmartGuide Predict app, which utilizes IBM’s artificial intelligence and machine learning capabilities to analyze real-time glucose data and predict future fluctuations. This innovative software is designed to forecast glucose levels up to two hours in advance and estimate the risk of hypoglycemia within the next 30 minutes. By providing predictive insights, the solution empowers patients to take proactive measures, such as adjusting medication or carbohydrate intake, thereby improving glycemic control and safety within the Global Artificial Intelligence in Diabetes Management Market.
• In December 2024, Dexcom launched a new generative artificial intelligence feature for its Stelo continuous glucose monitoring system, marking a first for the industry. This update integrated advanced language models to provide users with personalized insights and educational content directly related to their metabolic health data. The AI-driven platform was designed to analyze glucose patterns alongside user-logged data such as sleep, activity, and meals, offering tailored recommendations to improve lifestyle choices. This product launch highlighted the growing role of generative AI in the diabetes management market, moving beyond simple data tracking to provide actionable, context-aware guidance for individuals with Type 2 diabetes or prediabetes who do not use insulin.
• In August 2024, Abbott and Medtronic announced a unique global partnership to collaborate on an integrated digital health solution for diabetes management. This strategic alliance focuses on connecting Abbott’s FreeStyle Libre continuous glucose monitoring sensors with Medtronic’s automated insulin delivery (AID) systems and smart insulin pens. By integrating these leading technologies, the collaboration aims to enable automatic insulin adjustments based on real-time glucose data, leveraging advanced algorithms to keep glucose levels in range. This development represents a significant advancement in the Global Artificial Intelligence in Diabetes Management Market, as it combines widely used sensing technology with sophisticated delivery algorithms to reduce the decision-making burden for millions of people living with diabetes.

Key Market Players

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

By Device	By Technique	By Region
Diagnostic Devices Glucose Monitoring Devices Insulin Delivery Devices	Case-Based Reasoning Intelligent Data Analysis	North America Europe Asia Pacific South America Middle East & Africa

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