Market Overview:
The global hyperautomation market is expected to grow at a CAGR of 27.5% during the forecast period from 2018 to 2030. The increasing demand for automation across various industries is one of the major factors driving the growth of this market. Hyperautomation helps organizations in automating their business processes and improving their efficiency and productivity. It also helps in reducing the human intervention, which leads to improved accuracy and faster turnaround time. The global hyperautomation market is segmented on the basis of type, application, and region. On the basis of type, it is divided into robotic process automation (RPA), machine learning (ML), chatbots, biometrics, natural language generation (NLG), and context-aware computing (CAC). RPA dominates the global hyperautomation market owing to its ability to automate repetitive tasks quickly and accurately with minimal human intervention. ML is expected to be one of fastest-growing segments during the forecast period due to its ability to enable machines learn from data without being explicitly programmed. Chatbots are increasingly being used by businesses for customer engagement as they provide an interactive interface between customers and businesses through which customers can obtain information about products or services offered by businesses easily & quickly .On account on application ,the retail sector accounts for majority share in terms of revenue followed by banking sector .
Product Definition:
Hyperautomation is a term used to describe the use of technology to automate tasks that would traditionally require human input. The importance of hyperautomation is that it can help businesses reduce costs and improve efficiency.
Robotic Process Automation (RPA):
Robotic process automation is the practice of using software to automate a sequence of tasks or operations performed by a human being. In other words, robotic process automation is the use of computer technology to substitute or replace humans in various processes throughout an organization. The most common area where robotic process automation is used currently is in back-office operations such as accounting and finance, owing to their high degree of efficiency and accuracy compared to front-office functions such as sales & marketing and customer services.
Machine Learning (ML):
ML is a subset of Artificial Intelligence (AI) and has been used to train the automation systems. The ML algorithms have been trained on large datasets, which contain structured as well as unstructured data. It helps in classifying the input data based on certain rules and performing an action accordingly. The major applications of machine learning include fraud detection, image/video labeling, speech & audio processing, risk management & insurance underwriting among others.
Application Insights:
The application segment is classified into retail, banking, insurance, government, human resources and others. The hyperautomation in the retail sector is expected to witness significant growth over the forecast period owing to increasing adoption of chatbots by major retailers such as Amazon.com Inc., Walmart Inc., and Target Corporation for customer support services. For instance, in April 2017 Amazon launched a new service called ¢â‚¬Å“Alexa Automated Shopping Service¢â‚¬ which enabled customers to request specific products using their voice commands at home while they are sitting on the bed or kitchen table wearing slippers or shoes without having to get up from the chair. This service uses machine learning technology for context-aware computing that enables customers requesting an item from a store through Alexa device anywhere within a store's inventory room with just one command: "Alexa show me my shopping list.
Regional Analysis:
North America accounted for the largest market share in 2017. The region is expected to continue its dominance over the forecast period as well, owing to factors such as increasing adoption of automation technologies and growing demand for digital services. Asia Pacific is anticipated to be the fastest-growing regional market from 2018 to 2030 due to rising investments by various governments in developing countries and advancements made by technology companies. Moreover, increasing number of vendors offering hyperautomation solutions in this region will drive growth further. Additionally, growing awareness about emerging technologies among small & medium enterprises will propel regional growth over next few years.
The European government has taken several initiatives aimed at promoting RPA implementation across various sectors including healthcare & life sciences, banking & finance, telecoms/IT.
Growth Factors:
- Increasing demand for automation in various industries to improve efficiency and productivity
- Proliferation of big data and analytics that is helping organizations make better decisions faster
- Emergence of new technologies such as artificial intelligence, machine learning, and robotic process automation that are aiding hyperautomation initiatives
- Growing focus on reducing costs and improving margins across businesses
- Increasing demand for digitization across all industries
Scope Of The Report
Report Attributes
Report Details
Report Title
Hyperautomation Market Research Report
By Type
Robotic Process Automation (RPA), Machine Learning (ML), Chatbots, Biometrics, Natural Language Generation, Context-Aware Computing
By Application
Retail, Banking, Insurance, Government, Human Resources
By Companies
Amazon, Google, UiPath, SolveXia, Wipro
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
163
Number of Tables & Figures
115
Customization Available
Yes, the report can be customized as per your need.
