2026 Global: Artificial Intelligence (Ai) In Food And Beverage Market -Competitive Review (2032) report
Description
The 2026 Global: Artificial Intelligence (Ai) In Food And Beverage Market -Competitive Review (2031) report features the global market size and projected growth/decline data for the period 2021 through 2032. The report primarily provides an examination of the business strategies for the ten largest global companies in the market and how their strategies differ.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for artificial intelligence (ai) in food and beverage market by geography and historical trend. The scope of the report extends to sizing of the artificial intelligence (ai) in food and beverage market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
Coca‑Cola, Nestlé, PepsiCo, Starbucks, McDonald’s, Kraft Heinz, NotCo, NVIDIA, IBM, and Amazon are among the ten major companies shaping the Artificial Intelligence in Food and Beverage market through applications spanning product innovation, quality control, supply‑chain optimization, personalization, and food‑service automation. Coca‑Cola uses AI-driven consumer and vending‑machine data to create new flavours and personalise offerings, while also applying computer vision and predictive analytics to manufacturing and packaging operations. Nestlé deploys proprietary AI tools across R&D, demand forecasting, and enterprise functions—reducing product ideation time significantly and running internal large‑language model tools (NesGPT) for sales, marketing, and legal workflows. PepsiCo leverages AI for demand forecasting and supply‑chain optimisation, combining consumer behaviour and external data (for example weather) to better align production schedules and reduce waste. Starbucks applies AI (Deep Brew) for personalised recommendations, demand forecasting, site selection, and operational automation within its mobile app and store operations to enhance customer lifetime value and inventory planning. McDonald’s implements AI for dynamic menu personalization and predictive decisioning in restaurants via partnerships (for example Dynamic Yield) to tailor orders by time, traffic, and local popularity. Kraft Heinz has realised measurable revenue gains by deploying AI platforms (e.g., Lighthouse) focused on operational intelligence, logistics, and promotion optimisation, reporting tens of millions in sales impact from AI initiatives. NotCo is an AI‑native food company using its Giuseppe system to analyse ingredient properties and consumer preferences to design plant‑based products that mimic animal counterparts, exemplifying how generative and data‑driven food R&D can create new product lines and accelerate go‑to‑market timelines. NVIDIA provides the hardware and software stack (GPUs, inference platforms, and edge AI tools) that enables computer vision, deep learning, and real‑time analytics in food manufacturing, inspection systems, robotics, and personalised retail applications across the sector. IBM supplies AI and enterprise analytics tools (including Watson‑class offerings) used for food safety, traceability, predictive maintenance, and quality assurance workflows that are critical for regulatory compliance and risk reduction in food production. Amazon combines AI across grocery retail (demand prediction, cashierless stores), supply‑chain logistics, and cloud/ML services (AWS) that food and beverage companies use to run large models, scale analytics, and deploy AI‑powered customer experiences and automated fulfilment.
These companies collectively span three complementary roles in the AI in Food & Beverage market: global consumer brands that embed AI into products and operations (Coca‑Cola, Nestlé, PepsiCo, Starbucks, McDonald’s, Kraft Heinz, NotCo), technology and platform providers that supply compute, models, and enterprise AI services (NVIDIA, IBM, Amazon), and cross‑industry integrators whose solutions accelerate adoption across manufacturing, retail, and food service. Adoption hotspots include computer vision for quality control and packaging, predictive forecasting to reduce waste and optimise inventory, generative AI for recipe and product ideation, personalization engines for retail and foodservice, and robotic/automation systems for packaging and sorting—areas where the listed companies either deploy AI at scale or provide the enabling technology to do so.
Perry/Hope Partners' reports provide the most accurate industry forecasts based on our proprietary economic models. Our forecasts project the product market size nationally and by regions for 2021 to 2032 using regression analysis in our modeling. and Perry/Hope is the only market research publisher that utilizes both longitudinal (historical) and vertical (from market section to market division to market class) analysis, since we study every manufactured product in the countries we analyze. The report also provides written analysis on the market definition, market segments, and SWOT analysis (market strengths, weaknesses, opportunities, and threats).
The market study aims at estimating the market size and the growth potential of this market. Topics analyzed within the report include a detailed breakdown of the global markets for artificial intelligence (ai) in food and beverage market by geography and historical trend. The scope of the report extends to sizing of the artificial intelligence (ai) in food and beverage market market and global market trends with market data for 2024 as the base year, 2025 and 2026 as the estimate years with projection of CAGR from 2027 to 2032.
