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市場調查報告書

商品編碼

1696216

全球快餐店人工智慧和機器人市場 - 2025 至 2032 年

Global AI and Robotics in Quick-Service Restaurants Market - 2025-2032

出版日期: 2025年03月25日 | 出版商:

DataM Intelligence | 英文 180 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

2024 年全球快餐店人工智慧和機器人市場規模達到 53.9 億美元，預計到 2032 年將達到 129.1 億美元，2025-2032 年預測期內的複合年成長率為 11.54%。

人工智慧 (AI) 和機器人技術正在透過提高營運效率和客戶滿意度日益改變快餐店 (QSR) 行業。麥當勞和塔可鐘等大型連鎖店處於這項技術轉變的前沿。麥當勞正在其全球 43,000 家門市實施人工智慧，以加快服務速度並改善顧客和員工的體驗。這包括支援人工智慧的免下車服務和管理工具，旨在確保訂單準確性和預測設備問題。

麥當勞公司於 2023 年與 Google Cloud 合作，以促進更快的現場資料處理，旨在減輕員工壓力，到 2027 年將忠實客戶群從 1.75 億增加到 2.5 億。人工智慧和機器人技術在 QSR 中的整合不僅簡化了營運，而且還解決了勞動力短缺和工資上漲的問題。

市場動態

促進因素－提高營運效率和降低成本

人工智慧（AI）和機器人技術在快餐店（QSR）中的整合顯著提高了營運效率並降低了成本。機器人可以比人類更快地執行任務，從而減少等待時間並提高客戶滿意度。例如，研究表明，餐廳中的機器人協助可以減少服務時間，使人類員工專注於更複雜的任務，從而提高整體效率。

此外，機器人可以透過程式設計來收集和分析即時資料，在幾分鐘內完成人類需要更長時間才能完成的任務。此功能增強了庫存管理，確保了供應的持續供應並減少浪費。

約束－員工的工作保障問題

儘管在營運方面有優勢，但在 QSR 中採用人工智慧和機器人卻引發了對員工工作保障的擔憂。服務員工對採用和使用服務機器人的意識顯著影響他們對機器人導致失業的認知。

這種看法可能會導致對技術採用的抵制，進而影響員工的士氣和生產力。此外，由於機器人的實施而導致的服務體驗非人性化可能會影響客戶滿意度，這對 QSR 中人工智慧和機器人的廣泛應用構成額外的挑戰。

Artificial intelligence (AI) and robotics are increasingly transforming the quick-service restaurant (QSR) industry by enhancing operational efficiency and customer satisfaction. Major chains like McDonald's and Taco Bell are at the forefront of this technological shift. McDonald's is implementing AI across its 43,000 global locations to expedite service and improve experiences for both customers and employees. This includes AI-enabled drive-throughs and management tools designed to ensure order accuracy and predict equipment issues.

McD company partnered with Google Cloud in 2023 to facilitate faster, on-site data processing, aiming to reduce employee stress and increase its loyal customer base from 175 million to 250 million by 2027. The integration of AI and robotics in QSRs not only streamlines operations but also addresses labor shortages and rising wage issues.

Market Dynamics

Driver - Enhanced Operational Efficiency and Cost Reduction

The integration of artificial intelligence (AI) and robotics in quick-service restaurants (QSRs) significantly enhances operational efficiency and reduces costs. Robots can perform tasks faster than humans, leading to reduced waiting times and improved customer satisfaction. For instance, studies have shown that robotic assistance in restaurants can decrease service time, allowing human staff to focus on more complex tasks, thereby improving overall efficiency.

Additionally, robots can be programmed to collect and analyze real-time data, performing tasks in minutes that would take humans much longer to complete. This capability enhances inventory management, ensuring consistently stocked supplies and reducing waste.

Restraint - Employee Job Security Concerns

Despite the operational benefits, the adoption of AI and robotics in QSRs raises concerns about employee job security. Service employees' awareness of adopting and using service robots significantly impacts their perception of robot-induced unemployment.

This perception can lead to resistance to technological adoption, affecting employee morale and productivity. Furthermore, the potential dehumanization of service experiences due to robot implementation may impact customer satisfaction, posing additional challenges to the widespread adoption of AI and robotics in QSRs.

Segment Analysis

The global AI and robotics in quick-service restaurants market is segmented based on function, deployment type, technology and region.

Food Preparation & Cooking in the global market is expected to drive the market.

The Food Preparation & Cooking segment is expected to be a major driver of AI and robotics adoption in quick-service restaurants (QSRs) worldwide. Automated cooking systems and robotic food preparation technologies are being increasingly deployed to enhance efficiency, improve food consistency, and reduce operational costs. Studies indicate that AI-powered robotic chefs can reduce food preparation time by up to 50%, leading to faster service and improved customer experience.

Additionally, automation helps maintain food safety standards by minimizing human contact, which has become a priority post-pandemic. The U.S. Department of Agriculture (USDA) has emphasized the role of automation in food processing and handling, highlighting its potential to reduce waste and optimize ingredient usage. Governments worldwide are also investing in AI-driven food production innovations to enhance food security and address labor shortages in the restaurant industry. Japan, for example, has implemented AI-driven robotic kitchen solutions to counter labor shortages in the foodservice sector

Geographical Penetration

Rapid Technological Advancements in North America.

The demand for AI and robotics in the quick-service restaurants (QSR) market in North America is rapidly growing due to labor shortages, rising operational costs, and increasing consumer expectations for faster service. The U.S. Bureau of Labor Statistics (BLS) projects a continued decline in foodservice labor availability, with over 1 million job vacancies in hospitality and food services as of early 2024.

