Hyper Automation Market Overview

Global Hyperautomation Market was valued at USD 5.82 Billion in 2021 and is expected to reach USD 18.91 Billion by the year 2028, at a CAGR of 21.75%.

Hyperautomation is a business-centric, disciplined approach that organizations use to quickly identify, inspect, and automate as many business and IT processes as possible. Hyperautomation involves the systematic use of multiple technologies. Hyperautomation allows companies to quickly identify and automate as many processes as possible using technologies such as robotic process automation (RPA), low-code application platforms (LCAP), artificial intelligence (AI), and virtual assistants. Tools such as RPA, LCAP, and AI are considered process-independent software which is easier to be deployed across multiple IT and business uses in any organization. Process-agnostic software is most in demand as a major enabler of the ultra-automated trend. The fastest-growing category of hyper-automated software includes tools for mapping business activities, automating and managing content ingestion, coordinating work across multiple systems, and visualizing the deployment of complex rule engines. The market is expected to grow at double-digit rates until 2022. Other software designed to automate more specific tasks, such as ERP, supply chains, and CRM systems also expected to grow at a substantial rate.

Market Dynamics and Factors For Hyperautomation Market

Drivers

Hyperautomation promises end-to-end automation of office tasks using a variety of technologies such as robotic process automation (RPA), artificial intelligence (AI), and machine learning. However, workplace Hyperautomation is hampered by constantly changing processes, tools, and goals, which need high levels of flexibility and adaptation from office personnel. Although business process management (BPM) technologies allow for the automation of the most frequent standard procedures, less visible and less standard, but extremely repetitive, monotonous operations are still done by hand. To automate such processes, a new strategy is required such as one that is less centralized and standardized while yet being more adaptable, intelligent, and powerful. RPA with AI is turning towards intelligent automation, resulting in a Digital Workforce – trainable, intelligent digital assistants for specific functional jobs rather than procedures.

New-age technologies are also swiftly understanding the disruptive roles they can play in supporting company development and process efficiency, and how they have become a critical accelerator of this transformation story. In the energy and utility industries, service continuity and operational efficiency are crucial. Because of digitalization and automation to meet changing market dynamics and expectations, industry throughout the world is experiencing a huge shift in consumer behavior and the way businesses function. Technology is driving the way energy is sourced, provided, and utilized today. In addition, factors including increased renewable energy adoption, battery storage, distributed grid-edge generation (prosumers), the advent of electric automobiles, decarbonization, and decentralization is producing unprecedented upheaval in the energy and utility sectors. As organizations transform their business processes, the adoption of new era technologies such as ultra-automation, AI, advanced analytics, cloud, and IIoT is expected to accelerate and accelerate. Shortly, chatbots and language support, RPA, and super-automation will emerge as important technological growth drivers.

Restraints

As RPA gains momentum in the industry to be viewed as a new emerging technology and utilized as a new phase of the sophisticated business evolution to automate the business process.  As a result, some points in the process are often overlooked during the evaluation phase. This later led to the challenge of overall automation. Such factors are difficult to determine because the reducing total dependency of manual processes in RPA can result in many errors in the same process. This was primarily due to high ROI expectations associated with the dismissal of workers, which is incorrect. Most of the automated processes failed because they couldn't be automated, but they were still very manual. Instead, ROI should ideally come from making business processes more reliable, quicker, and better. The proportionate integration of RPA and manual force in the business process with realistic ROI is essential for the success of Hyperautomation in the business.

Opportunities

AI and Hyperautomation in legal technology have increased the productivity of legal support personnel, notably in in-house and contract law companies. Legal Automation refers to the creation, implementation, and management of legal procedures, workflows, practices, and data mining that are based on pre-determined norms. Automation is a subset of software engineering that focuses on modeling, developing, analyzing, controlling, and implementing legal software systems.

One of the largest industries focused on automation trends in the financial industry. Companies in the financial sector are continually looking for new ways to automate their business models and streamline processes that traditionally required a large number of people to perform. FinTech automation trends are leveraging technological advances to create new opportunities for cost savings, efficiency, and productivity gains. To effectively handle complex and demanding financial transactions, the software must work very efficiently. The software used to automate the process of bank automation requires advances in both hardware and software technologies. One such software program is known as an intuitive approach that greatly simplifies the process of automating financial transactions for financial institutions using artificial intelligence technology to use automation in a financial transaction carried out effortlessly for financial institutions.

Challenges

The lack or difficulty of applying automation at scale is the primary barrier preventing major organizations from benefiting from their RPA initiatives. The way automation initiatives are governed has been identified as a root factor. Separate business processes are being automated by several independent teams and departments. Organizations face a hurdle in successfully tracking their automation program due to this scattered setup. This issue is caused by several factors, including the lack of a standardized technological stack (i.e., different RPA tools for different functions or initiatives, friction between functions, and their corresponding application environment). Organizations are unable to pinpoint improvement opportunities due to a lack of appropriate governance to review and analyze automation programs. As a result, business user satisfaction is poor making it a prominent challenge in the market.

