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市场调查报告书
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1876661

人工智慧赋能营养配方市场预测至2032年：按技术、应用、最终用户和地区分類的全球分析

AI-Driven Nutritional Formulation Market Forecasts to 2032 - Global Analysis By Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，全球人工智慧营养配方市场预计到 2025 年将达到 12.9 亿美元，到 2032 年将达到 41.3 亿美元，在预测期内的复合年增长率为 18.0%。

人工智慧驱动的营养配方技术利用机器学习、预测模型和深度数据分析，为食品、膳食补充剂和保健品设计高度针对性的营养混合物。透过处理消费者的饮食、生物标记、成分相互作用和代谢行为等信息，人工智慧能够更快、更准确地提供配方建议。这使得研发人员能够优化成分比例、降低研发成本，并透过预测配方在实际应用中的表现来提升营养功效。各大品牌正在利用这些工具打造专注于免疫力、体重管理、提升能量和改善思维清晰度的解决方案。总而言之，人工智慧推动了产品创新，并确保个人化营养解决方案能更好地满足消费者的需求和健康目标。

《Forward Fooding (2025)》报告指出，到2030年，食品配方中的预测分析可透过减少废弃物，每年节省高达1.27亿美元。该报告也引述麦肯锡的估计，人工智慧预计每年创造高达5,000亿美元的全球价值，使包括食品製造业在内的各产业的创新速度翻倍。

对个人化营养的需求日益增长

消费者对个人化饮食解决方案日益增长的兴趣正在推动人工智慧营养处方市场的发展。如今，消费者需要根据自身健康指标、基因资讯、生活方式和健康需求量身定制的营养计划和产品。人工智慧在分析包括生物标记、饮食史和持续健康数据在内的各种数据集方面发挥关键作用，从而製定精准的个人化处方。预防医学意识的增强、慢性病发病率的上升以及改善长期健康的愿望进一步推动了这一趋势。随着人们对精准个人化的期望不断提高，各公司正在利用人工智慧平台开发客製化的营养补充剂、机能性食品和个人化营养方案，加速市场扩张。

高昂的实施成本

人工智慧技术实施成本高是限制人工智慧营养配方市场发展的主要阻碍因素。为了取得显着成效，企业需要在人工智慧软体、资料储存系统、分析引擎和可靠资料集方面投入大量资金。中小製造商往往难以负担这些费用，这限制了它们将人工智慧融入产品开发的能力。此外，维护、网路安全、培训和软体升级等持续性成本进一步加剧了企业的财务压力。这些高昂的支出造成了大中小型企业之间的差距，限制了人工智慧的广泛应用。因此，只有财力雄厚的企业才能部署先进的人工智慧配方工具，减缓了市场整体的成长速度。

扩展我们的个人化营养平台

个人化营养平台的日益普及为人工智慧驱动的营养处方领域带来了巨大的机会。随着人们寻求根据自身生物特征数据、生活习惯和健康目标量身定制的营养方案，人工智慧能够以高效且可扩展的方式实现高级个人化。品牌可以利用整合于穿戴式装置、健康应用程式以及基因和微生物组评估的人工智慧模型，提供持续的洞察和客製化的营养解决方案。这将催生出个人化营养补充品包、客製化饮食计画和订阅式营养服务等选择。随着全球数位健康技术的普及，人工智慧驱动的个人化有望彻底改变消费者的营养体验，并为利用这些先进技术的公司带来巨大的市场扩张。

科技快速过时

技术变革的快速步伐对人工智慧驱动的营养配方产业构成重大威胁。人工智慧模型、计算工具和分析框架频繁更新，迫使企业持续投资系统升级。这些快速发展推高了营运成本，缩短了现有技术的使用寿命。由于资源有限，小规模的公司往往落后于时代，造成竞争不平衡。过时的人工智慧工具会产生不可靠的配方结果，从而可能损害品牌声誉。持续升级、演算法重新训练以及新资料系统的整合增加了复杂性。这种不断适应技术的需求加大了企业的压力，并限制了其製定稳定的长期规划。

