Product Code: GVR-4-68040-845-3
AI In Personalized Nutrition Market Summary
The global AI in personalized nutrition market size was estimated at USD 1.54 billion in 2025 and is projected to reach USD 10.21 billion by 2033, growing at a CAGR of 27.21% from 2026 to 2033. Rising prevalence of lifestyle-related and chronic diseases, advances in AI, data analytics, and omics integration, and growing consumer demand for preventive and personalized health solutions are significant factors contributing to market growth.
Moreover, the expansion of digital health ecosystems and enterprise adoption is strengthening the market environment. The increasing prevalence of lifestyle-related and chronic diseases is a key factor driving market growth. Diseases such as obesity, diabetes, cardiovascular disorders, and metabolic syndrome are closely associated with poor dietary habits and sedentary behavior. For instance, according to the International Diabetes Federation (IDF), approximately 589 million people are currently living with diabetes, with an estimated number to reach 853 million by 2050. Conventional dietary guidelines frequently fail to account for individual differences in metabolism, genetics, and health status. AI-powered nutrition platforms facilitate precise dietary interventions by analyzing biometric data, clinical records, and lifestyle information. These technologies enable early risk identification and the development of targeted nutritional recommendations.
Healthcare systems and employers are adopting personalized nutrition tools to enhance preventive care strategies. The emphasis on reducing long-term healthcare costs through nutrition-based interventions is further accelerating market adoption. For instance, in December 2025, Avid Health partnered with Healthnix to strengthen chronic care programs for FQHCs and primary-care practices in Texas by making nutrition education and behavioral skills more accessible to patients. The partnership leverages Aivid's MagSync platform, which aggregates clinical, RPM, and SDOH data, and integrates Healthnix's Medical Nutrition Therapy tools, personalized dietitian advice, and curricula on gut-brain-pain connections.
Furthermore, the increasing availability of affordable wearable devices and at-home testing kits has expanded access to health data, supplying artificial intelligence models with longitudinal datasets for generating highly personalized recommendations. For instance, in May 2025, OURA launched Meals and Glucose features in its ring, integrating AI-driven meal photo analysis with Stelo by Dexcom's FDA-cleared OTC glucose biosensor in the Oura App. Meals provides non-judgmental macronutrient breakdowns, protein/fiber insights, and Oura Advisor guidance for sustainable habits.
"Personalized guidance and insights are essential for helping people understand how their lifestyle choices affect their body, while also encouraging them to make informed health decisions that can improve their overall quality of life. By integrating with OURA, we're bringing the first glucose biosensor and smart ring integration to the market, providing a one-of-a-kind and personalized metabolic health experience that allows users to better understand the link between activity, sleep, stress, nutrition, and their glucose. Through this partnership, we're once again redefining the wearable technology category in the pursuit of empowering people to take control of their health."
Jake Leach, executive vice president and chief operating officer at Dexcom.
Moreover, microbiome analysis of stool samples supports individualized prebiotic interventions, while digital platforms update these recommendations weekly. Thus, such technologies enable dynamic nutrition recommendations that adapt to real-time physiological and behavioral changes, thereby further driving market growth.
Global AI In Personalized Nutrition Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI in personalized nutrition market report based on type, application, end use, and region:
- Type Outlook (Revenue, USD Million, 2021 - 2033)
- AI Nutrition Apps
- Test-based personalization (DNA / Microbiome / Blood)
- Device-linked metabolic platforms
- Enterprise / Clinical platforms
- Application Outlook (Revenue, USD Million, 2021 - 2033)
- AI-Based Meal Planning & Recommendations
- Nutrient & Micronutrient Analysis
- Personalized Supplement Recommendations
- Allergen & Food Sensitivity Identification
- Health & Metabolic Monitoring
- Others
- End Use Outlook (Revenue, USD Million, 2021 - 2033)
- Individuals / Consumers
- Fitness & Wellness Organizations
- Healthcare Providers
- Employers & Enterprises
- Others
- Regional Outlook (Revenue, USD Million, 2021 - 2033)
- North America
- Europe
- Germany
- UK
- France
- Italy
- Spain
- Denmark
- Sweden
- Norway
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Thailand
- Latin America
- MEA
- South Africa
- Saudi Arabia
- UAE
- Kuwait
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation & Scope
- 1.2. Market Definitions
- 1.2.1. Type Segment
- 1.2.2. Application Segment
- 1.2.3. End Use
- 1.3. Information analysis
- 1.3.1. Market formulation & data visualization
- 1.4. Data validation & publishing
- 1.5. Information Procurement
- 1.6. Information or Data Analysis
- 1.7. Market Formulation & Validation
- 1.8. Market Model
- 1.9. Total Market: CAGR Calculation
- 1.10. Objectives
- 1.10.1. Objective 1
- 1.10.2. Objective 2
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Snapshot
- 2.3. Competitive Insights Landscape
Chapter 3. AI in Personalized Nutrition Market Variables, Trends & Scope
- 3.1. Market Lineage Outlook
- 3.1.1. Parent market outlook
- 3.1.2. Related/ancillary market outlook.