Market Segmentation

Segmentation Analysis of Hyperautomation Market:

By Technology, Robotic Process Automation is expected to be dominating the Hyperautomation Market. Robotic Process Automation (RPA) is a technology that operates on top of a computer and works with nearly any sort of system. It helps firms automate repetitive procedures and make them human workforce more productive. It can save 25-50 percent of extra and operating costs. Robots can improve the efficiency and cost-effectiveness of the most repetitive tasks. RPA focuses on areas where there is a high risk of human mistakes, making it dependable and efficient while also helping to improve overall quality. The quality and analysis of data will increase as a result of its error-free and accurate data from multiple sources, resulting in improved corporate decision-making. Therefore, RPA presents remarkable growth prospects during the forecasted period. The AI is also one of the branches of Hyperautomation that is growing at a fast pace in business integration. Artificial intelligence is a foundational catalyst for advanced process automation and human augmentation and engagement. Automation is highly dependent on the organization’s existing IT architecture and business practices to be successful. Whether leveraging robotic process automation to connect legacy and modern systems or Hyperautomation to connect a combination of multiple machine learning, packaged software, and automation tools to deliver work.

By Application, Large enterprise segment is dominating the Hyperautomation Market. Large enterprises are the general use of such newly emerging technologies due to massive operations and enormous data which need to be organized in the optimum way to improve the efficiency of the company. Large manufacturing firms, banking, and financing institution, and companies as well as giant e-commerce platforms require to automate large inventory management, documentation, invoices of internal and external sources, as well as repetitive data filing and reporting reduces the efficiency of the company. Integration of business process management and robotic process automation, increased the productivity by 30-35% in overall operation which can project the greatest return on investment in such software. Therefore, large enterprises show a great opportunity for the growth of Hyperautomation during the forecasted period.

By End-Use Industry, Manufacturing sector is expected to dominate the Hyperautomation market. The manufacturing process that requires extensive documentation and communication across multiple platforms can become bottlenecks if not properly managed. Whether it's the supply chain or the back-office process, there are errors and delays in every step. Automating these processes not only streamlines the process, but also helps reduce errors and increase efficiency. With RPA manufacturing integration, work can be carried out 24/7 without interruption, perform rule-based tasks accurately, and be scalable, flexible, and reliable.  RPA also helps handle a large number of repetitive tasks and complete them with high accuracy. Errors can be detected and corrected immediately. For example, using a Blue Prism digital worker, the digital worker recorded every morning every product that was incorrectly labeled in inventory. Human workers have been released to do further research to improve the process.

Regional Analysis of Hyperautomation Market:

North America is dominating the Hyperautomation Market. The United States is providing a potent technological ecosystem for companies that develops and integrates the Hyperautomation means and increases the productivity opportunity via newly developed software for various business verticals. The United States happens to be one of the largest Hyperautomation markets in the world. Growth in the United States is partly due to the presence of established players such as Automation Anywhere Inc., UiPath, and Appian Corp. Local Catalyst Inc. In addition, the United States is one of the fastest-changing and most competitive markets in the world. The region is also expected to adopt new technologies faster than any other country in the world.

The European region is one of the fastest-growing in the Hyperautomation market. Increasing demand for high efficiency and reduced operating costs, coupled with increased penetration of digitalization, is one of the main drivers behind market growth in Europe. Companies in the region are adopting super-automation to build a more resilient supply chain. In addition, the growing demand for automation in various sectors of countries such as Germany, Italy, France, and the United Kingdom in Europe allowed the hyper-automation market to grow significantly during the forecast period.

The Asia Pacific shows massive opportunity for the growth of Hyperautomation in the manufacturing sector. As a growing manufacturing industry due to robust supply chain creating growth in China India, Cambodia and Vietnam. These countries have the largest textile manufacturing industry, which contributes majorly to the global textile export. Also, China is the largest chemical manufacturing hub in the world. Therefore, from large-scale to SMEs, integration of automation can increase the output in the region. India and China are early adopters of the technology and are expected to be key contributors to the growth of Hyperautomation in the region.

Players Covered in Hyper Automation market are :

  • UiPath
  • SolveXia
  • Mitsubishi Electric Corporation
  • Allerin Tech Pvt. Ltd.
  • Wipro Limited
  • Catalytic Inc.
  • Appian
  • Tata Consultancy Services Ltd.
  • OneGlobe LLC
  • Automation Anywhere Inc
  • JK Tech
  • Vuram Technologies
  • IBM
  • Oracle and others major players.

Covid19 Impact on Hyperautomation Market:

The COVID19 pandemic has catalyzed the development of automation technology by global and Indian companies, especially in the Indian IT industry, which is the field of drones for surveillance and drug delivery purposes. The unprecedented economic impact of COVID19 on supply and demand, as well as its impact on geopolitics and globalization, will shape the future of automation. The coronavirus pandemic has the potential to drive improved automated digitization and artificial intelligence (AI) in the automotive sector in the post-COVID era, improving resilience to future pandemics. In these situations, automation and robotics may reduce reliance on human labor, increase productivity, and reduce the likelihood of future plant outages. In addition, IoT, AI, and digitalization will be very important in the future and will determine new ways of working. This opens up the possibility of a super-automated market in the coming years.

