AI in Nutrigenomics and Personalized Nutrition Market Size, Share & Trends Analysis Distribution By Type of Product (Dietary Supplements (Vitamins, Minerals, Probiotics, Prebiotics, Botanicals, Proteins, Carbohydrates, and Fats), Functional Foods, and Nutraceuticals), By Type of Service (Dietary Assessment, Nutrigenomics, Personalized Meal Planning, Lifestyle Assessment, and Health Monitoring), By Type of Technology (Machine Learning, Natural Language Processing, Computer Vision, and Predictive Analytics), by Type of Component (Software, Hardware, and Services), By Application Area (Weight Management, Sports Nutrition, Digestive Health, Cognitive Health, and Immune Health), By Type of Device (Wearables, Smartphones, and Tablets), By Type of Deployment Mode (Cloud-Based, and On-Premises) and Segment Forecasts, 2025-2034

Report Id: 3218 Pages: 180 Last Updated: 14 October 2025 Format: PDF / PPT / Excel / Power BI
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Segmentation of AI in Nutrigenomics and Personalized Nutrition Market -

AI in Nutrigenomics and Personalized Nutrition Market by Type of Product-

·         Dietary Supplements (Vitamins, Minerals, Probiotics, Prebiotics, Botanicals, Proteins, Carbohydrates, and Fats)

·         Functional Foods 

·         Nutraceuticals

AI in Nutrigenomics and Personalized Nutrition Market

AI in Nutrigenomics and Personalized Nutrition Market by Type of Service-

·         Dietary Assessment

·         Nutrigenomics

·         Personalized Meal Planning

·         Lifestyle Assessment

·         Health Monitoring

AI in Nutrigenomics and Personalized Nutrition Market by Type of Technology-

·         Machine Learning

·         Natural Language Processing

·         Computer Vision

·         Predictive Analytics

AI in Nutrigenomics and Personalized Nutrition Market by Type of Component-

·         Software

·         Hardware

·         Services

AI in Nutrigenomics and Personalized Nutrition Market by Application Area-

·         Weight Management

·         Sports Nutrition

·         Digestive Health

·         Cognitive Health

·         Immune Health

AI in Nutrigenomics and Personalized Nutrition Market by Type of Device-

·         Wearables

·         Smartphones

·         Tablets

AI in Nutrigenomics and Personalized Nutrition Market by Deployment Mode-

·         Cloud-Based

·         On-Premises

AI in Nutrigenomics and Personalized Nutrition Market by Region-

North America-

·         The US

·         Canada

Europe-

·         Germany

·         The UK

·         France

·         Italy

·         Spain

·         Rest of Europe

Asia-Pacific-

·         China

·         Japan

·         India

·         South Korea

·         Southeast Asia

·         Rest of Asia Pacific

Latin America-

·         Brazil

·         Argentina

·         Mexico

·         Rest of Latin America

 Middle East & Africa-

·         GCC Countries

·         South Africa

·         Rest of the Middle East and Africa

Chapter 1.    Methodology and Scope
1.1.    Research Methodology
1.2.    Research Scope & Assumptions

Chapter 2.    Executive Summary

Chapter 3.    Global AI in Nutrigenomics and Personalized Nutrition Market Snapshot

Chapter 4.    Global AI in Nutrigenomics and Personalized Nutrition Market Variables, Trends & Scope
4.1.    Market Segmentation & Scope
4.2.    Drivers
4.3.    Challenges
4.4.    Trends 
4.5.    Investment and Funding Analysis 
4.6.    Porter's Five Forces Analysis
4.7.    Incremental Opportunity Analysis (US$ MN), 2025-2034 
4.8.    Competitive Landscape & Market Share Analysis, By Key Player (2024)
4.9.    Use/impact of AI on AI in Nutrigenomics and Personalized Nutrition Market Industry Trends 
4.10.    Global AI in Nutrigenomics and Personalized Nutrition Market Penetration & Growth Prospect Mapping (US$ Mn), 2024-2034

Chapter 5.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 1: By Product, Estimates & Trend Analysis
5.1.    Market Share by Product, 2024 & 2034
5.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Product:

5.2.1.    Dietary Supplements (Vitamins, Minerals, Probiotics, Prebiotics, Botanicals, Proteins, Carbohydrates, and Fats)
5.2.2.    Functional Foods
5.2.3.    Nutraceuticals

Chapter 6.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 2: By Service, Estimates & Trend Analysis
6.1.    Market Share by Service, 2024 & 2034
6.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Service:

