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Global Autonomous Delivery Robots Market to reach USD XXX billion by the end of 2029

Global Autonomous Delivery Robots Market Size study & Forecast, by End User (Healthcare, Hospitality, Retail & Logistics), Regional Analysis, 2022-2029

Product Code: ALTL-51960196
Publish Date: 5-01-2023
Page: 200

Global Autonomous Delivery Robots Market is valued approximately USD XXX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Robots that are used primarily for delivery and service applications are autonomous delivery robots. Autonomous delivery robots (ADR) have revolutionized delivery systems, providing a cheaper and more efficient way of delivery. Though delivery robots did not experience high adoption in the past, they are expected to witness high growth in the future, owing to multiple advantages. The increasing adoption of ADR is mainly driven by the growing affordability and return on investment of a rising variety of infrastructure-light robots, along with persisting needs for flexible and efficient automated fulfillment. The Autonomous Delivery Robots market is expanding because of factors such as rising demand from healthcare industry, rising healthcare expenditure and rising demand from logistics sector

The Bureau of Labor Statistics projects that the number of nurses needed in the United States will rise from 2.7 million in 2014 to 3.2 million in 2024, a 16% increase. The majority of the expansion will be driven by the ageing baby boomers who require more care. Additionally, investment in the healthcare industry is rising daily, a sign that autonomous delivery robots are becoming more common. For instance, according to the India Brand Equity Foundation, the predicted cost of healthcare in India in 2020 was USD 194 billion and is anticipated to rise, reaching USD 372 billion in 2022. Thus, rising demand from healthcare is catering the growth of market. Furthermore, need to manage last-mile deliveries and growing automation in the logistics industry. However, the high cost of Autonomous Delivery Robots stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Autonomous Delivery Robots Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. Among these region, North America hold the highest share owing to factors such as rising number of startups, rising technological advancement, rising demand for automation in the industry is catering the growth of market in the projected region. Also, Asia Pacific is expected to have the fastest growth owing to factors such as rising healthcare infrastructure spending, rising healthcare automation in the region.

Major market player included in this report are:
Starship Technologies
Relay Robotics, Inc.
Ottonomy.IO
Nuro Inc.
Serve Robotics Inc
Eliport
TeleRetail (Aitonomi AG)
Aethon Inc.
Kiwibot
Postmates Inc.

Recent Developments in the Market:
 In August 2022, Ottonomy Inc. announced the seed funding of USD 3.3 and launched Ottobot 2.0 latest version of autonomous delivery robot. The company states it plans to scale up the deployments of Ottobot in retail store, airports, and restaurants.
 In Aug 2021, Google announced its investment in Nuro, it is focused on delivering and goods using robotic autonomous vehicles. Overall, the company raised USD 600 million in the fundraising round led by Tiger Global Management.
Global Autonomous Delivery Robots Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered End User Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and End User offerings of key players. The detailed segments and sub-segment of the market are explained below:

By End User:
Healthcare
Hospitality
Retail & Logistics

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Autonomous Delivery Robots Market, by Region, 2019-2029 (USD Billion)
1.2.2. Autonomous Delivery Robots Market, by End User, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Autonomous Delivery Robots Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Autonomous Delivery Robots Market Dynamics
3.1. Autonomous Delivery Robots Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing incidence of diabetes
3.1.1.2. Growing Geriatric Population
3.1.2. Market Challenges
3.1.2.1. High cost of Autonomous Delivery Robots
3.1.3. Market Opportunities
3.1.3.1. Advancements in Formulation
Chapter 4. Global Autonomous Delivery Robots Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Autonomous Delivery Robots Market, by End User
6.1. Market Snapshot
6.2. Global Autonomous Delivery Robots Market by End User, Performance – Potential Analysis
6.3. Global Autonomous Delivery Robots Market Estimates & Forecasts by End User 2019-2029 (USD Billion)
6.4. Autonomous Delivery Robots Market, Sub Segment Analysis
6.4.1. Healthcare
6.4.2. Hospitality
6.4.3. Retail & Logistics
Chapter 7. Global Autonomous Delivery Robots Market, Regional Analysis
7.1. Autonomous Delivery Robots Market, Regional Market Snapshot
7.2. North America Autonomous Delivery Robots Market
7.2.1. U.S. Autonomous Delivery Robots Market
7.2.1.1. End User breakdown estimates & forecasts, 2019-2029
7.2.2. Canada Autonomous Delivery Robots Market
7.3. Europe Autonomous Delivery Robots Market Snapshot
7.3.1. U.K. Autonomous Delivery Robots Market
7.3.2. Germany Autonomous Delivery Robots Market
7.3.3. France Autonomous Delivery Robots Market
7.3.4. Spain Autonomous Delivery Robots Market
7.3.5. Italy Autonomous Delivery Robots Market
7.3.6. Rest of Europe Autonomous Delivery Robots Market
7.4. Asia-Pacific Autonomous Delivery Robots Market Snapshot
7.4.1. China Autonomous Delivery Robots Market
7.4.2. India Autonomous Delivery Robots Market
7.4.3. Japan Autonomous Delivery Robots Market
7.4.4. Australia Autonomous Delivery Robots Market
7.4.5. South Korea Autonomous Delivery Robots Market
7.4.6. Rest of Asia Pacific Autonomous Delivery Robots Market
7.5. Latin America Autonomous Delivery Robots Market Snapshot
7.5.1. Brazil Autonomous Delivery Robots Market
7.5.2. Mexico Autonomous Delivery Robots Market
7.6. Rest of The World Autonomous Delivery Robots Market

Chapter 8. Competitive Intelligence
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. Starship Technologies
8.2.1.1. Key Information
8.2.1.2. Overview
8.2.1.3. Financial (Subject to Data Availability)
8.2.1.4. Product Summary
8.2.1.5. Recent Developments
8.2.2. Relay Robotics, Inc.
8.2.3. Ottonomy.IO
8.2.4. Nuro Inc.
8.2.5. Serve Robotics Inc
8.2.6. Eliport
8.2.7. TeleRetail (Aitonomi AG)
8.2.8. Aethon Inc.
8.2.9. Kiwibot
8.2.10. Postmates Inc.
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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