- 3.2. Market Dynamics
- 3.2.1. Market driver analysis
- 3.2.2. Market restraint analysis
- 3.2.3. Market opportunity analysis
- 3.2.4. Market challenges analysis
- 3.3. AI in Personalized Nutrition Market Analysis Tools
- 3.3.1. Industry Analysis - Porter's
- 3.3.1.1. Supplier power
- 3.3.1.2. Buyer power
- 3.3.1.3. Substitution threat
- 3.3.1.4. Threat of new entrant
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Technological landscape
- 3.3.2.3. Economic landscape
- 3.3.2.4. Environmental Landscape
- 3.3.2.5. Legal Landscape
- 3.3.2.6. Social Landscape
Chapter 4. AI in Personalized Nutrition Market: Type Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. Global AI in Personalized Nutrition Market Type Movement Analysis
- 4.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by Type, 2021 to 2033 (USD Million)
- 4.4. AI Nutrition Apps
- 4.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 4.5. Test-based personalization (DNA / Microbiome / Blood)
- 4.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 4.6. Device-linked metabolic platforms
- 4.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 4.7. Enterprise / Clinical Platforms
- 4.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
Chapter 5. AI in Personalized Nutrition Market: Application Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. Global AI in Personalized Nutrition Market Application Movement Analysis
- 5.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by Application, 2021 to 2033 (USD Million)
- 5.4. AI-Based Meal Planning & Recommendations
- 5.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 5.5. Nutrient & Micronutrient Analysis
- 5.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 5.6. Personalized Supplement Recommendations
- 5.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 5.7. Allergen & Food Sensitivity Identification
- 5.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 5.8. Health & Metabolic Monitoring
- 5.8.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 5.9. Others
- 5.9.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
Chapter 6. AI in Personalized Nutrition Market: End Use Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. Global AI in Personalized Nutrition Market End Use Movement Analysis
- 6.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by End Use, 2021 to 2033 (USD Million)
- 6.4. Individuals / Consumers
- 6.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 6.5. Fitness & Wellness Organizations
- 6.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 6.6. Healthcare Providers
- 6.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 6.7. Employers & Enterprises
- 6.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
- 6.8. Others
- 6.8.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
Chapter 7. AI in Personalized Nutrition Market: Regional Estimates & Trend Analysis
- 7.1. Regional Market Share Analysis, 2025 & 2033
- 7.2. Regional Market Dashboard
- 7.3. Market Size & Forecasts Trend Analysis, 2021 to 2033:
- 7.4. North America
- 7.4.1. U.S.