The report also features a list of the top ten largest global players in the market. A review of each company includes 1) an estimate of the market share, 2) a listing of the products and/or services in the market, and 3) the features of these products and/or services in the market. The report has a chapter on Comparative Business Strategies for the largest four players. An example of the Comparative Business Strategies analysis would be -- How does Netflix's business strategy to expand its market share in the global online streaming compare to Amazon Prime's business strategy through its video products and services?
The ten market players in this report and a brief synopsis of their participation in the market are:
Coca‑Cola, Nestlé, PepsiCo, Starbucks, McDonald’s, Kraft Heinz, NotCo, NVIDIA, IBM, and Amazon are among the ten major companies shaping the Artificial Intelligence in Food and Beverage market through applications spanning product innovation, quality control, supply‑chain optimization, personalization, and food‑service automation. Coca‑Cola uses AI-driven consumer and vending‑machine data to create new flavours and personalise offerings, while also applying computer vision and predictive analytics to manufacturing and packaging operations. Nestlé deploys proprietary AI tools across R&D, demand forecasting, and enterprise functions—reducing product ideation time significantly and running internal large‑language model tools (NesGPT) for sales, marketing, and legal workflows. PepsiCo leverages AI for demand forecasting and supply‑chain optimisation, combining consumer behaviour and external data (for example weather) to better align production schedules and reduce waste. Starbucks applies AI (Deep Brew) for personalised recommendations, demand forecasting, site selection, and operational automation within its mobile app and store operations to enhance customer lifetime value and inventory planning. McDonald’s implements AI for dynamic menu personalization and predictive decisioning in restaurants via partnerships (for example Dynamic Yield) to tailor orders by time, traffic, and local popularity. Kraft Heinz has realised measurable revenue gains by deploying AI platforms (e.g., Lighthouse) focused on operational intelligence, logistics, and promotion optimisation, reporting tens of millions in sales impact from AI initiatives. NotCo is an AI‑native food company using its Giuseppe system to analyse ingredient properties and consumer preferences to design plant‑based products that mimic animal counterparts, exemplifying how generative and data‑driven food R&D can create new product lines and accelerate go‑to‑market timelines. NVIDIA provides the hardware and software stack (GPUs, inference platforms, and edge AI tools) that enables computer vision, deep learning, and real‑time analytics in food manufacturing, inspection systems, robotics, and personalised retail applications across the sector. IBM supplies AI and enterprise analytics tools (including Watson‑class offerings) used for food safety, traceability, predictive maintenance, and quality assurance workflows that are critical for regulatory compliance and risk reduction in food production. Amazon combines AI across grocery retail (demand prediction, cashierless stores), supply‑chain logistics, and cloud/ML services (AWS) that food and beverage companies use to run large models, scale analytics, and deploy AI‑powered customer experiences and automated fulfilment.
These companies collectively span three complementary roles in the AI in Food & Beverage market: global consumer brands that embed AI into products and operations (Coca‑Cola, Nestlé, PepsiCo, Starbucks, McDonald’s, Kraft Heinz, NotCo), technology and platform providers that supply compute, models, and enterprise AI services (NVIDIA, IBM, Amazon), and cross‑industry integrators whose solutions accelerate adoption across manufacturing, retail, and food service. Adoption hotspots include computer vision for quality control and packaging, predictive forecasting to reduce waste and optimise inventory, generative AI for recipe and product ideation, personalization engines for retail and foodservice, and robotic/automation systems for packaging and sorting—areas where the listed companies either deploy AI at scale or provide the enabling technology to do so.
Table of Contents
32 Pages
- 1.0 Scope of Report and Methodology
- 2.0 Market SWOT Analysis and Players
- 2.1 Market Definition
- 2.2 Market Segments
- 2.3 Market Strengths
- 2.4 Market Weaknesses
- 2.5 Market Threats
- 2.6 Market Opportunities
- 2.7 Major Players
- 3.0 Competitive Analysis
- 3.1 Market Player 1
- 3.2 Market Player 2
- 3.3 Market Player 3
- 3.4 Market Player 4
- 3.5 Market Player 5
- 3.6 Market Player 6
- 3.7 Market Player 7
- 3.8 Market Player 8
- 3.9 Market Player 9
- 3.10 Market Player 10
- 4.0 Comparative Business Strategies
- 4.1 Comparative Business Strategies of Player 1 and 2
- 4.2 Comparative Business Strategies of Player 1 and 3
- 4.3 Comparative Business Strategies of Player 1 and 4
- 4.4 Comparative Business Strategies of Player 2 and 3
- 4.5 Comparative Business Strategies of Player 2 and 4
- 4.6 Comparative Business Strategies of Player 3 and 4
- 5.0 Appendix
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