Recent Key Developments of Hyperautomation Market:

  • October 2021, Vuram, the Hyperautomation services company that focuses on low-code enterprise automation declared the launch of the upgraded Contract Management System solution at the US edition of the Hyperautomation Expo 2021. Vuram’s new Contract Management Solution is loaded with new features to tackle modern contract lifecycle management (CLM) challenges.
  • May 19, 2021, JK Tech, a global IT solutions company, has partnered with Evolute IQ, a market-leading ultra-automated technology company. Through this strategic alliance, JK Tech will use the e.IQ Low-code / No code Hyperautomation platform to co-develop innovative business solutions for claims, compliance, financial services, healthcare, retail customer journey management, and CPG.
  • October 2020, Mindfields, a global intelligent automation, and artificial intelligence (AI) consultancy, and Amelia, the largest independent leader in enterprise AI, announced a partnership to provide Australian customers with their hyper-automation services. The solution integrates Amelia, a market-leading conversational AI agent, with Mindfields' vertical and horizontal automation products such as CoE.exe, CFO.exe, MindVirutal, MindEzy, MindUni, and MindSupport. Mindfields automation implementation and consulting services will also be integrated into Amelia.
  • December 2020, Appian has announced the latest version of the Appian Low-code Automation Platform. With the new release, it's easier for IT departments to quickly and meaningfully derive business value from a new generation of powerful and scalable enterprise automation technology integrated into an industry-leading platform for low-code development.

Global Hyperautomation Market

Base Year:

2021

Forecast Period:

2022-2028

Historical Data:

2016 to 2020

Market Size in 2021:

USD 5.82 Bn.

Forecast Period 2022-28 CAGR:

21.75%

Market Size in 2028:

USD 18.91 Bn.

Segments Covered:

By Enterprise Size

  • SMEs
  • Large Enterprise

By Technology

  • Artificial Intelligence
  • Machine Learning
  • Robotic Process Automation
  • Others

By End Use

  • IT & Telecom
  • BFSI
  • Manufacturing
  • Retail
  • Automotive
  • Others

By Region

  • North America (U.S., Canada, Mexico)
  • Europe (Germany, U.K., France, Italy, Russia, Spain, Rest of Europe)
  • Asia-Pacific (China, India, Japan, Singapore, Australia, New Zealand, Rest of APAC)
  • Middle East & Africa (Turkey, Saudi Arabia, Iran, UAE, Africa, Rest of MEA)
  • South America (Brazil, Argentina, Rest of SA)

Key Market Drivers:

  • Increasing Demand from Different Industrial verticals

Key Market Restraints:

  • It is Costly and Complicated

Key Opportunities:

  • Rising Adoption in Financial Industry and Legal Technology

Companies Covered in the report:

  • UiPath, SolveXia, Mitsubishi Electric Corporation, Allerin Tech Pvt. Ltd., Wipro Limited, and Other Major Players

Chapter 1: Introduction
 1.1 Research Objectives
 1.2 Research Methodology
 1.3 Research Process
 1.4 Scope and Coverage
  1.4.1 Market Definition
  1.4.2 Key Questions Answered
 1.5 Market Segmentation

Chapter 2:Executive Summary

Chapter 3:Growth Opportunities By Segment
 3.1 By Enterprise Size
 3.2 By Technology
 3.3 By End User

Chapter 4: Market Landscape
 4.1 Porter's Five Forces Analysis
  4.1.1 Bargaining Power of Supplier
  4.1.2 Threat of New Entrants
  4.1.3 Threat of Substitutes
  4.1.4 Competitive Rivalry
  4.1.5 Bargaining Power Among Buyers
 4.2 Industry Value Chain Analysis
 4.3 Market Dynamics
  4.3.1 Drivers
  4.3.2 Restraints
  4.3.3 Opportunities
  4.5.4 Challenges
 4.4 Pestle Analysis
 4.5 Technological Roadmap
 4.6 Regulatory Landscape
 4.7 SWOT Analysis
 4.8 Price Trend Analysis
 4.9 Patent Analysis
 4.10 Analysis of the Impact of Covid-19
  4.10.1 Impact on the Overall Market
  4.10.2 Impact on the Supply Chain
  4.10.3 Impact on the Key Manufacturers
  4.10.4 Impact on the Pricing

Chapter 5: Hyperautomation Market by Enterprise Size
 5.1 Hyperautomation Market Overview Snapshot and Growth Engine
 5.2 Hyperautomation Market Overview
 5.3 SMEs
  5.3.1 Introduction and Market Overview
  5.3.2 Historic and Forecasted Market Size (2016-2028F)
  5.3.3 Key Market Trends, Growth Factors and Opportunities
  5.3.4 SMEs: Grographic Segmentation
 5.4 Large Enterprise
  5.4.1 Introduction and Market Overview
  5.4.2 Historic and Forecasted Market Size (2016-2028F)
  5.4.3 Key Market Trends, Growth Factors and Opportunities
  5.4.4 Large Enterprise: Grographic Segmentation