新冠疫情的影响：

新冠疫情提升了消费者对增强免疫力、个人化营养和预防医学的关注度，为人工智慧营养配方市场注入了强劲动力。对于寻求实证膳食指导的消费者而言，人工智慧配方工具已成为设计精准营养补充剂和机能性食品的得力助手。远端医疗、数位健康平台和营养管理应用程式的日益普及也推动了人工智慧的应用。儘管供应链受到监管方面的干扰，实体研发流程也出现延误，但对个人化营养解决方案日益增长的需求最终克服了这些障碍。疫情刺激了对人工智慧技术的投资，巩固了数据驱动营养在医疗保健系统和消费者健康市场的长期地位。

预计在预测期内，营养成分分析和平衡细分市场将占据最大的市场份额。

由于营养成分分析和平衡是精准高效产品设计的基础，预计在预测期内，该细分市场将占据最大的市场份额。此细分市场专注于评估营养成分、检验成分协同作用，并确定安全有效产品开发所需的最佳营养水平。人工智慧工具处理生化资料集、饮食行为洞察和成分特性，以设计满足预期健康益处的配方。由于适当的营养平衡对于开发膳食补充剂、机能性食品、个人化饮食以及遵守监管准则至关重要，因此各公司正在广泛使用这些系统。其普遍重要性和基础性意义使其成为最大的细分市场。

预计在预测期内，个人化营养平台细分市场将实现最高的复合年增长率。

受消费者对数据驱动型客製化健康解决方案的强劲需求推动，个人化营养平台领域预计将在预测期内实现最高成长率。这些平台利用人工智慧分析健康追踪器、基因资讯、生物标记测量和生活方式数据等信息，从而製定高度精准的营养计划。数位健康工具、远端医疗服务和持续监测设备的兴起进一步推动了该领域的成长。消费者对个人化营养补充品、动态调整的饮食和机能性食品的需求持续成长。随着全球对预防性医疗保健的日益重视，人工智慧驱动的个人化服务正在迅速发展，使其成为营养技术生态系统中成长最快的领域。

占比最大的地区：

预计北美将在预测期内占据最大的市场份额，这主要得益于其成熟的医疗保健体系、广泛应用的数位健康工具以及大量的研发投入。该地区蓬勃发展的膳食补充剂、机能性食品和健康产业为人工智慧在营养设计领域的应用提供了理想的环境。美国消费者对客製化和预防性营养的高需求正在推动人工智慧技术的应用。充满活力的AIStart-Ups、研究中心和科技公司生态系统正在推动进一步的创新。有利于医疗保健技术和数据驱动型解决方案的法规环境也为成长提供了支持。这些因素共同作用，使北美主导人工智慧营养设计在多元化应用领域的拓展。

年复合成长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率。这一快速成长主要得益于健康意识的提高、智慧型手机和穿戴式装置的普及，以及中国和印度等国家收入的成长。亚太地区越来越多的消费者开始倾向于数据驱动的健康选择、预防性营养和机能性食品。同时，区域政府和企业也在增加对数位健康和​​人工智慧平台的投资。这些因素共同作用，使亚太地区成为人工智慧营养解决方案领域最具活力和成长最快的市场，其成长速度超过了成熟地区。

免费客製化服务：

购买此报告后，您将获得以下免费自订选项之一：

  • 公司概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 主要参与者（最多3家公司）的SWOT分析
  • 区域细分
    • 根据客户要求，提供主要国家的市场估算和预测以及复合年增长率（註：可行性需确认）。
  • 竞争基准化分析
    • 基于产品系列、地域覆盖范围和策略联盟基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 原始研究资料
    • 二手研究资料
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球人工智慧营养配方市场（按技术划分）

  • 介绍
  • 机器学习在预测处方的应用
  • 用于成分标籤和消费者回馈的自然语言处理
  • 电脑视觉在原料品质辨识的应用
  • 具备人工智慧优化功能的处方软体
  • 基于生物标誌物的个人化人工智慧引擎
  • AI-IoT融合实现即时营养监测

6. 全球人工智慧营养配方市场（按应用领域划分）

  • 介绍
  • 原料选择演算法
  • 营养分析与平衡
  • 客製化补充剂设计
  • 机能性食品工程
  • 过敏原和敏感性检测
  • 感觉建模
  • 健康结果预测
  • 适应性营养回馈系统

