The global AI in food and beverages market is projected to grow from $1.1 billion to $4.9 billion in just six years, nearly a fivefold increase. The U.S. quick-service restaurant market is forecast to reach $399.3 billion by 2028. This article presents the key statistics driving this massive technological investment.
Key Takeaways
- 13.3% of global foodservice industry revenue is forecasted to grow from 2023 to 2028 (CAGR context for QSR technology investment planning)
- The global fast-food market size was $790.7 billion in 2023
- The global fast-food market is projected to reach $1,038.3 billion by 2030
- Drive-through is a major QSR channel; about 3 in 5 quick-service customers use drive-through at least once per month (channel usage indicator for AI drive-thru optimization)
- Self-service kiosks were projected to grow; kiosks are expected to reach 2.3 million units in the U.S. by 2025 (supporting AI/vision ordering adoption)
- Self-service kiosks market in the U.S. is forecast to reach $10.2 billion by 2025 (AI kiosks and computer-vision upsell relevance)
- Inventory carrying cost is commonly 20% to 30% of inventory value per year (QSR AI demand planning target for cost reduction)
- McKinsey estimated that AI can reduce marketing costs by 10% to 30% (relevant to QSR targeted promotions and personalization spend)
- Gartner estimated that poor data quality costs the U.S. and Europe about $15 million every year (data quality importance for QSR AI systems)
- KFC reported a reduction in labor time for food preparation by using AI-assisted demand and operations planning (case evidence; time savings cited in newsroom)
- In a QSR customer experience study, 58% of consumers said digital ordering improves speed (indicator for AI-enabled personalization and order management)
- A study by Toast found that restaurants using online ordering can increase revenue by 10% to 30% (QSR relevance for AI-assisted ordering)
- Starbucks reported 2023 mobile order and pay accounted for 35% of transactions (QSR-style order automation adoption indicator for AI ranking/optimization)
- Starbucks reported that 2023 delivery mix increased; mobile order and pay plus delivery combined with loyalty program engagement (adoption context)
- A 2021 survey found that 41% of restaurants were using some form of AI or automation in operations (baseline adoption context for QSR)
Fast food and QSR technology are rapidly growing, driving fast adoption of AI to boost revenue and cut costs.
Related reading
01 · Category
Market Size21 stats
01
13.3% of global foodservice industry revenue is forecasted to grow from 2023 to 2028 (CAGR context for QSR technology investment planning)
02
The global fast-food market size was $790.7 billion in 2023
03
The global fast-food market is projected to reach $1,038.3 billion by 2030
04
The global fast-food market forecast CAGR is 3.8% from 2024 to 2030
05
The U.S. quick-service restaurant industry is forecast to reach $399.3 billion by 2028
06
The global restaurant software market size was $8.8 billion in 2023
07
The global restaurant software market is projected to reach $14.2 billion by 2028
08
The restaurant management system market (software category often used in QSR) is forecast to grow at a CAGR of 10.1% from 2023 to 2028
09
Global AI in food and beverages market size was $1.1 billion in 2020
10
Global AI in food and beverages market is projected to reach $4.9 billion by 2026
11
AI in food and beverages market is forecast to grow at a CAGR of 27.3% from 2021 to 2026
12
McKinsey estimated that generative AI could add $2.6 trillion to $4.4 trillion annually across industries (QSR technology budgeting context)
13
McKinsey estimated that generative AI could add $200to $340 billion annually to retail and consumer goods (adjacent category including QSR ordering and personalization)
14
McKinsey estimated that generative AI could add $1.5to $2.5 trillion annually in customer operations (relevant to QSR support and ordering inquiries)
15
DoorDash’s 2023 Marketplace report showed that 1 million+ merchants used the platform (context for AI forecasting in delivery-driven QSR ecosystems)
16
AI software market (global) size was $136.6 billion in 2022 (investment scale relevant to QSR AI tools)
17
AI software market is projected to reach $554.3 billion by 2030
18
The global AI in food and beverages market forecast CAGR is 27.3% (foodservice adjacency for QSR)
19
McKinsey estimates AI may deliver $450 billion to $550 billion in value in retail and consumer sectors (QSR adjacent)
20
Statista reports that the global smart kitchen appliances market reached $7.6 billion in 2023 (context for AI-enabled equipment adoption in foodservice)
21
Statista estimates the global smart kitchen appliances market will reach $12.3 billion by 2030 (tailwind for QSR equipment AI)
Interpretation
Market Size Interpretation
With the global AI in food and beverages market projected to surge from $1.1 billion in 2020 to $4.9 billion by 2026 at a 27.3% CAGR, QSRs are clearly moving toward major AI investment alongside fast-food growth reaching $1,038.3 billion by 2030.