AI-driven automation helps fill this gap by improving efficiency, reducing reliance on human labor, and optimizing restaurant operations. The National Institute of Standards and Technology (NIST) highlights AI's role in predictive maintenance for kitchen equipment, reducing downtime and enhancing productivity in QSRs. Robotics is also being integrated into food preparation, order processing, and customer service to meet growing demand for speed and consistency.

Sustainability Analysis

Implementing AI and robotics in QSRs contributes to sustainability by optimizing resource use, reducing waste, and enhancing energy efficiency. For instance, McDonald's has embarked on a global initiative to upgrade its 43,000 restaurants with AI-driven technologies aimed at improving operational efficiency and customer experience. These upgrades include internet-connected kitchen equipment and AI-enabled drive-through systems designed to streamline operations and minimize resource wastage.

Furthermore, AI's role in enhancing food safety cannot be overlooked. The U.S. Food and Drug Administration (FDA) has recognized the potential of AI in revolutionizing food safety protocols. AI applications can quickly analyze data to detect potential foodborne pathogens, ensuring safer food handling practices and reducing the risk of contamination.

Technology Analysis

The technological landscape of QSRs is rapidly evolving with the adoption of AI and robotics. McDonald's partnership with Google Cloud in 2023 exemplifies this shift, enabling edge computing capabilities across its restaurants. This technology allows for faster and more efficient data processing on-site, which is crucial for real-time applications like AI-powered drive-throughs and kitchen operations.

Robotics is making significant inroads into QSR kitchens. Companies like Miso Robotics have developed AI-driven robotic platforms, such as "Flippy," which can perform frying tasks in commercial kitchens. These robots are designed with extensive AI skill sets and machine learning capabilities, aiming to improve consistency and efficiency in food preparation.

The U.S. Bureau of Labor Statistics (BLS) projects that total employment will grow by 4.0 percent, adding 6.7 million jobs from 2023 to 2033. However, the retail trade sector, which includes QSRs, is the only sector projected to lose jobs over this period. This projection underscores the potential impact of automation and AI on employment within the industry, highlighting the need for workforce adaptation and upskilling.

Competitive Landscape

The major global players in the market include McDonald's Corporation, Yum! Brands (Taco Bell, KFC, Pizza Hut), Domino's Pizza, Inc., Starbucks Corporation, Wendy's Company, Burger King (Restaurant Brands International), Chipotle Mexican Grill, Inc., Panera Bread, White Castle, and CaliBurger.

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Target Audience 2024

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Function
3.2. Snippet by Deployment Type
3.3. Snippet by Technology
3.4. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Enhanced Operational Efficiency and Cost Reduction
- 4.1.2. Restraints
  - 4.1.2.1. Employee Job Security Concerns
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Value Chain Analysis
5.4. Pricing Analysis
5.5. Regulatory and Compliance Analysis
5.6. AI & Automation Impact Analysis
5.7. R&D and Innovation Analysis
5.8. Sustainability & Green Technology Analysis
5.9. Next Generation Technology Analysis
5.10. Technology Roadmap
5.11. DMI Opinion

6. By Function

6.1. Introduction
- 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 6.1.2. Market Attractiveness Index, By Function
6.2. Order Management & Processing*
- 6.2.1. Introduction
- 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
6.3. Food Preparation & Cooking
6.4. Inventory & Supply Chain Management
6.5. Customer Engagement & Personalization Service
6.6. Others

7. By Deployment Type

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 7.1.2. Market Attractiveness Index, By Deployment Type
7.2. On-premises*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Cloud-based

8. By Technology

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 8.1.2. Market Attractiveness Index, By Technology
8.2. AI-Based Solutions*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Robotic Solutions

9. By Region

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 9.1.2. Market Attractiveness Index, By Region
9.2. North America
- 9.2.1. Introduction
- 9.2.2. Key Region-Specific Dynamics
- 9.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 9.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 9.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.2.6.1. U.S.
  - 9.2.6.2. Canada
  - 9.2.6.3. Mexico
9.3. Europe
- 9.3.1. Introduction
- 9.3.2. Key Region-Specific Dynamics
- 9.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 9.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 9.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.3.6.1. Germany
  - 9.3.6.2. UK
  - 9.3.6.3. France
  - 9.3.6.4. Italy
  - 9.3.6.5. Russia
  - 9.3.6.6. Rest of Europe
9.4. South America
- 9.4.1. Introduction
- 9.4.2. Key Region-Specific Dynamics
- 9.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 9.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 9.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.4.6.1. Brazil
  - 9.4.6.2. Argentina
  - 9.4.6.3. Rest of South America
9.5. Asia-Pacific
- 9.5.1. Introduction
- 9.5.2. Key Region-Specific Dynamics
- 9.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 9.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 9.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 9.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 9.5.6.1. China
  - 9.5.6.2. India
  - 9.5.6.3. Japan
  - 9.5.6.4. Australia
  - 9.5.6.5. Rest of Asia-Pacific
9.6. Middle East and Africa
- 9.6.1. Introduction
- 9.6.2. Key Region-Specific Dynamics
- 9.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Function
- 9.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 9.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology

10. Competitive Landscape

10.1. Competitive Scenario
10.2. Market Positioning/Share Analysis
10.3. Mergers and Acquisitions Analysis

11. Company Profiles

11.1. McDonald's Corporation*
- 11.1.1. Company Overview
- 11.1.2. Product Portfolio and Description
- 11.1.3. Financial Overview
- 11.1.4. Key Developments
11.2. Yum! Brands (Taco Bell, KFC, Pizza Hut)
11.3. Domino's Pizza, Inc.
11.4. Starbucks Corporation
11.5. Wendy's Company
11.6. Burger King (Restaurant Brands International)
11.7. Chipotle Mexican Grill, Inc.
11.8. Panera Bread
11.9. White Castle
11.10. CaliBurger

LIST NOT EXHAUSTIVE