7. 全球人工智慧营养配方市场（按最终用户划分）

  • 介绍
  • 营养补充品製造商
  • 机能性食品创新者
  • 个人化营养平台
  • 研发实验室和合约配方师
  • 运动营养品牌
  • 宠物营养动物用药品公司
  • 临床和治疗营养提供者

8. 全球人工智慧营养配方市场（按地区划分）

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第九章：重大发展

  • 协议、伙伴关係、合作和合资企业
  • 收购与併购
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十章：企业概况

  • Suggestic
  • EatLove
  • Viome Life Sciences
  • DNAfit（Prenetics）
  • DayTwo Ltd.
  • PIPA AI
  • NutrifyGenie AI
  • Amway
  • Nutrigenie
  • BetterMeal AI
  • Heali AI
  • Habit
  • Bioniq
  • ZOE
  • Nutrino
Product Code: SMRC32345

According to Stratistics MRC, the Global AI-Driven Nutritional Formulation Market is accounted for $1.29 billion in 2025 and is expected to reach $4.13 billion by 2032 growing at a CAGR of 18.0% during the forecast period. AI-powered nutritional formulation uses machine learning, predictive models, and deep data analysis to design highly targeted nutrient blends for foods, supplements, and wellness products. By processing information on consumer diets, biological indicators, ingredient interactions, and metabolic behavior, AI delivers faster and more accurate formulation insights. It enables developers to fine-tune ingredient ratios, lower R&D costs, and enhance nutritional performance by forecasting how formulations will function in real life. Brands apply these tools to create solutions focused on immunity, weight control, energy, or mental clarity. Overall, AI strengthens product innovation and ensures that personalized nutrition solutions better meet consumer needs and health objectives.

According to Forward Fooding (2025), data shows that predictive analytics in food formulation could save up to $127 million annually by 2030 through reduced waste. McKinsey estimates cited in the report suggest that AI could unlock up to $500 billion in annual global value, particularly by doubling the speed of innovation across industries, including food manufacturing.

Market Dynamics:

Driver:

Rising demand for personalized nutrition

Rising interest in personalized dietary solutions is significantly boosting the AI-driven nutritional formulation market. Consumers now want nutrition plans and products designed according to their unique health markers, genetics, lifestyle patterns, and wellness priorities. AI plays a crucial role by analyzing diverse datasets-including biomarkers, dietary history, and continuous health readings-to build precise and individualized formulations. This trend is strengthened by growing awareness of preventive health, increasing chronic illness cases, and the desire for better long-term wellness outcomes. As expectations for highly accurate personalization increase, companies are turning to AI-based platforms to create customized supplements, functional foods, and tailored nutrition programs, accelerating market expansion.

Restraint:

High implementation costs

The substantial cost associated with adopting AI technologies is a key limitation in the AI-driven nutritional formulation market. Organizations must invest heavily in AI software, data storage systems, analytics engines, and reliable datasets to achieve effective outcomes. Smaller manufacturers often find these expenses challenging, restricting their ability to integrate AI into product development. Additional recurring costs-including maintenance, cybersecurity, training, and software upgrades-further increase financial pressure. These high expenditures create disparities between large companies and smaller firms, limiting widespread AI adoption. Consequently, only businesses with strong financial resources can adopt advanced AI-driven formulation tools, slowing the overall growth of market implementation.

Opportunity:

Expansion of personalized nutrition platforms

The growing popularity of personalized nutrition platforms offers a strong opportunity for the AI-driven nutritional formulation sector. As individuals seek nutrition plans tailored to their biological data, lifestyle choices, and wellness objectives, AI makes high-level personalization both efficient and scalable. Brands can use AI models integrated with wearables, health apps, and genetic or microbiome assessments to deliver continuous insights and customized nutrient solutions. This unlocks options such as personalized supplement packs, bespoke diet programs, and subscription-based nutrition services. With digital health adoption rising globally, AI-enabled personalization can reshape consumer nutrition experiences and generate substantial market expansion for companies leveraging these advanced technologies.

