Category

Global Hyperautomation Market Size, Share, Opportunities And Trends By Technology Type (Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Biometrics, Chatbots, Natural Language Generation (NLG), Others), By End Use Industry (Manufacturing, Automotive, Healthcare, BFSI, Retail, Others), And By Geography - Forecasts From 2021 To 2026

Published: Jul 2021 | Report Code:  KSI061614139 | Pages:  120

The global hyperautomation market was evaluated at US$4.904 billion for the year 2020 which is projected to witness promising growth over the forecast period.

Hyperautomation can be defined as the use of technologies like robotic process automation, artificial intelligence, and machine learning among others which when combined, can be used to automate tasks that were once done by humans. Hyperautomation consists of various automation technologies like robotic process automation (RPA), business process management (BPM), artificial intelligence (AI), Machine learning (ML), and advanced analytics which act as its components. These components have their own wide applications across various industries, therefore, when combined, have the capability of automating even the most complex business processes which would otherwise have had required human experts. Hyperautomation can be defined as the next level of automation, the prior being robotic process automation (RPA).  This is due to the fact that using RPA, only those repetitive tasks could be automated which were rule-based and utilize structured data, whereas hyperautomation can be used to automate nearly any tedious and scalable task. There have been fears that advancements in hyperautomation and its widespread adoption may lead to huge job losses as most tasks will get automated. Rather, through automation, humans will be freed from repetitive and low-value tasks to focus on ones that are of a higher value to the organization. Together, automation and human involvement help organizations to provide superior customer experiences while reducing operational costs and boosting profitability. Hyperautomation provides significant benefits as it provides the organization with flexibility in terms of not relying on just a single automation technology which helps the organization in achieving true digital agility. It improves employee productivity as they can automate repetitive tasks which don’t require their special attention and focus on more important things while also reducing human errors and decreasing operations costs.  Automation, however, requires careful planning and implementation. Organizations need to understand how these technologies will fit into their existing workflows. Another major attribute for hyperautomation is integration. To achieve scalability in operations, various automation technologies must work together seamlessly. Careful planning, implementation, and improvement of processes should be carried out for maximum return on investment. Hyperautomation has various applications in industries like manufacturing, automotive, healthcare, BFSI, retail, etc. with the manufacturing sector being the biggest adopter and key growth driving sector.

While having various benefits, hyperautomation has high initial costs. The return on investment should be carefully ascertained before any investments are made in the technology. Also, integration and interoperability of the underlying technologies are very important which requires high technical knowledge. Therefore companies that may not have the financial resources or the technical know-how may miss out on this opportunity.

The global automation market can be segmented on the basis of Technology Type, End-Use Industry, and Geography.

By technology, the market is segmented as Robotic Process Automation (RPA), Machine Learning (ML), Chatbots, Biometrics, Natural Language Generation, Context-aware Computing, and others.

By end-user industry, the market is segmented as Manufacturing, Automotive, Healthcare, BFSI, Retail, and others.

By geography, the market can be segmented into North America, South America, Europe, Middle East, and Africa, and Asia – Pacific.

Growth Factors

  • Reduces operational cost

Hyperautomation reduces operational costs of a company by reducing the number of humans working on repetitive tasks which also reduces the scope of human errors and time is taken to complete these tasks.

  • Increases revenue

With the automation of repetitive tasks in an organization, the employees can now focus on higher-value tasks which will in - turn increase the revenue of the organization.

Restraints

  • High initial costs

Hyperautomation requires high investments as these tools are expensive to purchase. The deployment costs are also high as the integration of these tools in the organization’s current workflow requires experts who charge good amounts for their services.

  • Expertise required

The integration of these systems in the organization’s current workflow requires expertise to derive maximum benefits out of these tools, their seamless integration with the workflows is an absolute necessity. Also, the interoperability of these technologies is important and thus, organizations that lack the technical knowledge may have a hard time getting the maximum ROI out of these tools which may act as a restrain to the growth of the hyperautomation market.

Impact of COVID – 19

Due to the economic depression caused by COVID – 19, many companies resisted investing in these emerging technologies. The manufacturing sector which is considered the biggest adopter of hyperautomation tools faced a slow-down in manufacturing activities across the globe, which affected the growth of the hyperautomation market.

Key Developments

  • George Mason University Centre and UiPath Partner to Form Robotic Process Automation Initiative - The mission of the RPA Initiative is to research, educate, and communicate how the adoption of this emerging technology can improve productivity, operations, and service delivery of public sector organizations.
  • Udacity, UiPath Launch Robotic Process Automation Developer Nanodegree® Program to Future-Proof Careers - Udacity, the global online learning platform that trains the world’s workforce for the careers of the future, today launched its Robotic Process Automation (RPA) Developer Nanodegree program in conjunction with UiPath, the leading enterprise robotic process automation software company.
  • Alteryx and UiPath Partner to Accelerate Digital Transformation with Hyperautomation - Alteryx and UiPath, today announced a strategic partnership to speed end-to-end automation across data-driven business processes. Together, UiPath and Alteryx offer a solution that empowers business leaders, analysts, data scientists, and data engineers to increase operational efficiency and automate time-to-insight, bringing together the benefits of APA and RPA to drive faster business outcomes.
  • UiPath Launches Virtual Streaming Solution to Support Fully Remote UiPath Immersion Lab Automation Experience.

Competitive Insights

The global hyperautomation market is a competitive and saturated market with a number of big and small players catering to local and international demands. Prominent/major key market players in the global hyperautomation market include UiPath, SolveXia, Appian, Mitsubishi Electric Corporation, Automation Anywhere Inc. among others. The players in the global hyperautomation market are implementing various growth strategies to gain a competitive advantage over their competitors in this market. Major market players in the market have been covered along with their relative competitive strategies and the report also mentions recent deals and investments of different market players over the last few years. The company profiles section details the business overview, financial performance (public companies) for the past few years, key products and services being offered along with the recent deals and investments of these important players in the global hyperautomation market.

Segmentation

  • By Technology Type
    • Robotic Process Automation (RPA)
    • Artificial Intelligence (AI)
    • Machine Learning (ML)
    • Biometrics
    • Chatbots
    • Natural Language Generation (NLG)
    • Others
  • By End-Use Industry
    • Manufacturing
    • Automotive
    • Healthcare
    • BFSI
    • Retail
    • Others
  • By Geography
    • North America
      • USA
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • Germany
      • Spain
      • United Kingdom
      • France
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Others
    • Asia Pacific
      • China
      • Japan
      • India
      • Australia
      • South Korea
      • Others

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