02 · Category
Industry Trends19 stats
01
Drive-through is a major QSR channel; about 3 in 5 quick-service customers use drive-through at least once per month (channel usage indicator for AI drive-thru optimization)
02
Self-service kiosks were projected to grow; kiosks are expected to reach 2.3 million units in the U.S. by 2025 (supporting AI/vision ordering adoption)
03
Self-service kiosks market in the U.S. is forecast to reach $10.2 billion by 2025 (AI kiosks and computer-vision upsell relevance)
04
The self-service kiosk market is forecast to grow at a CAGR of 9.8% from 2020 to 2027 (kiosk-adjacent AI adoption tailwind)
05
Chatbots are expected to help companies save $11 billion annually by 2023 (context for customer-service automation in QSR)
06
NLP chatbots are used to improve customer engagement; 1 in 5 consumers are already using chatbots for customer service (adoption context for QSR digital assistants)
07
Digital customer interactions are projected to account for 70% of all interactions by 2025 (driving conversational AI and self-service in QSR)
08
Gartner predicted that 70% of customer interactions will be managed by AI by 2023 (applied to QSR support and order inquiries)
09
Gartner predicted that by 2025, chatbots will be able to solve at least 75% of customer service requests without human intervention
10
Gartner predicted that by 2024, organizations will use AI for planning and scheduling to improve decision-making, reducing labor cost pressures (strategic indicator)
11
Salesforce’s State of Service report found 74% of service leaders believe AI will improve customer experience (context for QSR service AI)
12
A 2023 Gartner estimate: AI will augment more than 80% of marketing activities by 2025 (relevance to QSR promotions and loyalty)
13
In a survey, 76% of consumers say they would be more likely to order if offered personalized recommendations (AI menu/promo relevance)
14
U.S. restaurants and foodservice establishments (including QSR) employed about 12.2 million people in 2023 (workforce context for labor-scheduling AI)
15
A 2022 survey found that 45% of restaurants identified labor shortages as a top operational challenge (adoption driver for AI scheduling)
16
Forrester: 52% of firms expect AI to have a high business impact within 2 years (adoption driver)
17
Gartner: 54% of organizations plan to increase AI investment in 2024 (budget driver for QSR operators)
18
The smart kitchen appliances market forecast CAGR is 7.5% (QSR equipment digitization trend)
19
BLS reports that in 2024, the projected growth for food service managers is 5% (staff planning context for AI-driven operations)
Interpretation
Industry Trends Interpretation
With digital interactions projected to reach 70% of all QSR customer touchpoints by 2025 and Gartner expecting 70% of customer interactions to be managed by AI by 2023, the sector is rapidly shifting toward automation led by drive thru, self service kiosks growing to 2.3 million units by 2025, and chatbots delivering large-scale service improvements.
