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市场调查报告书
商品编码
2007911

人工智慧食谱市场预测至2034年：全球分析（按组件、部署模式、技术类型、解决方案类型、输入类型、企业规模、应用程式、最终用户和地区划分）

AI-Powered Recipe Market Forecasts to 2034 - Global Analysis By Component, Deployment Mode, Technology Type, Solution Type, Input Type, Enterprise Size, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球人工智慧食谱市场预计将在 2026 年达到 17 亿美元，在预测期内以 21.6% 的复合年增长率增长，到 2034 年达到 84 亿美元。

人工智慧驱动的食谱平台利用人工智慧演算法，根据用户偏好、饮食限制、可用食材和营养目标，产生、个人化并优化食谱。这些智慧型系统运用机器学习、自然语言处理和电脑视觉技术，彻底改变了个人和企业烹饪、饮食计划和食材选择的方式。市场涵盖了广泛的解决方案，从面向消费者的应用程式和智慧厨房集成，到面向食品配送服务、酒店餐饮业和零售连锁店的企业平台。

饮食限制和健康意识的提高

消费者越来越倾向于寻求个人化的营养指导，以应对糖尿病、食物过敏、乳糜泻和体重管理等健康问题。传统的食谱资讯来源往往难以满足个体复杂的饮食需求，而人工智慧平台则透过动态筛选和调整食谱来弥补这一不足。这些系统会随着时间的推移学习使用者的偏好，并在保持口味和营养均衡的前提下，为受限食材提案替代方案。随着生酮饮食、纯素和植物性饮食等特定饮食方式的日益普及，人们对能够适应不断变化的营养需求，同时又不牺牲多样性和便捷性的智慧食谱解决方案的需求也进一步增长。

对资料隐私和演算法准确性的担忧

使用者不愿共用个人健康数据、饮食习惯和烹饪行为，是人工智慧食谱平台普及的一大障碍。这些应用通常需要存取敏感讯息，例如医疗状况、连网设备的生物识别数据以及详细的消费模式，才能实现真正意义上的个人化推荐。不准确的食谱推荐，例如未能检测到隐藏的过敏原或错误计算营养价值，可能导致严重的健康问题，并削弱用户对这项技术的信任。此外，严格的地区资料保护条例也给开发者带来了合规负担，增加了营运成本，并延缓了新参与企业的市场准入。

与智慧厨房电器和物联网生态系统集成

智慧烤箱、冷藏库和烹饪助理等连网厨房电器是人工智慧食谱平台的重要成长路径。这些设备的整合能够同步烹饪步骤和电器设置，并根据特定食谱自动调整温度和时间。智慧冷藏库透过管理食物库存、提醒用户食物即将过期以及提案使用现有食材的食谱，帮助减少食物浪费。随着家庭物联网生态系统的扩展，食谱平台与厨房电器之间的无缝互通性创造了极具吸引力的价值提案，将普通用户转变为依赖集成烹饪智能进行日常膳食准备的忠实客户。

免费食谱内容和现有平台的激烈竞争

社交媒体、美食部落格和影片平台上的大量高品质免费食谱内容，给付费的AI食谱解决方案带来了巨大的竞争压力。现有的网站和行动应用程式已经建立了庞大的用户生成食谱库，并配备了先进的搜寻和筛选功能，通常还提供类似的个人化功能，且无需订阅费用。这些平台的优势在于其长期稳定的社群互动、用户信任以及庞大的内容量，而这些对于新进业者来说难以复製。此外，大型科技公司将解决方案整合到现有生态系统中，可能会导致AI食谱功能的商品化，从而可能降低单一供应商的利润率。

新冠疫情的影响：

疫情大大加速了人工智慧食谱解决方案的普及。封锁迫使消费者更频繁地在家中烹饪，同时也要应对食品短缺和供应链中断的问题。居家烹饪者转向数位平台，寻找利用现有食材的创意方法，而人工智慧工具尤其在替代缺失食材、同时保持食谱品质方面发挥了极其重要的作用。疫情期间人们健康意识的提高也促进了对个人化营养和增强免疫力饮食的兴趣。这种行为转变持续存在，许多消费者即使在食品限制放宽后仍然继续使用数位食谱助手，从而导致市场用户群的永久性增长。