6.2.1.    Dietary Assessment
6.2.2.    Nutrigenomics
6.2.3.    Personalized Meal Planning
6.2.4.    Lifestyle Assessment
6.2.5.    Health Monitoring

Chapter 7.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 3: By Application Area, Estimates & Trend Analysis
7.1.    Market Share by Application Area, 2024 & 2034
7.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Application Area:

7.2.1.    Weight Management
7.2.2.    Sports Nutrition
7.2.3.    Digestive Health
7.2.4.    Cognitive Health
7.2.5.    Immune Health

Chapter 8.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 4: By Device, Estimates & Trend Analysis
8.1.    Market Share by Device, 2024 & 2034
8.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Device:

8.2.1.    Wearables
8.2.2.    Smartphones
8.2.3.    Tablets

Chapter 9.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 5: By Component, Estimates & Trend Analysis
9.1.    Market Share by Component, 2024 & 2034
9.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Component:

9.2.1.    Hardware
9.2.2.    Software
9.2.3.    Services

Chapter 10.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 6: By Deployment Mode, Estimates & Trend Analysis
10.1.    Market Share by Deployment Mode, 2024 & 2034
10.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Deployment Mode:

10.2.1.    Cloud-Based
10.2.2.    On-Premise

Chapter 11.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 7: By Technology, Estimates & Trend Analysis
11.1.    Market Share by Technology, 2024 & 2034
11.2.    Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Technology:

11.2.1.    Machine Learning
11.2.2.    Natural Language Processing
11.2.3.    Computer Vision
11.2.4.    Predictive Analytics

Chapter 12.    AI in Nutrigenomics and Personalized Nutrition Market Segmentation 8: Regional Estimates & Trend Analysis
12.1.    Global AI in Nutrigenomics and Personalized Nutrition Market, Regional Snapshot 2024 & 2034
12.2.    North America

12.2.1.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

12.2.1.1.    US
12.2.1.2.    Canada

12.2.2.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Product, 2021-2034
12.2.3.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Service, 2021-2034
12.2.4.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
12.2.5.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Device, 2021-2034
12.2.6.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.2.7.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.2.8.    North America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

12.3.    Europe

12.3.1.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

12.3.1.1.    Germany
12.3.1.2.    U.K.
12.3.1.3.    France
12.3.1.4.    Italy
12.3.1.5.    Spain
12.3.1.6.    Rest of Europe

12.3.2.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Product, 2021-2034
12.3.3.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Service, 2021-2034
12.3.4.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
12.3.5.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Device, 2021-2034
12.3.6.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.3.7.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.3.8.    Europe AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

12.4.    Asia Pacific

12.4.1.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

12.4.1.1.    India 
12.4.1.2.    China
12.4.1.3.    Japan
12.4.1.4.    Australia
12.4.1.5.    South Korea
12.4.1.6.    Hong Kong
12.4.1.7.    Southeast Asia
12.4.1.8.    Rest of Asia Pacific

12.4.2.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Product, 2021-2034
12.4.3.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Service, 2021-2034
12.4.4.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
12.4.5.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Device, 2021-2034
12.4.6.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.4.7.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.4.8.    Asia Pacific AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

12.5.    Latin America

12.5.1.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034

12.5.1.1.    Brazil
12.5.1.2.    Mexico
12.5.1.3.    Rest of Latin America

12.5.2.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Product, 2021-2034
12.5.3.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Service, 2021-2034
12.5.4.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
12.5.5.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Device, 2021-2034
12.5.6.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.5.7.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.5.8.    Latin America AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

12.6.    Middle East & Africa 

12.6.1.    Middle East & Africa Wind Turbine Rotor Blade Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034

12.6.1.1.    GCC Countries
12.6.1.2.    Israel
12.6.1.3.    South Africa
12.6.1.4.    Rest of Middle East and Africa

12.6.2.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Product, 2021-2034
12.6.3.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Service, 2021-2034
12.6.4.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Application Area, 2021-2034
12.6.5.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Device, 2021-2034
12.6.6.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.6.7.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.6.8.    Middle East & Africa AI in Nutrigenomics and Personalized Nutrition Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034

Chapter 13.    Competitive Landscape
13.1.    Major Mergers and Acquisitions/Strategic Alliances
13.2.    Company Profiles
 

13.2.1.    Appinventiv (US)

13.2.1.1.    Business Overview
13.2.1.2.    Key Product/Service Overview
13.2.1.3.    Financial Performance
13.2.1.4.    Geographical Presence
13.2.1.5.    Recent Developments with Business Strategy