Chapter 6: Hyperautomation Market by Technology
 6.1 Hyperautomation Market Overview Snapshot and Growth Engine
 6.2 Hyperautomation Market Overview
 6.3 Artificial Intelligence
  6.3.1 Introduction and Market Overview
  6.3.2 Historic and Forecasted Market Size (2016-2028F)
  6.3.3 Key Market Trends, Growth Factors and Opportunities
  6.3.4 Artificial Intelligence: Grographic Segmentation
 6.4 Machine Learning
  6.4.1 Introduction and Market Overview
  6.4.2 Historic and Forecasted Market Size (2016-2028F)
  6.4.3 Key Market Trends, Growth Factors and Opportunities
  6.4.4 Machine Learning: Grographic Segmentation
 6.5 Robotic Process Automation
  6.5.1 Introduction and Market Overview
  6.5.2 Historic and Forecasted Market Size (2016-2028F)
  6.5.3 Key Market Trends, Growth Factors and Opportunities
  6.5.4 Robotic Process Automation: Grographic Segmentation
 6.6 Others
  6.6.1 Introduction and Market Overview
  6.6.2 Historic and Forecasted Market Size (2016-2028F)
  6.6.3 Key Market Trends, Growth Factors and Opportunities
  6.6.4 Others: Grographic Segmentation

Chapter 7: Hyperautomation Market by End User
 7.1 Hyperautomation Market Overview Snapshot and Growth Engine
 7.2 Hyperautomation Market Overview
 7.3 IT & Telecom
  7.3.1 Introduction and Market Overview
  7.3.2 Historic and Forecasted Market Size (2016-2028F)
  7.3.3 Key Market Trends, Growth Factors and Opportunities
  7.3.4 IT & Telecom: Grographic Segmentation
 7.4 BFSI
  7.4.1 Introduction and Market Overview
  7.4.2 Historic and Forecasted Market Size (2016-2028F)
  7.4.3 Key Market Trends, Growth Factors and Opportunities
  7.4.4 BFSI: Grographic Segmentation
 7.5 Manufacturing
  7.5.1 Introduction and Market Overview
  7.5.2 Historic and Forecasted Market Size (2016-2028F)
  7.5.3 Key Market Trends, Growth Factors and Opportunities
  7.5.4 Manufacturing: Grographic Segmentation
 7.6 Retail
  7.6.1 Introduction and Market Overview
  7.6.2 Historic and Forecasted Market Size (2016-2028F)
  7.6.3 Key Market Trends, Growth Factors and Opportunities
  7.6.4 Retail: Grographic Segmentation
 7.7 Automotive
  7.7.1 Introduction and Market Overview
  7.7.2 Historic and Forecasted Market Size (2016-2028F)
  7.7.3 Key Market Trends, Growth Factors and Opportunities
  7.7.4 Automotive: Grographic Segmentation
 7.8 Others
  7.8.1 Introduction and Market Overview
  7.8.2 Historic and Forecasted Market Size (2016-2028F)
  7.8.3 Key Market Trends, Growth Factors and Opportunities
  7.8.4 Others: Grographic Segmentation

Chapter 8: Company Profiles and Competitive Analysis
 8.1 Competitive Landscape
  8.1.1 Competitive Positioning
  8.1.2 Hyperautomation Sales and Market Share By Players
  8.1.3 Industry BCG Matrix
  8.1.4 Ansoff Matrix
  8.1.5 Hyperautomation Industry Concentration Ratio (CR5 and HHI)
  8.1.6 Top 5 Hyperautomation Players Market Share
  8.1.7 Mergers and Acquisitions
  8.1.8 Business Strategies By Top Players
 8.2 UIPATH
  8.2.1 Company Overview
  8.2.2 Key Executives
  8.2.3 Company Snapshot
  8.2.4 Operating Business Segments
  8.2.5 Product Portfolio
  8.2.6 Business Performance
  8.2.7 Key Strategic Moves and Recent Developments
  8.2.8 SWOT Analysis
 8.3 SOLVEXIA
 8.4 MITSUBISHI ELECTRIC CORPORATION
 8.5 ALLERIN TECH PVT. LTD.
 8.6 WIPRO LIMITED
 8.7 CATALYTIC INC.
 8.8 APPIAN
 8.9 TATA CONSULTANCY SERVICES LTD.
 8.10 ONEGLOBE LLC
 8.11 AUTOMATION ANYWHERE INC.
 8.12 JK TECH
 8.13 VURAM TECHNOLOGIES
 8.14 IBM
 8.15 ORACLE
 8.16 OTHERS MAJOR PLAYERS