在预测期内，大型企业细分市场预计将是规模最大的市场。

在预测期内，「大型企业」细分市场预计将占据最大的市场份额，这主要得益于其对人工智慧基础设施的大量投资以及全公司范围内的数位转型 (DX) 倡议。领先的食品配送平台、连锁饭店和零售食品公司正在大规模采用人工智慧食谱技术，以提升客户参与、简化营运流程，并在竞争激烈的市场中实现服务差异化。这些企业拥有必要的财力，可以进行客製化部署、与现有系统整合以及获得持续的技术支援。大型企业能够跨多个品牌、地区和消费者触点有效利用人工智慧食谱解决方案，这将确保它们在整个预测期内保持市场主导地位。

在预测期内，「个人化饮食计画」细分市场预计将实现最高的复合年增长率。

在预测期内，「个人化饮食计画」细分市场预计将呈现最高的成长率，这主要得益于消费者对个人化营养需求的日益增长以及人工智慧技术在处理复杂饮食数据方面的进步。这些应用超越了简单的食谱提案，整合了基因资讯、微生物组分析、即时血糖值监测和生活方式因素，从而产生高度个人化的饮食计划。肥胖和METABOLIC INC.症候群等与饮食相关的慢性疾病日益普遍，也促使消费者和医疗保健相关人员更加关注精准营养解决方案。随着穿戴式健康设备的普及以及用户逐渐习惯于持续接收生物特征数据回馈，个人化饮食规划平台预计将大幅成长。

市占率最大的地区：

在预测期内，北美预计将占据最大的市场份额，这主要得益于智慧型手机的高普及率、消费者在健康和保健领域的强劲支出，以及智慧厨房技术的早期应用。该地区聚集了众多领先的人工智慧技术公司、食品配送平台和零售创新者，它们正积极将智慧食谱融入自身的服务中。美国和加拿大的文化多样性催生了对能够满足不同饮食文化和习惯的高级个人化食谱的需求。创业投资对食品科技Start-Ups的强劲投入进一步加速了创新，并确保北美在整个预测期内保持市场领先地位。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于快速的数位化、不断壮大的中产阶级以及全部区域深厚的饮食文化底蕴。中国、印度、日本和韩国等国家以行动优先的人工智慧应用正蓬勃发展，消费者也越来越多地利用科技手段进行烹饪指导和膳食管理。由于该地区存在一些特殊的饮食需求，例如乳糖不耐受和不同的宗教饮食习惯，因此对个人化食谱解决方案的需求十分旺盛。政府推行的数位健康措施以及本地外送平台的蓬勃发展，进一步加速了全部区域的市场扩张。

免费客製化服务：

所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域细分
    • 应客户要求，我们提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需进行可行性检查）。
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 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
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球人工智慧食谱市场：按成分划分

  • 软体
    • 食谱生成平台
    • 营养分析软体
    • 膳食计划引擎
  • 服务
    • 整合与部署
    • 咨询
    • 支援与维护