03 · Category
Cost Analysis9 stats
01
Inventory carrying cost is commonly 20% to 30% of inventory value per year (QSR AI demand planning target for cost reduction)
02
McKinsey estimated that AI can reduce marketing costs by 10% to 30% (relevant to QSR targeted promotions and personalization spend)
03
Gartner estimated that poor data quality costs the U.S. and Europe about $15 million every year (data quality importance for QSR AI systems)
04
BLS: average hourly earnings for food services in May 2024 were $16.10(labor cost context for staffing optimization with AI)
05
BLS: job openings in food preparation and serving related occupations were 1.3 million in 2023 (staffing pressures for AI scheduling)
06
A peer-reviewed study reported that reinforcement learning reduced inventory costs by 15% compared to baseline policies (AI inventory control analog for QSR)
07
A study on dynamic staffing in quick service restaurants reduced labor cost by 12% through predictive scheduling (AI scheduling objective)
08
A peer-reviewed study found that predictive maintenance can reduce unplanned downtime by 30% (applies to QSR kitchen equipment uptime)
09
BLS reports that restaurant cooks employment is projected to decline by 3% from 2022 to 2032 (labor automation and productivity drivers for AI)
Interpretation
Cost Analysis Interpretation
Across QSR operations, AI is poised to deliver measurable savings of 10% to 30% in marketing costs, cut inventory costs by about 15%, and reduce unplanned downtime by 30%, all while addressing major labor pressures reflected in 1.3 million job openings and rising need for predictive scheduling.
More related reading
04 · Category
Performance Metrics10 stats
01
KFC reported a reduction in labor time for food preparation by using AI-assisted demand and operations planning (case evidence; time savings cited in newsroom)
02
In a QSR customer experience study, 58% of consumers said digital ordering improves speed (indicator for AI-enabled personalization and order management)
03
A study by Toast found that restaurants using online ordering can increase revenue by 10% to 30% (QSR relevance for AI-assisted ordering)
04
OpenAI reported that GPT-4 reached an 86.4% on the MMLU benchmark (capability indicator for generative AI assistants used in customer service)
05
In a QSR operations study, accurate demand forecasting can reduce stockouts by 10% (AI-driven forecasting objective)
06
A meta-analysis of machine learning in supply chain found error reduction of up to 20% on forecasting models (benchmark for QSR planning improvements)
07
A peer-reviewed paper on recommender systems reported that item-based collaborative filtering improved accuracy by 8% over baseline (relevant to AI menu/promo recommendations)
08
A computer-vision accuracy study reported 95% classification accuracy for detecting food items from images (objective for AI food recognition in QSR quality control)
09
A study on drive-thru queuing models reduced average wait time by 20% using optimization (AI scheduling/queue optimization objective)
10
A peer-reviewed study found that reducing order errors by 25% can increase customer satisfaction scores by 10 points (AI order verification objective)
Interpretation
Performance Metrics Interpretation
Across these QSR findings, AI is consistently tied to measurable gains, from cutting labor prep time and wait times by about 20% to boosting revenue by 10% to 30%, reducing stockouts by 10%, improving forecasting and recommendations by single digit to 20% margins, and even lifting satisfaction by 10 points when order errors drop 25%.
05 · Category
User Adoption5 stats
01
Starbucks reported 2023 mobile order and pay accounted for 35% of transactions (QSR-style order automation adoption indicator for AI ranking/optimization)
02
Starbucks reported that 2023 delivery mix increased; mobile order and pay plus delivery combined with loyalty program engagement (adoption context)
03
A 2021 survey found that 41% of restaurants were using some form of AI or automation in operations (baseline adoption context for QSR)
04
A 2022 survey found that 57% of restaurant operators planned to increase tech spending (enabling AI pilots)
05
In a global survey, 38% of organizations have adopted AI in at least one business function (benchmark for QSR adoption)
Interpretation
User Adoption Interpretation
The most telling trend is that QSR technology adoption is accelerating, with Starbucks citing 35% of 2023 transactions coming from mobile order and pay and broader surveys showing AI use rising from 41% in 2021 to 38% of organizations already using AI in at least one function and 57% of operators planning higher tech spending in 2022.
Reference
Cite This Report
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APA
Diana Reeves. (2026, February 13). AI In The Qsr Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-qsr-industry-statistics
MLA
Diana Reeves. "AI In The Qsr Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-qsr-industry-statistics.
Chicago
Diana Reeves. 2026. "AI In The Qsr Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-qsr-industry-statistics.
Sources & references
49 datasets cited across this report · attribution is report-level
+25 additional datasets cited (not shown individually)