Chapter 9: Global Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 9.1 Market Overview
 9.2 Historic and Forecasted Market Size By Enterprise Size
  9.2.1 SMEs
  9.2.2 Large Enterprise
 9.3 Historic and Forecasted Market Size By Technology
  9.3.1 Artificial Intelligence
  9.3.2 Machine Learning
  9.3.3 Robotic Process Automation
  9.3.4 Others
 9.4 Historic and Forecasted Market Size By End User
  9.4.1 IT & Telecom
  9.4.2 BFSI
  9.4.3 Manufacturing
  9.4.4 Retail
  9.4.5 Automotive
  9.4.6 Others

Chapter 10: North America Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 10.1 Key Market Trends, Growth Factors and Opportunities
 10.2 Impact of Covid-19
 10.3 Key Players
 10.4 Key Market Trends, Growth Factors and Opportunities
 10.4 Historic and Forecasted Market Size By Enterprise Size
  10.4.1 SMEs
  10.4.2 Large Enterprise
 10.5 Historic and Forecasted Market Size By Technology
  10.5.1 Artificial Intelligence
  10.5.2 Machine Learning
  10.5.3 Robotic Process Automation
  10.5.4 Others
 10.6 Historic and Forecasted Market Size By End User
  10.6.1 IT & Telecom
  10.6.2 BFSI
  10.6.3 Manufacturing
  10.6.4 Retail
  10.6.5 Automotive
  10.6.6 Others
 10.7 Historic and Forecast Market Size by Country
  10.7.1 U.S.
  10.7.2 Canada
  10.7.3 Mexico

Chapter 11: Europe Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 11.1 Key Market Trends, Growth Factors and Opportunities
 11.2 Impact of Covid-19
 11.3 Key Players
 11.4 Key Market Trends, Growth Factors and Opportunities
 11.4 Historic and Forecasted Market Size By Enterprise Size
  11.4.1 SMEs
  11.4.2 Large Enterprise
 11.5 Historic and Forecasted Market Size By Technology
  11.5.1 Artificial Intelligence
  11.5.2 Machine Learning
  11.5.3 Robotic Process Automation
  11.5.4 Others
 11.6 Historic and Forecasted Market Size By End User
  11.6.1 IT & Telecom
  11.6.2 BFSI
  11.6.3 Manufacturing
  11.6.4 Retail
  11.6.5 Automotive
  11.6.6 Others
 11.7 Historic and Forecast Market Size by Country
  11.7.1 Germany
  11.7.2 U.K.
  11.7.3 France
  11.7.4 Italy
  11.7.5 Russia
  11.7.6 Spain
  11.7.7 Rest of Europe

Chapter 12: Asia-Pacific Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 12.1 Key Market Trends, Growth Factors and Opportunities
 12.2 Impact of Covid-19
 12.3 Key Players
 12.4 Key Market Trends, Growth Factors and Opportunities
 12.4 Historic and Forecasted Market Size By Enterprise Size
  12.4.1 SMEs
  12.4.2 Large Enterprise
 12.5 Historic and Forecasted Market Size By Technology
  12.5.1 Artificial Intelligence
  12.5.2 Machine Learning
  12.5.3 Robotic Process Automation
  12.5.4 Others
 12.6 Historic and Forecasted Market Size By End User
  12.6.1 IT & Telecom
  12.6.2 BFSI
  12.6.3 Manufacturing
  12.6.4 Retail
  12.6.5 Automotive
  12.6.6 Others
 12.7 Historic and Forecast Market Size by Country
  12.7.1 China
  12.7.2 India
  12.7.3 Japan
  12.7.4 Singapore
  12.7.5 Australia
  12.7.6 New Zealand
  12.7.7 Rest of APAC

Chapter 13: Middle East & Africa Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 13.1 Key Market Trends, Growth Factors and Opportunities
 13.2 Impact of Covid-19
 13.3 Key Players
 13.4 Key Market Trends, Growth Factors and Opportunities
 13.4 Historic and Forecasted Market Size By Enterprise Size
  13.4.1 SMEs
  13.4.2 Large Enterprise
 13.5 Historic and Forecasted Market Size By Technology
  13.5.1 Artificial Intelligence
  13.5.2 Machine Learning
  13.5.3 Robotic Process Automation
  13.5.4 Others
 13.6 Historic and Forecasted Market Size By End User
  13.6.1 IT & Telecom
  13.6.2 BFSI
  13.6.3 Manufacturing
  13.6.4 Retail
  13.6.5 Automotive
  13.6.6 Others
 13.7 Historic and Forecast Market Size by Country
  13.7.1 Turkey
  13.7.2 Saudi Arabia
  13.7.3 Iran
  13.7.4 UAE
  13.7.5 Africa
  13.7.6 Rest of MEA