13.2.2.    BetterMeal AI (US)
13.2.3.    Culina Health (US)
13.2.4.    DayTwo (US)

13.2.5.    EatLove (US)
13.2.6.    LemonBox (China)
13.2.7.    Nutrify (India)
13.2.8.    Nourished (UK)
13.2.9.    Nutrino Health (Israel)
13.2.10.    Nutrigenomix (Canada)
13.2.11.    Persona Nutrition (US)
13.2.12.    Viome (US)
13.2.13.    Zoe (UK) 

Research Design and Approach

This study employed a multi-step, mixed-method research approach that integrates:

  • Secondary research
  • Primary research
  • Data triangulation
  • Hybrid top-down and bottom-up modelling
  • Forecasting and scenario analysis

This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.

Secondary Research

Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.

Sources Consulted

Secondary data for the market study was gathered from multiple credible sources, including:

  • Government databases, regulatory bodies, and public institutions
  • International organizations (WHO, OECD, IMF, World Bank, etc.)
  • Commercial and paid databases
  • Industry associations, trade publications, and technical journals
  • Company annual reports, investor presentations, press releases, and SEC filings
  • Academic research papers, patents, and scientific literature
  • Previous market research publications and syndicated reports

These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.

Secondary Research

Primary Research

Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.

Stakeholders Interviewed

Primary interviews for this study involved:

  • Manufacturers and suppliers in the market value chain
  • Distributors, channel partners, and integrators
  • End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
  • Industry experts, technology specialists, consultants, and regulatory professionals
  • Senior executives (CEOs, CTOs, VPs, Directors) and product managers

Interview Process

Interviews were conducted via:

  • Structured and semi-structured questionnaires
  • Telephonic and video interactions
  • Email correspondences
  • Expert consultation sessions

Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.

Data Processing, Normalization, and Validation

All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.

The data validation process included:

  • Standardization of units (currency conversions, volume units, inflation adjustments)
  • Cross-verification of data points across multiple secondary sources
  • Normalization of inconsistent datasets
  • Identification and resolution of data gaps
  • Outlier detection and removal through algorithmic and manual checks
  • Plausibility and coherence checks across segments and geographies

This ensured that the dataset used for modelling was clean, robust, and reliable.

Market Size Estimation and Data Triangulation

Bottom-Up Approach

The bottom-up approach involved aggregating segment-level data, such as:

  • Company revenues
  • Product-level sales
  • Installed base/usage volumes
  • Adoption and penetration rates
  • Pricing analysis

This method was primarily used when detailed micro-level market data were available.

Bottom Up Approach

Top-Down Approach

The top-down approach used macro-level indicators:

  • Parent market benchmarks
  • Global/regional industry trends
  • Economic indicators (GDP, demographics, spending patterns)
  • Penetration and usage ratios

This approach was used for segments where granular data were limited or inconsistent.

Hybrid Triangulation Approach

To ensure accuracy, a triangulated hybrid model was used. This included:

  • Reconciling top-down and bottom-up estimates
  • Cross-checking revenues, volumes, and pricing assumptions
  • Incorporating expert insights to validate segment splits and adoption rates

This multi-angle validation yielded the final market size.

Forecasting Framework and Scenario Modelling

Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.

Forecasting Methods

  • Time-series modelling
  • S-curve and diffusion models (for emerging technologies)
  • Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
  • Price elasticity models
  • Market maturity and lifecycle-based projections

Scenario Analysis

Given inherent uncertainties, three scenarios were constructed:

  • Base-Case Scenario: Expected trajectory under current conditions
  • Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
  • Conservative Scenario: Slow adoption, regulatory delays, economic constraints

Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.

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Frequently Asked Questions

The AI in Nutrigenomics and Personalized Nutrition market Size is valued at US$ 3.4 Bn in 2024 and is predicted to reach US$ 10.9 Bn by the year 2034 at an 12.8% CAGR over the forecast period.

The major players in the AI in Nutrigenomics and Personalized Nutrition market are Appinventiv, BetterMeal AI, Culina Health, DayTwo, EatLove, LemonBox, Nutrify, Nourished, Nutrino Health, Nutrigenomix, Persona Nutrition, Viome, and Zoe.

The primary AI in Nutrigenomics and Personalized Nutrition market segments are by type of product, by type of service, by type of technology, by type of component, by application area, by type of device, by type of deployment mode and by region.

North America leads the market for AI in Nutrigenomics and Personalized Nutrition due to advanced technological infrastructure, high healthcare expenditure, and increasing consumer demand for tailored nutrition solutions.

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