Threat:

Rapid technological obsolescence

The fast pace of technological change represents a significant threat to the AI-driven nutritional formulation industry. AI models, computing tools, and analytical frameworks are frequently updated, forcing companies to invest continuously in system upgrades. These rapid advancements raise operational costs and shorten the lifespan of existing technologies. Smaller firms often fall behind due to limited resources, leading to competitive inequality. Outdated AI tools can generate unreliable formulation results, potentially harming brand reputation. Constant upgrades, retraining of algorithms, and integration of new data systems create additional complexity. This ongoing need for technological adaptation increases pressure on organizations and restricts stable long-term planning.

Covid-19 Impact:

The COVID-19 pandemic created strong momentum for the AI-driven nutritional formulation market by elevating consumer interest in immunity enhancement, personalized nutrition, and preventive wellness. As individuals sought scientifically informed dietary guidance, AI-enabled formulation tools became valuable for designing precise supplements and functional foods. Increased reliance on telemedicine, digital health platforms, and nutrition-tracking apps further supported AI adoption. Although restrictions disrupted supply chains and slowed physical R&D processes, the heightened demand for tailored nutrition solutions ultimately outweighed these setbacks. The pandemic encouraged greater investment in AI technologies and reinforced the long-term role of data-driven nutrition in both healthcare systems and consumer health markets.

The nutrient profiling & balancing segment is expected to be the largest during the forecast period

The nutrient profiling & balancing segment is expected to account for the largest market share during the forecast period because it acts as the essential engine behind precise and effective formulation work. This segment focuses on assessing nutrient compositions, evaluating ingredient synergies, and determining optimal nutrient levels to build safe and performance-driven products. AI tools here process biochemical datasets, dietary behavior insights, and ingredient characteristics to design formulas that match desired health benefits. Since proper nutrient balancing is critical for developing supplements, functional foods, personalized diets, and meeting regulatory guidelines, businesses depend on these systems extensively. Its universal relevance and foundational importance position it as the largest market segment.

The personalized nutrition platforms segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the personalized nutrition platforms segment is predicted to witness the highest growth rate because consumers are shifting strongly toward data-driven, customized wellness solutions. These platforms use AI to analyze information from health trackers, genetic insights, biomarker readings, and lifestyle inputs to create highly targeted nutrition plans. The widespread use of digital wellness tools, remote health services, and continuous monitoring devices further boosts this segment's momentum. Demand for individualized supplements, dynamically adjusted diets, and personalized functional foods continue to rise. With increasing global focus on preventive healthcare, AI-powered personalization expands rapidly, making this segment the highest-growing within the nutrition technology ecosystem.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share owing to its mature healthcare systems, extensive use of digital health tools, and heavy R&D spending. The region's thriving nutraceutical, functional-food, and wellness industries make it ideal for leveraging AI in nutrient design. High consumer demand for tailored and preventive nutrition in the U.S. fuels adoption. A thriving ecosystem of AI startups, research centers, and tech companies further propels innovation. Favorable regulatory conditions for health-tech and data-driven solutions also support growth. These combined factors give North America a leading edge in scaling AI-enabled nutritional formulation across applications.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. This surge is driven by growing health consciousness, widespread smartphone and wearable use, and rising incomes in nations such as China and India. More consumers in APAC are gravitating toward data-backed wellness choices, preventive nutrition, and tailored functional foods. At the same time, regional governments and entrepreneurs are ramping up investments in digital health and AI-driven platforms. Together, these factors make Asia-Pacific the most dynamic and rapidly expanding market for AI-based nutrition solutions, surpassing mature regions in growth momentum.

Key players in the market

Some of the key players in AI-Driven Nutritional Formulation Market include Suggestic, EatLove, Viome Life Sciences, DNAfit (Prenetics), DayTwo Ltd., PIPA AI, NutrifyGenie AI, Amway, Nutrigenie, BetterMeal AI, Heali AI, Habit, Bioniq, ZOE and Nutrino.

Key Developments:

In October 2025, Amway will invest USD 12 million in India over the next three to five years to set up stores across the country, which it expects to become among its top three global markets. The company, which has completed ten years of manufacturing in India, is looking to enhance exports from the country, Nelson, who is in his maiden visit to India since assuming the President and CEO role, told PTI Videos in an interview.