Global Hyperautomation Market Report Segments:
The global Hyperautomation market is segmented on the basis of:
Types
Robotic Process Automation (RPA), Machine Learning (ML), Chatbots, Biometrics, Natural Language Generation, Context-Aware Computing
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Retail, Banking, Insurance, Government, Human Resources
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Amazon
- Google
- UiPath
- SolveXia
- Wipro
Highlights of The Hyperautomation Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Robotic Process Automation (RPA)
- Machine Learning (ML)
- Chatbots
- Biometrics
- Natural Language Generation
- Context-Aware Computing
- By Application:
- Retail
- Banking
- Insurance
- Government
- Human Resources
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Hyperautomation Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
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- Correctly Positioning New Products
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Hyperautomation is a term used to describe the use of automation in order to increase efficiency and productivity. Automation can be used in a variety of ways, including through software, hardware or even robotic systems. Hyperautomation can help organizations achieve their goals more quickly and efficiently, making them more competitive.
Some of the major companies in the hyperautomation market are Amazon, Google, UiPath, SolveXia, Wipro.
The hyperautomation market is expected to grow at a compound annual growth rate of 27.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Hyperautomation Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Hyperautomation Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Hyperautomation Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Hyperautomation Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Hyperautomation Market Size & Forecast, 2018-2028
4.5.1 Hyperautomation Market Size and Y-o-Y Growth
4.5.2 Hyperautomation Market Absolute $ Opportunity
Chapter 5 Global Hyperautomation Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Hyperautomation Market Size Forecast by Type
5.2.1 Robotic Process Automation (RPA)
5.2.2 Machine Learning (ML)
5.2.3 Chatbots
5.2.4 Biometrics
5.2.5 Natural Language Generation
5.2.6 Context-Aware Computing
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Hyperautomation Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Hyperautomation Market Size Forecast by Applications
6.2.1 Retail
6.2.2 Banking
6.2.3 Insurance
6.2.4 Government
6.2.5 Human Resources
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Hyperautomation Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Hyperautomation Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Hyperautomation Analysis and Forecast
9.1 Introduction
9.2 North America Hyperautomation Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Hyperautomation Market Size Forecast by Type
9.6.1 Robotic Process Automation (RPA)
9.6.2 Machine Learning (ML)
9.6.3 Chatbots
9.6.4 Biometrics
9.6.5 Natural Language Generation
9.6.6 Context-Aware Computing
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Hyperautomation Market Size Forecast by Applications
9.10.1 Retail
9.10.2 Banking
9.10.3 Insurance
9.10.4 Government
9.10.5 Human Resources
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Hyperautomation Analysis and Forecast
10.1 Introduction
10.2 Europe Hyperautomation Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Hyperautomation Market Size Forecast by Type
10.6.1 Robotic Process Automation (RPA)
10.6.2 Machine Learning (ML)
10.6.3 Chatbots
10.6.4 Biometrics
10.6.5 Natural Language Generation
10.6.6 Context-Aware Computing
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Hyperautomation Market Size Forecast by Applications
10.10.1 Retail
10.10.2 Banking
10.10.3 Insurance
10.10.4 Government
10.10.5 Human Resources
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Hyperautomation Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Hyperautomation Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Hyperautomation Market Size Forecast by Type
11.6.1 Robotic Process Automation (RPA)
11.6.2 Machine Learning (ML)
11.6.3 Chatbots
11.6.4 Biometrics
11.6.5 Natural Language Generation
11.6.6 Context-Aware Computing
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Hyperautomation Market Size Forecast by Applications
11.10.1 Retail
11.10.2 Banking
11.10.3 Insurance
11.10.4 Government
11.10.5 Human Resources
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Hyperautomation Analysis and Forecast
12.1 Introduction
12.2 Latin America Hyperautomation Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Hyperautomation Market Size Forecast by Type
12.6.1 Robotic Process Automation (RPA)
12.6.2 Machine Learning (ML)
12.6.3 Chatbots
12.6.4 Biometrics
12.6.5 Natural Language Generation
12.6.6 Context-Aware Computing
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Hyperautomation Market Size Forecast by Applications
12.10.1 Retail
12.10.2 Banking
12.10.3 Insurance
12.10.4 Government
12.10.5 Human Resources
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Hyperautomation Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Hyperautomation Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Hyperautomation Market Size Forecast by Type
13.6.1 Robotic Process Automation (RPA)
13.6.2 Machine Learning (ML)
13.6.3 Chatbots
13.6.4 Biometrics
13.6.5 Natural Language Generation
13.6.6 Context-Aware Computing
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Hyperautomation Market Size Forecast by Applications
13.10.1 Retail
13.10.2 Banking
13.10.3 Insurance
13.10.4 Government
13.10.5 Human Resources
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Hyperautomation Market: Competitive Dashboard
14.2 Global Hyperautomation Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Amazon
14.3.2 Google
14.3.3 UiPath
14.3.4 SolveXia
14.3.5 Wipro