第六章：全球人工智慧食谱市场：按部署模式划分

  • 基于云端的
  • 现场
  • 杂交种

第七章：全球人工智慧食谱市场：按技术类型划分

  • 基于机器学习的系统
  • 基于自然语言处理的系统
  • 基于电脑视觉的系统
  • 生成式人工智慧模型
  • 语音人工智慧与互动式系统

第八章：全球人工智慧食谱市场：按解决方案类型划分

  • 人工智慧驱动的膳食计划
  • 即时食谱提案
  • 食品替代品系统
  • 智能烹饪助手
  • 个性化食谱优化

第九章：全球人工智慧食谱市场：按输入类型划分

  • 基于文字的食谱产生工具
  • 基于图像的食谱生成工具
  • 基于影片的食谱产生工具
  • 语音控制食谱系统

第十章：全球人工智慧食谱市场：按公司规模划分

  • 大公司
  • 小型企业

第十一章：全球人工智慧食谱市场：按应用领域划分

  • 个人化膳食计划
  • 智慧厨房
  • 食品配送平台
  • 健康与保健应用程式
  • 饭店餐饮业
  • 零售和杂货平台

第十二章：全球人工智慧食谱市场：按最终用户划分

  • 个人消费者
  • 餐厅及餐饮服务供应商
  • 食品製造商
  • 註册营养师
  • 零售与电子商务平台
  • 内容创作者与美食部落客

第十三章：全球人工智慧食谱市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十四章 策略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十五章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十六章：公司简介

  • IBM
  • Google
  • Microsoft
  • Amazon
  • Samsung Electronics
  • Whirlpool Corporation
  • SideChef Group
  • Innit
  • Plant Jammer
  • DishGen
  • Chef Watson
  • Yummly
  • Cookpad
  • Tasty
  • Blue Apron
Product Code: SMRC34755

According to Stratistics MRC, the Global AI-Powered Recipe Market is accounted for $1.7 billion in 2026 and is expected to reach $8.4 billion by 2034 growing at a CAGR of 21.6% during the forecast period. AI-powered recipe platforms utilize artificial intelligence algorithms to generate, personalize, and optimize recipes based on user preferences, dietary restrictions, available ingredients, and nutritional goals. These intelligent systems leverage machine learning, natural language processing, and computer vision to transform how individuals and businesses approach cooking, meal planning, and food discovery. The market encompasses solutions ranging from consumer-facing apps and smart kitchen integrations to enterprise platforms serving food delivery services, hospitality establishments, and retail grocery chains.

Market Dynamics:

Driver:

Rising prevalence of dietary restrictions and health consciousness

Consumers increasingly seek personalized nutrition guidance to manage conditions such as diabetes, food allergies, celiac disease, and weight management goals. Traditional recipe resources often fail to accommodate the complexity of individual dietary needs, creating a gap that AI-powered platforms fill by dynamically filtering and modifying recipes. These systems learn user preferences over time, suggesting alternatives for restricted ingredients while maintaining flavor profiles and nutritional balance. The growing adoption of specialized eating patterns, including keto, vegan, and plant-based diets, further amplifies demand for intelligent recipe solutions that can adapt to evolving nutritional requirements without sacrificing variety or convenience.

Restraint:

Concerns over data privacy and algorithmic accuracy

User hesitation around sharing personal health data, dietary habits, and kitchen behaviors poses a barrier to widespread adoption of AI recipe platforms. These applications often require access to sensitive information including medical conditions, biometric data from connected devices, and detailed consumption patterns to deliver meaningful personalization. Instances of inaccurate recipe recommendations such as failing to detect a hidden allergen or miscalculating nutritional values can lead to serious health consequences, eroding trust in the technology. Strict data protection regulations across regions also create compliance burdens for developers, increasing operational costs and slowing market entry for new players.

Opportunity:

Integration with smart kitchen appliances and IoT ecosystems

Connected kitchen devices, including smart ovens, refrigerators, and cooking assistants, present a significant growth avenue for AI-powered recipe platforms. When integrated, these systems can synchronize cooking instructions with appliance settings, automatically adjusting temperatures and timers based on the specific recipe. Smart refrigerators can inventory ingredients, notify users of expiring items, and suggest recipes that utilize available foods, reducing waste. As the Internet of Things ecosystem expands within households, seamless interoperability between recipe platforms and kitchen hardware creates compelling value propositions, converting casual users into engaged customers who rely on integrated culinary intelligence for daily meal preparation.

Threat:

Intense competition from free recipe content and established platforms

The abundance of free, high-quality recipe content available through social media, food blogs, and video platforms creates significant competitive pressure on paid AI-powered solutions. Established websites and mobile applications have built extensive libraries of user-generated recipes with sophisticated search and filtering capabilities, often offering similar personalization without subscription fees. These platforms benefit from years of community engagement, user trust, and content volume that new entrants find difficult to replicate. Furthermore, large technology companies are entering the space with integrated solutions bundled into existing ecosystems, potentially commoditizing AI recipe functionality and eroding margins for standalone providers.