In January 2024, Bioniq is thrilled to announce its strategic partnership with Meta, the pioneering hybrid healthcare company combining Digital Therapeutics (DTx) with human-centric clinical care. Bioniq will be serving members under both of Meta's platforms, GluCare.Health and Zone.Health. This collaboration marks a significant milestone in the quest for redefining healthcare services in the GCC, particularly in the realm of metabolic health, chronic disease management, preventive health, and longevity.

In May 2023, Suggestic announced that it has acquired Wishroute, a leading provider of human-powered engagement and healthy habit coaching. The acquisition allows Suggestic to expand its product and service offerings, enter new markets, and accelerate its growth in the Telewellness and Behavioral Engagement market.

Technologies Covered:

  • Machine Learning for Predictive Formulation
  • NLP for Ingredient Labeling & Consumer Feedback
  • Computer Vision for Ingredient Quality & Recognition
  • Formulation Software with AI-Driven Optimization
  • Biomarker-Linked AI Engines for Personalization
  • AI-IoT Integration for Real-Time Nutritional Monitoring

Applications Covered:

  • Ingredient Selection Algorithms
  • Nutrient Profiling & Balancing
  • Custom Supplement Design
  • Functional Food Engineering
  • Allergen & Sensitivity Detection
  • Sensory Modeling
  • Health Outcome Prediction
  • Adaptive Nutrition Feedback Systems

End Users Covered:

  • Nutraceutical Product Manufacturers
  • Functional Food Innovators
  • Personalized Nutrition Platforms
  • R&D Labs & Contract Formulators
  • Sports & Performance Nutrition Brands
  • Pet Nutrition & Animal Health Companies
  • Clinical & Therapeutic Nutrition Providers

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-Driven Nutritional Formulation Market, By Technology

  • 5.1 Introduction
  • 5.2 Machine Learning for Predictive Formulation
  • 5.3 NLP for Ingredient Labeling & Consumer Feedback
  • 5.4 Computer Vision for Ingredient Quality & Recognition
  • 5.5 Formulation Software with AI-Driven Optimization
  • 5.6 Biomarker-Linked AI Engines for Personalization
  • 5.7 AI-IoT Integration for Real-Time Nutritional Monitoring

6 Global AI-Driven Nutritional Formulation Market, By Application

  • 6.1 Introduction
  • 6.2 Ingredient Selection Algorithms
  • 6.3 Nutrient Profiling & Balancing
  • 6.4 Custom Supplement Design
  • 6.5 Functional Food Engineering
  • 6.6 Allergen & Sensitivity Detection
  • 6.7 Sensory Modeling
  • 6.8 Health Outcome Prediction
  • 6.9 Adaptive Nutrition Feedback Systems

7 Global AI-Driven Nutritional Formulation Market, By End User

  • 7.1 Introduction
  • 7.2 Nutraceutical Product Manufacturers
  • 7.3 Functional Food Innovators
  • 7.4 Personalized Nutrition Platforms
  • 7.5 R&D Labs & Contract Formulators
  • 7.6 Sports & Performance Nutrition Brands
  • 7.7 Pet Nutrition & Animal Health Companies
  • 7.8 Clinical & Therapeutic Nutrition Providers

8 Global AI-Driven Nutritional Formulation Market, By Geography

  • 8.1 Introduction
  • 8.2 North America
    • 8.2.1 US
    • 8.2.2 Canada
    • 8.2.3 Mexico
  • 8.3 Europe
    • 8.3.1 Germany
    • 8.3.2 UK
    • 8.3.3 Italy
    • 8.3.4 France
    • 8.3.5 Spain
    • 8.3.6 Rest of Europe
  • 8.4 Asia Pacific
    • 8.4.1 Japan
    • 8.4.2 China
    • 8.4.3 India
    • 8.4.4 Australia
    • 8.4.5 New Zealand
    • 8.4.6 South Korea
    • 8.4.7 Rest of Asia Pacific
  • 8.5 South America
    • 8.5.1 Argentina
    • 8.5.2 Brazil
    • 8.5.3 Chile
    • 8.5.4 Rest of South America
  • 8.6 Middle East & Africa
    • 8.6.1 Saudi Arabia
    • 8.6.2 UAE
    • 8.6.3 Qatar
    • 8.6.4 South Africa
    • 8.6.5 Rest of Middle East & Africa

