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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Global 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 during the forecast period for 2025-2034.

AI in nutrigenomics and personalized nutrition refers to the use of artificial intelligence to analyze genetic, metabolic, and lifestyle data, enabling customized dietary recommendations that optimize individual health, prevent diseases, and enhance overall well-being.

AI in Nutrigenomics and Personalized Nutrition Market

The AI in Nutrigenomics and Personalized Nutrition market is rapidly expanding as artificial intelligence improves genetic data analysis to make accurate dietary recommendations. AI algorithms read genomic, metabolic, and lifestyle data to personalize nutrition plans that maximize individual health outcomes. The increased significance of nutrigenomics comes from the fact that it can connect genes with responses to nutrients, making truly personalized nutrition possible. One of the major drivers for this market is growing consumer interest in data-informed health solutions that avoid chronic conditions, promote wellness, and extend life. Also, advances in genomics, wearable health technology, and machine learning drive adoption across healthcare and nutrition markets.

The AI in nutrigenomics and personalized nutrition market is being driven by the rising adoption of medical wearable devices that track biomarkers such as glucose, heart rate, sleep patterns, and physical activity in real time. These devices develop vast datasets that, when integrated with AI algorithms, allow for highly personalized dietary and health recommendations. The growing consumer preference for data-driven wellness insights, combined with the increasing prevalence of lifestyle-related diseases, is fueling the demand for AI-powered nutrition platforms. Furthermore, healthcare professionals are leveraging wearable-generated data to design adaptive nutritional plans, improving preventive healthcare and personalized treatment outcomes.

Competitive Landscape:

Some of the Key Players in the AI in Nutrigenomics and Personalized Nutrition Market:

·         Appinventiv

·         BetterMeal AI

·         Culina Health

·         DayTwo

·         EatLove

·         LemonBox

·         Nutrify

·         Nourished

·         Nutrino Health

·         Nutrigenomix

·         Persona Nutrition

·         Viome

·         Zoe

Market Segmentation:

The AI in nutrigenomics and personalized nutrition market is segmented by type of product, type of services, type of technology, type of component, application area, type of device, type of deployment mode,  and by region. By type of product, the market is segmented into dietary supplements (vitamins, minerals, probiotics, prebiotics, botanicals, proteins, carbohydrates, and fats), functional foods, and nutraceuticals. By type of services, the market is segmented into dietary assessment, nutrigenomics, personalized meal planning, lifestyle assessment, and health monitoring. By type of technology, the market is segmented into machine learning, natural language processing, computer vision, and predictive analytics. By type of component, the market is segmented into software, hardware, and services. By application area, the market is segmented into weight management, sports nutrition, digestive health, cognitive health, and immune health. By type of device, the market is segmented into wearables, smartphones, and tablets. By type of deployment type, the market is segmented into cloud-based, and on-premises.

By Type of Product, the Dietary Supplements Segment is Expected to Drive the AI in Nutrigenomics and Personalized Nutrition Market 

In 2024, the dietary supplements held the major market share over the projected period due to rising adoption of dietary supplements tailored to individual genetic profiles. Artificial intelligence enables the analysis of genetic, metabolic, and lifestyle data to develop personalised nutrition plans, thereby optimising supplement efficacy and health outcomes. Growing consumer awareness of preventive medicine and chronic disease management is driving the demand for AI-based personalised nutrition. Further boosting market growth worldwide are growing applications of machine learning in diet assessment and predictive health analytics.

Software Segment by Type of Component is Growing at the Highest Rate in the AI in Nutrigenomics and Personalized Nutrition Market

The AI in nutrigenomics and personalized nutrition market is dominated by software due to the growing demand for tailored health and wellness solutions. Increasing health consciousness, combined with rising incidences of lifestyle disorders such as obesity and diabetes, is driving the adoption of AI-based solutions that interpret genomic information for personalized nutrition recommendations. Further, advances in machine learning and bioinformatics, robust research infrastructure, and growing collaborations among biotech firms and healthcare professionals further drive market growth in the region.

Regionally, North America Led the AI in Nutrigenomics and Personalized Nutrition Market

North America dominates the market for AI in nutrigenomics and personalized nutrition due to region’s rising demand for customized dietary plans based on genetic profiles. Growing health awareness, coupled with increasing prevalence of lifestyle-related disorders such as obesity and diabetes, is fueling the adoption of AI-driven solutions that analyse genomic data for personalised nutrition insights. Additionally, advancements in machine learning and bioinformatics, strong research infrastructure, and expanding partnerships between biotech firms and healthcare providers further accelerate market growth in the region.

Moreover, Europe's AI in Nutrigenomics and Personalised Nutrition market is also fueled due to the region’s increasing consumer awareness of personalised health solutions and preventive care. The rising prevalence of lifestyle-related diseases such as obesity, diabetes, and cardiovascular disorders drives demand for tailored nutrition plans. Advances in AI, genomics, and bioinformatics enable the delivery of precise diet recommendations tailored to individual genetic profiles. Additionally, declining costs of genetic testing, supportive government initiatives, and growing investment in health technology startups are accelerating market growth across Europe.

AI in Nutrigenomics and Personalized Nutrition Market Report Scope:

Report Attribute Specifications
Market Size Value In 2024 USD 3.4 Bn
Revenue Forecast In 2034 USD 10.9 Bn
Growth Rate CAGR CAGR of 12.8% from 2025 to 2034
Quantitative Units Representation of revenue in US$ Bn and CAGR from 2025 to 2034
Historic Year 2021 to 2024
Forecast Year 2025-2034
Report Coverage The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends
Segments Covered 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
Regional Scope North America, Europe, Asia Pacific, Latin America, Middle East & Africa
Country Scope U.S., Canada, Germany, The UK, France, Italy, Spain, Rest of Europe, China, Japan, India, South Korea, Southeast Asia, Rest of Asia Pacific, Brazil, Argentina, Mexico, Rest of Latin America, GCC Countries, South Africa, Rest of the Middle East and Africa
Competitive Landscape Appinventiv, BetterMeal AI, Culina Health, DayTwo, EatLove, LemonBox, Nutrify, Nourished, Nutrino Health, Nutrigenomix, Persona Nutrition, Viome, and Zoe
Customization Scope Free customization report with the procurement of the report, Modifications to the regional and segment scope.  Geographic competitive landscape.                     
Pricing and Available Payment Methods Explore pricing alternatives that are customized to your particular study requirements.

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

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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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