Covid-19 Impact:

The pandemic profoundly accelerated adoption of AI-powered recipe solutions as lockdowns forced consumers to cook more frequently at home while navigating ingredient shortages and supply chain disruptions. Home cooks turned to digital platforms for creative ways to use available pantry items, with AI tools proving particularly valuable for substituting missing ingredients while maintaining recipe integrity. The surge in health awareness during the pandemic also heightened interest in personalized nutrition and immune-supporting meals. This behavioral shift has proven durable, with many consumers retaining the habit of using digital recipe assistants even after dining restrictions eased, permanently expanding the market's user base.

The Large Enterprises segment is expected to be the largest during the forecast period

The Large Enterprises segment is expected to account for the largest market share during the forecast period, driven by substantial investments in AI infrastructure and enterprise-wide digital transformation initiatives. Major food delivery platforms, hospitality chains, and retail grocery corporations deploy AI recipe technology at scale to enhance customer engagement, streamline operations, and differentiate their offerings in competitive markets. These organizations possess the capital resources necessary for custom implementations, integration with existing systems, and ongoing technical support. The ability of large enterprises to leverage AI recipe solutions across multiple brands, regions, and consumer touchpoints ensures their continued dominance throughout the forecast timeline.

The Personalized Diet Planning segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Personalized Diet Planning segment is predicted to witness the highest growth rate, reflecting the convergence of consumer demand for individualized nutrition with advancements in AI's ability to process complex dietary data. These applications go beyond simple recipe suggestions, incorporating genetic information, microbiome analysis, real-time glucose monitoring, and lifestyle factors to generate hyper-personalized meal plans. The rising prevalence of chronic conditions linked to diet, such as obesity and metabolic syndrome, drives both consumer and healthcare interest in precision nutrition solutions. As wearable health devices proliferate and users become accustomed to continuous biometric feedback, personalized diet planning platforms are positioned for exceptional expansion.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by high smartphone penetration, strong consumer spending on health and wellness, and early adoption of connected kitchen technologies. The region hosts a concentration of leading AI technology firms, food delivery platforms, and retail innovators that are actively integrating recipe intelligence into their service offerings. Cultural diversity across the United States and Canada creates demand for sophisticated recipe personalization capable of accommodating varied culinary traditions and dietary practices. Robust venture capital investment in food-tech startups further accelerates innovation, ensuring North America maintains its market leadership throughout the forecast period.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid digitalization, expanding middle-class populations, and the deep cultural significance of culinary diversity across the region. Countries including China, India, Japan, and South Korea are witnessing surging adoption of mobile-first AI applications, with consumers increasingly turning to technology for cooking guidance and dietary management. The region's high prevalence of specific dietary requirements, including lactose intolerance and diverse religious dietary practices, creates strong demand for personalized recipe solutions. Government initiatives promoting digital health and the proliferation of regional food delivery platforms further accelerate market expansion throughout Asia Pacific.

Key players in the market

Some of the key players in AI-Powered Recipe Market include IBM, Google, Microsoft, Amazon, Samsung Electronics, Whirlpool Corporation, SideChef Group, Innit, Plant Jammer, DishGen, Chef Watson, Yummly, Cookpad, Tasty, and Blue Apron.

Key Developments:

In March 2026, IBM announced the expansion of its watsonx orchestration platform to include advanced agentic AI capabilities. While the original "Chef Watson" project has been absorbed into the broader IBM Watson research legacy, the new watsonx.governance and Orchestrate tools are being used by enterprise food clients to manage supply chains and "agentic" recipe development workflows.

In February 2026, At KBIS 2026, Samsung debuted the Bespoke AI 3-Door French Door Refrigerator. It's "AI Vision Inside" feature can now identify 33 different fresh food items and automatically suggest recipes via the 9-inch AI Home Display before the items expire.