9 Key Developments

  • 9.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 9.2 Acquisitions & Mergers
  • 9.3 New Product Launch
  • 9.4 Expansions
  • 9.5 Other Key Strategies

10 Company Profiling

  • 10.1 Suggestic
  • 10.2 EatLove
  • 10.3 Viome Life Sciences
  • 10.4 DNAfit (Prenetics)
  • 10.5 DayTwo Ltd.
  • 10.6 PIPA AI
  • 10.7 NutrifyGenie AI
  • 10.8 Amway
  • 10.9 Nutrigenie
  • 10.10 BetterMeal AI
  • 10.11 Heali AI
  • 10.12 Habit
  • 10.13 Bioniq
  • 10.14 ZOE
  • 10.15 Nutrino

List of Tables

  • Table 1 Global AI-Driven Nutritional Formulation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Driven Nutritional Formulation Market Outlook, By Technology (2024-2032) ($MN)
  • Table 3 Global AI-Driven Nutritional Formulation Market Outlook, By Machine Learning for Predictive Formulation (2024-2032) ($MN)
  • Table 4 Global AI-Driven Nutritional Formulation Market Outlook, By NLP for Ingredient Labeling & Consumer Feedback (2024-2032) ($MN)
  • Table 5 Global AI-Driven Nutritional Formulation Market Outlook, By Computer Vision for Ingredient Quality & Recognition (2024-2032) ($MN)
  • Table 6 Global AI-Driven Nutritional Formulation Market Outlook, By Formulation Software with AI-Driven Optimization (2024-2032) ($MN)
  • Table 7 Global AI-Driven Nutritional Formulation Market Outlook, By Biomarker-Linked AI Engines for Personalization (2024-2032) ($MN)
  • Table 8 Global AI-Driven Nutritional Formulation Market Outlook, By AI-IoT Integration for Real-Time Nutritional Monitoring (2024-2032) ($MN)
  • Table 9 Global AI-Driven Nutritional Formulation Market Outlook, By Application (2024-2032) ($MN)
  • Table 10 Global AI-Driven Nutritional Formulation Market Outlook, By Ingredient Selection Algorithms (2024-2032) ($MN)
  • Table 11 Global AI-Driven Nutritional Formulation Market Outlook, By Nutrient Profiling & Balancing (2024-2032) ($MN)
  • Table 12 Global AI-Driven Nutritional Formulation Market Outlook, By Custom Supplement Design (2024-2032) ($MN)
  • Table 13 Global AI-Driven Nutritional Formulation Market Outlook, By Functional Food Engineering (2024-2032) ($MN)
  • Table 14 Global AI-Driven Nutritional Formulation Market Outlook, By Allergen & Sensitivity Detection (2024-2032) ($MN)
  • Table 15 Global AI-Driven Nutritional Formulation Market Outlook, By Sensory Modeling (2024-2032) ($MN)
  • Table 16 Global AI-Driven Nutritional Formulation Market Outlook, By Health Outcome Prediction (2024-2032) ($MN)
  • Table 17 Global AI-Driven Nutritional Formulation Market Outlook, By Adaptive Nutrition Feedback Systems (2024-2032) ($MN)
  • Table 18 Global AI-Driven Nutritional Formulation Market Outlook, By End User (2024-2032) ($MN)
  • Table 19 Global AI-Driven Nutritional Formulation Market Outlook, By Nutraceutical Product Manufacturers (2024-2032) ($MN)
  • Table 20 Global AI-Driven Nutritional Formulation Market Outlook, By Functional Food Innovators (2024-2032) ($MN)
  • Table 21 Global AI-Driven Nutritional Formulation Market Outlook, By Personalized Nutrition Platforms (2024-2032) ($MN)
  • Table 22 Global AI-Driven Nutritional Formulation Market Outlook, By R&D Labs & Contract Formulators (2024-2032) ($MN)
  • Table 23 Global AI-Driven Nutritional Formulation Market Outlook, By Sports & Performance Nutrition Brands (2024-2032) ($MN)
  • Table 24 Global AI-Driven Nutritional Formulation Market Outlook, By Pet Nutrition & Animal Health Companies (2024-2032) ($MN)
  • Table 25 Global AI-Driven Nutritional Formulation Market Outlook, By Clinical & Therapeutic Nutrition Providers (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.