Chapter 14: South America Hyperautomation Market Analysis, Insights and Forecast, 2016-2028
 14.1 Key Market Trends, Growth Factors and Opportunities
 14.2 Impact of Covid-19
 14.3 Key Players
 14.4 Key Market Trends, Growth Factors and Opportunities
 14.4 Historic and Forecasted Market Size By Enterprise Size
  14.4.1 SMEs
  14.4.2 Large Enterprise
 14.5 Historic and Forecasted Market Size By Technology
  14.5.1 Artificial Intelligence
  14.5.2 Machine Learning
  14.5.3 Robotic Process Automation
  14.5.4 Others
 14.6 Historic and Forecasted Market Size By End User
  14.6.1 IT & Telecom
  14.6.2 BFSI
  14.6.3 Manufacturing
  14.6.4 Retail
  14.6.5 Automotive
  14.6.6 Others
 14.7 Historic and Forecast Market Size by Country
  14.7.1 Brazil
  14.7.2 Argentina
  14.7.3 Rest of SA

Chapter 15 Investment Analysis

Chapter 16 Analyst Viewpoint and Conclusion

Global Hyperautomation Market

Base Year:

2021

Forecast Period:

2022-2028

Historical Data:

2016 to 2020

Market Size in 2021:

USD 5.82 Bn.

Forecast Period 2022-28 CAGR:

21.75%

Market Size in 2028:

USD 18.91 Bn.

Segments Covered:

By Enterprise Size

  • SMEs
  • Large Enterprise

By Technology

  • Artificial Intelligence
  • Machine Learning
  • Robotic Process Automation
  • Others

By End Use

  • IT & Telecom
  • BFSI
  • Manufacturing
  • Retail
  • Automotive
  • Others

By Region

  • North America (U.S., Canada, Mexico)
  • Europe (Germany, U.K., France, Italy, Russia, Spain, Rest of Europe)
  • Asia-Pacific (China, India, Japan, Singapore, Australia, New Zealand, Rest of APAC)
  • Middle East & Africa (Turkey, Saudi Arabia, Iran, UAE, Africa, Rest of MEA)
  • South America (Brazil, Argentina, Rest of SA)

Key Market Drivers:

  • Increasing Demand from Different Industrial verticals

Key Market Restraints:

  • It is Costly and Complicated

Key Opportunities:

  • Rising Adoption in Financial Industry and Legal Technology

Companies Covered in the report:

  • UiPath, SolveXia, Mitsubishi Electric Corporation, Allerin Tech Pvt. Ltd., Wipro Limited, and Other Major Players