In May 2025, Microsoft launched new "Kitchen Copilot" templates for developers on Azure. This enables recipe platforms (like SideChef) to use Microsoft's multimodal models to convert cooking videos into structured, shoppable step-by-step guides automatically.

Components Covered:

  • Hardware
  • Services

Deployment Modes Covered:

  • Cloud-Based
  • On-Premise
  • Hybrid

Technology Types Covered:

  • Machine Learning-Based Systems
  • Natural Language Processing-Based Systems
  • Computer Vision-Based Systems
  • Generative AI Models
  • Voice AI & Conversational Systems

Solution Types Covered:

  • AI-Based Meal Planning
  • Real-Time Recipe Suggestions
  • Ingredient Substitution Systems
  • Smart Cooking Assistants
  • Personalized Recipe Optimization

Input Types Covered:

  • Text-Based Recipe Generators
  • Image-Based Recipe Generators
  • Video-Based Recipe Generators
  • Voice-Enabled Recipe Systems

Enterprise Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises

Applications Covered:

  • Personalized Diet Planning
  • Smart Kitchens
  • Food Delivery Platforms
  • Health & Wellness Apps
  • Hospitality & Restaurants
  • Retail & Grocery Platforms

End Users Covered:

  • Individual Consumers
  • Restaurants & Food Service Providers
  • Food Manufacturers
  • Nutritionists & Dieticians
  • Retail & E-commerce Platforms
  • Content Creators & Food Bloggers

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI-Powered Recipe Market, By Component

  • 5.1 Software
    • 5.1.1 Recipe Generation Platforms
    • 5.1.2 Nutrition Analysis Software
    • 5.1.3 Meal Planning Engines
  • 5.2 Services
    • 5.2.1 Integration & Deployment
    • 5.2.2 Consulting
    • 5.2.3 Support & Maintenance

6 Global AI-Powered Recipe Market, By Deployment Mode

  • 6.1 Cloud-Based
  • 6.2 On-Premise
  • 6.3 Hybrid

7 Global AI-Powered Recipe Market, By Technology Type

  • 7.1 Machine Learning-Based Systems
  • 7.2 Natural Language Processing-Based Systems
  • 7.3 Computer Vision-Based Systems
  • 7.4 Generative AI Models
  • 7.5 Voice AI & Conversational Systems

8 Global AI-Powered Recipe Market, By Solution Type

  • 8.1 AI-Based Meal Planning
  • 8.2 Real-Time Recipe Suggestions
  • 8.3 Ingredient Substitution Systems
  • 8.4 Smart Cooking Assistants
  • 8.5 Personalized Recipe Optimization

9 Global AI-Powered Recipe Market, By Input Type

  • 9.1 Text-Based Recipe Generators
  • 9.2 Image-Based Recipe Generators
  • 9.3 Video-Based Recipe Generators
  • 9.4 Voice-Enabled Recipe Systems

10 Global AI-Powered Recipe Market, By Enterprise Size

  • 10.1 Large Enterprises
  • 10.2 Small & Medium Enterprises

11 Global AI-Powered Recipe Market, By Application

  • 11.1 Personalized Diet Planning
  • 11.2 Smart Kitchens
  • 11.3 Food Delivery Platforms
  • 11.4 Health & Wellness Apps
  • 11.5 Hospitality & Restaurants
  • 11.6 Retail & Grocery Platforms

12 Global AI-Powered Recipe Market, By End User

  • 12.1 Individual Consumers
  • 12.2 Restaurants & Food Service Providers
  • 12.3 Food Manufacturers
  • 12.4 Nutritionists & Dieticians
  • 12.5 Retail & E-commerce Platforms
  • 12.6 Content Creators & Food Bloggers