- 7.4.1.1. Key country dynamics
- 7.4.1.2. Regulatory framework
- 7.4.1.3. Competitive scenario
- 7.4.1.4. U.S. market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.4.2. Canada
- 7.4.2.1. Key country dynamics
- 7.4.2.2. Regulatory framework
- 7.4.2.3. Competitive scenario
- 7.4.2.4. Canada market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.4.3. Mexico
- 7.4.3.1. Key country dynamics
- 7.4.3.2. Regulatory framework
- 7.4.3.3. Competitive scenario
- 7.4.3.4. Mexico market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5. Europe
- 7.5.1. UK
- 7.5.1.1. Key country dynamics
- 7.5.1.2. Regulatory framework
- 7.5.1.3. Competitive scenario
- 7.5.1.4. UK market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.2. Germany
- 7.5.2.1. Key country dynamics
- 7.5.2.2. Regulatory framework
- 7.5.2.3. Competitive scenario
- 7.5.2.4. Germany market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.3. France
- 7.5.3.1. Key country dynamics
- 7.5.3.2. Regulatory framework
- 7.5.3.3. Competitive scenario
- 7.5.3.4. France market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.4. Italy
- 7.5.4.1. Key country dynamics
- 7.5.4.2. Regulatory framework
- 7.5.4.3. Competitive scenario
- 7.5.4.4. Italy market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.5. Spain
- 7.5.5.1. Key country dynamics
- 7.5.5.2. Regulatory framework
- 7.5.5.3. Competitive scenario
- 7.5.5.4. Spain market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.6. Norway
- 7.5.6.1. Key country dynamics
- 7.5.6.2. Regulatory framework
- 7.5.6.3. Competitive scenario
- 7.5.6.4. Norway market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.7. Sweden
- 7.5.7.1. Key country dynamics
- 7.5.7.2. Regulatory framework
- 7.5.7.3. Competitive scenario
- 7.5.7.4. Sweden market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.5.8. Denmark
- 7.5.8.1. Key country dynamics
- 7.5.8.2. Regulatory framework
- 7.5.8.3. Competitive scenario
- 7.5.8.4. Denmark market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6. Asia Pacific
- 7.6.1. Japan
- 7.6.1.1. Key country dynamics
- 7.6.1.2. Regulatory framework
- 7.6.1.3. Competitive scenario
- 7.6.1.4. Japan market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6.2. China
- 7.6.2.1. Key country dynamics
- 7.6.2.2. Regulatory framework
- 7.6.2.3. Competitive scenario
- 7.6.2.4. China market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6.3. India
- 7.6.3.1. Key country dynamics
- 7.6.3.2. Regulatory framework
- 7.6.3.3. Competitive scenario
- 7.6.3.4. India market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6.4. Australia
- 7.6.4.1. Key country dynamics
- 7.6.4.2. Regulatory framework
- 7.6.4.3. Competitive scenario
- 7.6.4.4. Australia market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6.5. South Korea
- 7.6.5.1. Key country dynamics
- 7.6.5.2. Regulatory framework
- 7.6.5.3. Competitive scenario
- 7.6.5.4. South Korea market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.6.6. Thailand
- 7.6.6.1. Key country dynamics
- 7.6.6.2. Regulatory framework
- 7.6.6.3. Competitive scenario
- 7.6.6.4. Thailand market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.7. Latin America
- 7.7.1. Brazil
- 7.7.1.1. Key country dynamics
- 7.7.1.2. Regulatory framework
- 7.7.1.3. Competitive scenario
- 7.7.1.4. Brazil market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.7.2. Argentina
- 7.7.2.1. Key country dynamics
- 7.7.2.2. Regulatory framework
- 7.7.2.3. Competitive scenario
- 7.7.2.4. Argentina market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.8. MEA
- 7.8.1. South Africa
- 7.8.1.1. Key country dynamics
- 7.8.1.2. Regulatory framework
- 7.8.1.3. Competitive scenario
- 7.8.1.4. South Africa market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.8.2. Saudi Arabia