LIST OF TABLES

TABLE 001. EXECUTIVE SUMMARY
TABLE 002. HYPERAUTOMATION MARKET BARGAINING POWER OF SUPPLIERS
TABLE 003. HYPERAUTOMATION MARKET BARGAINING POWER OF CUSTOMERS
TABLE 004. HYPERAUTOMATION MARKET COMPETITIVE RIVALRY
TABLE 005. HYPERAUTOMATION MARKET THREAT OF NEW ENTRANTS
TABLE 006. HYPERAUTOMATION MARKET THREAT OF SUBSTITUTES
TABLE 007. HYPERAUTOMATION MARKET BY ENTERPRISE SIZE
TABLE 008. SMES MARKET OVERVIEW (2016-2028)
TABLE 009. LARGE ENTERPRISE MARKET OVERVIEW (2016-2028)
TABLE 010. HYPERAUTOMATION MARKET BY TECHNOLOGY
TABLE 011. ARTIFICIAL INTELLIGENCE MARKET OVERVIEW (2016-2028)
TABLE 012. MACHINE LEARNING MARKET OVERVIEW (2016-2028)
TABLE 013. ROBOTIC PROCESS AUTOMATION MARKET OVERVIEW (2016-2028)
TABLE 014. OTHERS MARKET OVERVIEW (2016-2028)
TABLE 015. HYPERAUTOMATION MARKET BY END USER
TABLE 016. IT & TELECOM MARKET OVERVIEW (2016-2028)
TABLE 017. BFSI MARKET OVERVIEW (2016-2028)
TABLE 018. MANUFACTURING MARKET OVERVIEW (2016-2028)
TABLE 019. RETAIL MARKET OVERVIEW (2016-2028)
TABLE 020. AUTOMOTIVE MARKET OVERVIEW (2016-2028)
TABLE 021. OTHERS MARKET OVERVIEW (2016-2028)
TABLE 022. NORTH AMERICA HYPERAUTOMATION MARKET, BY ENTERPRISE SIZE (2016-2028)
TABLE 023. NORTH AMERICA HYPERAUTOMATION MARKET, BY TECHNOLOGY (2016-2028)
TABLE 024. NORTH AMERICA HYPERAUTOMATION MARKET, BY END USER (2016-2028)
TABLE 025. N HYPERAUTOMATION MARKET, BY COUNTRY (2016-2028)
TABLE 026. EUROPE HYPERAUTOMATION MARKET, BY ENTERPRISE SIZE (2016-2028)
TABLE 027. EUROPE HYPERAUTOMATION MARKET, BY TECHNOLOGY (2016-2028)
TABLE 028. EUROPE HYPERAUTOMATION MARKET, BY END USER (2016-2028)
TABLE 029. HYPERAUTOMATION MARKET, BY COUNTRY (2016-2028)
TABLE 030. ASIA PACIFIC HYPERAUTOMATION MARKET, BY ENTERPRISE SIZE (2016-2028)
TABLE 031. ASIA PACIFIC HYPERAUTOMATION MARKET, BY TECHNOLOGY (2016-2028)
TABLE 032. ASIA PACIFIC HYPERAUTOMATION MARKET, BY END USER (2016-2028)
TABLE 033. HYPERAUTOMATION MARKET, BY COUNTRY (2016-2028)
TABLE 034. MIDDLE EAST & AFRICA HYPERAUTOMATION MARKET, BY ENTERPRISE SIZE (2016-2028)
TABLE 035. MIDDLE EAST & AFRICA HYPERAUTOMATION MARKET, BY TECHNOLOGY (2016-2028)
TABLE 036. MIDDLE EAST & AFRICA HYPERAUTOMATION MARKET, BY END USER (2016-2028)
TABLE 037. HYPERAUTOMATION MARKET, BY COUNTRY (2016-2028)
TABLE 038. SOUTH AMERICA HYPERAUTOMATION MARKET, BY ENTERPRISE SIZE (2016-2028)
TABLE 039. SOUTH AMERICA HYPERAUTOMATION MARKET, BY TECHNOLOGY (2016-2028)
TABLE 040. SOUTH AMERICA HYPERAUTOMATION MARKET, BY END USER (2016-2028)
TABLE 041. HYPERAUTOMATION MARKET, BY COUNTRY (2016-2028)
TABLE 042. UIPATH: SNAPSHOT
TABLE 043. UIPATH: BUSINESS PERFORMANCE
TABLE 044. UIPATH: PRODUCT PORTFOLIO
TABLE 045. UIPATH: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 045. SOLVEXIA: SNAPSHOT
TABLE 046. SOLVEXIA: BUSINESS PERFORMANCE
TABLE 047. SOLVEXIA: PRODUCT PORTFOLIO
TABLE 048. SOLVEXIA: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 048. MITSUBISHI ELECTRIC CORPORATION: SNAPSHOT
TABLE 049. MITSUBISHI ELECTRIC CORPORATION: BUSINESS PERFORMANCE
TABLE 050. MITSUBISHI ELECTRIC CORPORATION: PRODUCT PORTFOLIO
TABLE 051. MITSUBISHI ELECTRIC CORPORATION: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 051. ALLERIN TECH PVT. LTD.: SNAPSHOT
TABLE 052. ALLERIN TECH PVT. LTD.: BUSINESS PERFORMANCE
TABLE 053. ALLERIN TECH PVT. LTD.: PRODUCT PORTFOLIO
TABLE 054. ALLERIN TECH PVT. LTD.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 054. WIPRO LIMITED: SNAPSHOT
TABLE 055. WIPRO LIMITED: BUSINESS PERFORMANCE
TABLE 056. WIPRO LIMITED: PRODUCT PORTFOLIO
TABLE 057. WIPRO LIMITED: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 057. CATALYTIC INC.: SNAPSHOT
TABLE 058. CATALYTIC INC.: BUSINESS PERFORMANCE
TABLE 059. CATALYTIC INC.: PRODUCT PORTFOLIO
TABLE 060. CATALYTIC INC.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 060. APPIAN: SNAPSHOT
TABLE 061. APPIAN: BUSINESS PERFORMANCE
TABLE 062. APPIAN: PRODUCT PORTFOLIO
TABLE 063. APPIAN: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 063. TATA CONSULTANCY SERVICES LTD.: SNAPSHOT
TABLE 064. TATA CONSULTANCY SERVICES LTD.: BUSINESS PERFORMANCE
TABLE 065. TATA CONSULTANCY SERVICES LTD.: PRODUCT PORTFOLIO
TABLE 066. TATA CONSULTANCY SERVICES LTD.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 066. ONEGLOBE LLC: SNAPSHOT
TABLE 067. ONEGLOBE LLC: BUSINESS PERFORMANCE
TABLE 068. ONEGLOBE LLC: PRODUCT PORTFOLIO
TABLE 069. ONEGLOBE LLC: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 069. AUTOMATION ANYWHERE INC.: SNAPSHOT
TABLE 070. AUTOMATION ANYWHERE INC.: BUSINESS PERFORMANCE
TABLE 071. AUTOMATION ANYWHERE INC.: PRODUCT PORTFOLIO
TABLE 072. AUTOMATION ANYWHERE INC.: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 072. JK TECH: SNAPSHOT
TABLE 073. JK TECH: BUSINESS PERFORMANCE
TABLE 074. JK TECH: PRODUCT PORTFOLIO
TABLE 075. JK TECH: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 075. VURAM TECHNOLOGIES: SNAPSHOT
TABLE 076. VURAM TECHNOLOGIES: BUSINESS PERFORMANCE
TABLE 077. VURAM TECHNOLOGIES: PRODUCT PORTFOLIO
TABLE 078. VURAM TECHNOLOGIES: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 078. IBM: SNAPSHOT
TABLE 079. IBM: BUSINESS PERFORMANCE
TABLE 080. IBM: PRODUCT PORTFOLIO
TABLE 081. IBM: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 081. ORACLE: SNAPSHOT
TABLE 082. ORACLE: BUSINESS PERFORMANCE
TABLE 083. ORACLE: PRODUCT PORTFOLIO
TABLE 084. ORACLE: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 084. OTHERS MAJOR PLAYERS: SNAPSHOT
TABLE 085. OTHERS MAJOR PLAYERS: BUSINESS PERFORMANCE
TABLE 086. OTHERS MAJOR PLAYERS: PRODUCT PORTFOLIO
TABLE 087. OTHERS MAJOR PLAYERS: KEY STRATEGIC MOVES AND DEVELOPMENTS