13 Global AI-Powered Recipe Market, By Geography

  • 13.1 North America
    • 13.1.1 United States
    • 13.1.2 Canada
    • 13.1.3 Mexico
  • 13.2 Europe
    • 13.2.1 United Kingdom
    • 13.2.2 Germany
    • 13.2.3 France
    • 13.2.4 Italy
    • 13.2.5 Spain
    • 13.2.6 Netherlands
    • 13.2.7 Belgium
    • 13.2.8 Sweden
    • 13.2.9 Switzerland
    • 13.2.10 Poland
    • 13.2.11 Rest of Europe
  • 13.3 Asia Pacific
    • 13.3.1 China
    • 13.3.2 Japan
    • 13.3.3 India
    • 13.3.4 South Korea
    • 13.3.5 Australia
    • 13.3.6 Indonesia
    • 13.3.7 Thailand
    • 13.3.8 Malaysia
    • 13.3.9 Singapore
    • 13.3.10 Vietnam
    • 13.3.11 Rest of Asia Pacific
  • 13.4 South America
    • 13.4.1 Brazil
    • 13.4.2 Argentina
    • 13.4.3 Colombia
    • 13.4.4 Chile
    • 13.4.5 Peru
    • 13.4.6 Rest of South America
  • 13.5 Rest of the World (RoW)
    • 13.5.1 Middle East
      • 13.5.1.1 Saudi Arabia
      • 13.5.1.2 United Arab Emirates
      • 13.5.1.3 Qatar
      • 13.5.1.4 Israel
      • 13.5.1.5 Rest of Middle East
    • 13.5.2 Africa
      • 13.5.2.1 South Africa
      • 13.5.2.2 Egypt
      • 13.5.2.3 Morocco
      • 13.5.2.4 Rest of Africa

14 Strategic Market Intelligence

  • 14.1 Industry Value Network and Supply Chain Assessment
  • 14.2 White-Space and Opportunity Mapping
  • 14.3 Product Evolution and Market Life Cycle Analysis
  • 14.4 Channel, Distributor, and Go-to-Market Assessment

15 Industry Developments and Strategic Initiatives

  • 15.1 Mergers and Acquisitions
  • 15.2 Partnerships, Alliances, and Joint Ventures
  • 15.3 New Product Launches and Certifications
  • 15.4 Capacity Expansion and Investments
  • 15.5 Other Strategic Initiatives

16 Company Profiles

  • 16.1 IBM
  • 16.2 Google
  • 16.3 Microsoft
  • 16.4 Amazon
  • 16.5 Samsung Electronics
  • 16.6 Whirlpool Corporation
  • 16.7 SideChef Group
  • 16.8 Innit
  • 16.9 Plant Jammer
  • 16.10 DishGen
  • 16.11 Chef Watson
  • 16.12 Yummly
  • 16.13 Cookpad
  • 16.14 Tasty
  • 16.15 Blue Apron