- 7.8.2.1. Key country dynamics
- 7.8.2.2. Regulatory framework
- 7.8.2.3. Competitive scenario
- 7.8.2.4. Saudi Arabia market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.8.3. UAE
- 7.8.3.1. Key country dynamics
- 7.8.3.2. Regulatory framework
- 7.8.3.3. Competitive scenario
- 7.8.3.4. UAE market estimates and forecasts, 2021 - 2033 (USD Million)
- 7.8.4. Kuwait
- 7.8.4.1. Key country dynamics
- 7.8.4.2. Regulatory framework
- 7.8.4.3. Competitive scenario
- 7.8.4.4. Kuwait market estimates and forecasts, 2021 - 2033 (USD Million)
Chapter 8. Competitive Landscape
- 8.1. Company/Competition Categorization
- 8.2. Strategy Mapping
- 8.3. Company Market Position Analysis, 2025
- 8.4. Company Profiles/Listing
- 8.4.1. Appinventiv
- 8.4.1.1. Company overview
- 8.4.1.2. Financial performance
- 8.4.1.3. Product benchmarking
- 8.4.1.4. Strategic initiatives
- 8.4.2. BetterMeal Al
- 8.4.2.1. Company overview
- 8.4.2.2. Financial performance
- 8.4.2.3. Product benchmarking
- 8.4.2.4. Strategic initiatives
- 8.4.3. BiteAI
- 8.4.3.1. Company overview
- 8.4.3.2. Financial performance
- 8.4.3.3. Product benchmarking
- 8.4.3.4. Strategic initiatives
- 8.4.4. Culina Health
- 8.4.4.1. Company overview
- 8.4.4.2. Financial performance
- 8.4.4.3. Product benchmarking
- 8.4.4.4. Strategic initiatives
- 8.4.5. DayTwo
- 8.4.5.1. Company overview
- 8.4.5.2. Financial performance
- 8.4.5.3. Product benchmarking
- 8.4.5.4. Strategic initiatives
- 8.4.6. EatLove
- 8.4.6.1. Company overview
- 8.4.6.2. Financial performance
- 8.4.6.3. Product benchmarking
- 8.4.6.4. Strategic initiatives
- 8.4.7. EIT Food
- 8.4.7.1. Company overview
- 8.4.7.2. Financial performance
- 8.4.7.3. Product benchmarking
- 8.4.7.4. Strategic initiatives
- 8.4.8. Habit
- 8.4.8.1. Company overview
- 8.4.8.2. Financial performance
- 8.4.8.3. Product benchmarking
- 8.4.8.4. Strategic initiatives
- 8.4.9. InsideTracker
- 8.4.9.1. Company overview
- 8.4.9.2. Financial performance
- 8.4.9.3. Product benchmarking
- 8.4.9.4. Strategic initiatives
- 8.4.10. January AI
- 8.4.10.1. Company overview
- 8.4.10.2. Financial performance
- 8.4.10.3. Product benchmarking
- 8.4.10.4. Strategic initiatives
- 8.4.11. LemonBox
- 8.4.11.1. Company overview
- 8.4.11.2. Financial performance
- 8.4.11.3. Product benchmarking
- 8.4.11.4. Strategic initiatives
- 8.4.12. Nourished
- 8.4.12.1. Company overview
- 8.4.12.2. Financial performance
- 8.4.12.3. Product benchmarking
- 8.4.12.4. Strategic initiatives
- 8.4.13. Nutrigenomix Inc.
- 8.4.13.1. Company overview
- 8.4.13.2. Financial performance
- 8.4.13.3. Product benchmarking
- 8.4.13.4. Strategic initiatives
- 8.4.14. Nutrify LLC
- 8.4.14.1. Company overview
- 8.4.14.2. Financial performance
- 8.4.14.3. Product benchmarking
- 8.4.14.4. Strategic initiatives
- 8.4.15. Nutrino Health Ltd.
- 8.4.15.1. Company overview
- 8.4.15.2. Financial performance
- 8.4.15.3. Product benchmarking
- 8.4.15.4. Strategic initiatives
- 8.4.16. Persona Nutrition
- 8.4.16.1. Company overview
- 8.4.16.2. Financial performance
- 8.4.16.3. Product benchmarking
- 8.4.16.4. Strategic initiatives
- 8.4.17. Spur Fit
- 8.4.17.1. Company overview
- 8.4.17.2. Financial performance
- 8.4.17.3. Product benchmarking
- 8.4.17.4. Strategic initiatives
- 8.4.18. Viome Inc.
- 8.4.18.1. Company overview
- 8.4.18.2. Financial performance
- 8.4.18.3. Product benchmarking
- 8.4.18.4. Strategic initiatives
- 8.4.19. Suggestic Inc.
- 8.4.19.1. Company overview
- 8.4.19.2. Financial performance
- 8.4.19.3. Product benchmarking
- 8.4.19.4. Strategic initiatives
- 8.4.20. Zoe Ltd.
- 8.4.20.1. Company overview
- 8.4.20.2. Financial performance
- 8.4.20.3. Product benchmarking
- 8.4.20.4. Strategic initiatives