LIST OF FIGURES

FIGURE 001. YEARS CONSIDERED FOR ANALYSIS
FIGURE 002. SCOPE OF THE STUDY
FIGURE 003. HYPERAUTOMATION MARKET OVERVIEW BY REGIONS
FIGURE 004. PORTER'S FIVE FORCES ANALYSIS
FIGURE 005. BARGAINING POWER OF SUPPLIERS
FIGURE 006. COMPETITIVE RIVALRYFIGURE 007. THREAT OF NEW ENTRANTS
FIGURE 008. THREAT OF SUBSTITUTES
FIGURE 009. VALUE CHAIN ANALYSIS
FIGURE 010. PESTLE ANALYSIS
FIGURE 011. HYPERAUTOMATION MARKET OVERVIEW BY ENTERPRISE SIZE
FIGURE 012. SMES MARKET OVERVIEW (2016-2028)
FIGURE 013. LARGE ENTERPRISE MARKET OVERVIEW (2016-2028)
FIGURE 014. HYPERAUTOMATION MARKET OVERVIEW BY TECHNOLOGY
FIGURE 015. ARTIFICIAL INTELLIGENCE MARKET OVERVIEW (2016-2028)
FIGURE 016. MACHINE LEARNING MARKET OVERVIEW (2016-2028)
FIGURE 017. ROBOTIC PROCESS AUTOMATION MARKET OVERVIEW (2016-2028)
FIGURE 018. OTHERS MARKET OVERVIEW (2016-2028)
FIGURE 019. HYPERAUTOMATION MARKET OVERVIEW BY END USER
FIGURE 020. IT & TELECOM MARKET OVERVIEW (2016-2028)
FIGURE 021. BFSI MARKET OVERVIEW (2016-2028)
FIGURE 022. MANUFACTURING MARKET OVERVIEW (2016-2028)
FIGURE 023. RETAIL MARKET OVERVIEW (2016-2028)
FIGURE 024. AUTOMOTIVE MARKET OVERVIEW (2016-2028)
FIGURE 025. OTHERS MARKET OVERVIEW (2016-2028)
FIGURE 026. NORTH AMERICA HYPERAUTOMATION MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 027. EUROPE HYPERAUTOMATION MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 028. ASIA PACIFIC HYPERAUTOMATION MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 029. MIDDLE EAST & AFRICA HYPERAUTOMATION MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 030. SOUTH AMERICA HYPERAUTOMATION MARKET OVERVIEW BY COUNTRY (2016-2028)

Frequently Asked Questions :

What would be the forecast period in the Hyperautomation Market research report?

The forecast period in the Hyperautomation Market research report is 2022-2028.

Who are the key players in Hyperautomation Market?

UiPath, SolveXia, Mitsubishi Electric Corporation, Allerin Tech Pvt. Ltd., Wipro Limited, Catalytic Inc., Appian, Tata Consultancy Services Ltd., OneGlobe LLC, Automation Anywhere Inc, JK Tech, Vuram Technologies, IBM, Oracle, and Other Major Players.

What are the segments of Hyperautomation Market?

Hyperautomation Market is segmented into Enterprise Size, Technology, End User and region. By Enterprise Size, the market is categorized SMEs, Large Enterprise. By Technology, the market is categorized into Artificial Intelligence, Machine Learning, Robotic Process Automation, Others. By End User, the market is categorized IT & Telecom, BFSI, Manufacturing, Retail, Automotive, Others. By region, it is analysed across North America (U.S.; Canada; Mexico), Europe (Germany; U.K.; France; Italy; Russia; Spain, etc.), Asia-Pacific (China; India; Japan; Southeast Asia, etc.), South America (Brazil; Argentina, etc.), Middle East & Africa (Saudi Arabia; South Africa, etc.).

What is the Hyperautomation Market?

Hyperautomation is a business-centric, disciplined approach that organizations use to quickly identify, inspect, and automate as much business and IT processes as possible. Hyperautomation involves the systematic use of multiple technologies.

How big is Hyperautomation Market?

Global Hyperautomation Market was valued at USD 5.82 Billion in 2021 and is expected to reach USD 18.91 Billion by the year 2028, at a CAGR of 21.75%.