List of Tables

  • Table 1 Global AI-Powered Recipe Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Recipe Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Powered Recipe Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global AI-Powered Recipe Market Outlook, By Recipe Generation Platforms (2023-2034) ($MN)
  • Table 5 Global AI-Powered Recipe Market Outlook, By Nutrition Analysis Software (2023-2034) ($MN)
  • Table 6 Global AI-Powered Recipe Market Outlook, By Meal Planning Engines (2023-2034) ($MN)
  • Table 7 Global AI-Powered Recipe Market Outlook, By Services (2023-2034) ($MN)
  • Table 8 Global AI-Powered Recipe Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 9 Global AI-Powered Recipe Market Outlook, By Consulting (2023-2034) ($MN)
  • Table 10 Global AI-Powered Recipe Market Outlook, By Support & Maintenance (2023-2034) ($MN)
  • Table 11 Global AI-Powered Recipe Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 12 Global AI-Powered Recipe Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 13 Global AI-Powered Recipe Market Outlook, By On-Premise (2023-2034) ($MN)
  • Table 14 Global AI-Powered Recipe Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 15 Global AI-Powered Recipe Market Outlook, By Technology Type (2023-2034) ($MN)
  • Table 16 Global AI-Powered Recipe Market Outlook, By Machine Learning-Based Systems (2023-2034) ($MN)
  • Table 17 Global AI-Powered Recipe Market Outlook, By Natural Language Processing-Based Systems (2023-2034) ($MN)
  • Table 18 Global AI-Powered Recipe Market Outlook, By Computer Vision-Based Systems (2023-2034) ($MN)
  • Table 19 Global AI-Powered Recipe Market Outlook, By Generative AI Models (2023-2034) ($MN)
  • Table 20 Global AI-Powered Recipe Market Outlook, By Voice AI & Conversational Systems (2023-2034) ($MN)
  • Table 21 Global AI-Powered Recipe Market Outlook, By Solution Type (2023-2034) ($MN)
  • Table 22 Global AI-Powered Recipe Market Outlook, By AI-Based Meal Planning (2023-2034) ($MN)
  • Table 23 Global AI-Powered Recipe Market Outlook, By Real-Time Recipe Suggestions (2023-2034) ($MN)
  • Table 24 Global AI-Powered Recipe Market Outlook, By Ingredient Substitution Systems (2023-2034) ($MN)
  • Table 25 Global AI-Powered Recipe Market Outlook, By Smart Cooking Assistants (2023-2034) ($MN)
  • Table 26 Global AI-Powered Recipe Market Outlook, By Personalized Recipe Optimization (2023-2034) ($MN)
  • Table 27 Global AI-Powered Recipe Market Outlook, By Input Type (2023-2034) ($MN)
  • Table 28 Global AI-Powered Recipe Market Outlook, By Text-Based Recipe Generators (2023-2034) ($MN)
  • Table 29 Global AI-Powered Recipe Market Outlook, By Image-Based Recipe Generators (2023-2034) ($MN)
  • Table 30 Global AI-Powered Recipe Market Outlook, By Video-Based Recipe Generators (2023-2034) ($MN)
  • Table 31 Global AI-Powered Recipe Market Outlook, By Voice-Enabled Recipe Systems (2023-2034) ($MN)
  • Table 32 Global AI-Powered Recipe Market Outlook, By Enterprise Size (2023-2034) ($MN)
  • Table 33 Global AI-Powered Recipe Market Outlook, By Large Enterprises (2023-2034) ($MN)
  • Table 34 Global AI-Powered Recipe Market Outlook, By Small & Medium Enterprises (2023-2034) ($MN)
  • Table 35 Global AI-Powered Recipe Market Outlook, By Application (2023-2034) ($MN)
  • Table 36 Global AI-Powered Recipe Market Outlook, By Personalized Diet Planning (2023-2034) ($MN)
  • Table 37 Global AI-Powered Recipe Market Outlook, By Smart Kitchens (2023-2034) ($MN)
  • Table 38 Global AI-Powered Recipe Market Outlook, By Food Delivery Platforms (2023-2034) ($MN)
  • Table 39 Global AI-Powered Recipe Market Outlook, By Health & Wellness Apps (2023-2034) ($MN)
  • Table 40 Global AI-Powered Recipe Market Outlook, By Hospitality & Restaurants (2023-2034) ($MN)
  • Table 41 Global AI-Powered Recipe Market Outlook, By Retail & Grocery Platforms (2023-2034) ($MN)
  • Table 42 Global AI-Powered Recipe Market Outlook, By End User (2023-2034) ($MN)
  • Table 43 Global AI-Powered Recipe Market Outlook, By Individual Consumers (2023-2034) ($MN)
  • Table 44 Global AI-Powered Recipe Market Outlook, By Restaurants & Food Service Providers (2023-2034) ($MN)
  • Table 45 Global AI-Powered Recipe Market Outlook, By Food Manufacturers (2023-2034) ($MN)
  • Table 46 Global AI-Powered Recipe Market Outlook, By Nutritionists & Dieticians (2023-2034) ($MN)
  • Table 47 Global AI-Powered Recipe Market Outlook, By Retail & E-commerce Platforms (2023-2034) ($MN)
  • Table 48 Global AI-Powered Recipe Market Outlook, By Content Creators & Food Bloggers (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.