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Global Intelligent Process Automation Market to reach USD XX million by 2028.

Global Intelligent Process Automation Market Size study, By Technology (Machine Learning, Natural Language Processing, Virtual Agents, Computer Vision, Others), By Component (Solution, Service), By Vertical (BFSI, Healthcare, Retail, IT & Telecom, Manufacturing, Others), and Regional Forecasts 2022-2028

Product Code: ICTEITS-87756842
Publish Date: 25-05-2022
Page: 200

Global Intelligent Process Automation Market is valued at approximately USDXX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2028. Intelligent Process Automation (IPA) is the usage of Artificial Intelligence and associated emerging technologies in robotic process automation, along with computer vision, cognitive automation, and machine learning. This is an automation process that helps in creating smart business processes and streamlining the workflow. The surging demand for automated solutions for business continuity planning, growing adoption of machine learning (ML) and advanced analytics, growth of the robotic process automation industry, and increasing investments in digital transformation are the key factors impelling the market demand across the globe. For instance, according to Statista, the global robotic process automation (RPA) market size was worth nearly USD 1.23 billion in 2020. Also, the amount is anticipated to increase and is likely expected to reach around USD 13.39 billion by the year 2030. Therefore, the robotic process automation (RPA) industry is flourishing the demand for the Intelligent Process Automation, which, in turn, augments the market growth in the approaching years. However, the rise in cybersecurity threats and the high cost of investment impede the growth of the market over the forecast period of 2022-2028. Also, effective monitoring of data and fraud detection and growing investment in the IPA market are anticipated to act as catalyzing factors for the market demand during the forecast period.

The key regions considered for the global Intelligent Process Automation Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing penetration of automation and process management solutions throughout the enterprise and presence of the leading market players. Whereas, Asia-Pacific is anticipated to exhibit the highest CAGR over the forecast period 2022-2028. Factors such as the increasing adoption of emerging technologies such as artificial intelligence, machine learning, RPA, and other related technologies, as well as transformation of developing countries such as India, and China into digital economies, would create lucrative growth prospects for the Intelligent Process Automation Market across the Asia-Pacific region.

Major market players included in this report are:
HCL Technologies Limited
IBM Corporation
Infosys Limited
Pegasystems Inc.
Atos Syntel Inc.
Tata Consultancy Services Limited
Tech Mahindra Limited
UiPath
Wipro Limited.
Virtual Operations

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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Technology:
Machine Learning
Natural Language Processing
Virtual Agents
Computer Vision
Others
By Component:
Solution
Service
By Vertical:
BFSI
Healthcare
Retail
IT & Telecom
Manufacturing
Others
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

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Intelligent Process Automation Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Intelligent Process Automation Market, by Region, 2020-2028 (USD Million)
1.2.2. Intelligent Process Automation Market, by Technology, 2020-2028 (USD Million)
1.2.3. Intelligent Process Automation Market, by Component, 2020-2028 (USD Million)
1.2.4. Intelligent Process Automation Market, by Vertical, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Intelligent Process Automation 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 Intelligent Process Automation Market Dynamics
3.1. Intelligent Process Automation Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Surging demand for automated solutions for business continuity planning
3.1.1.2. Growing adoption of ML and advanced analytics
3.1.2. Market Challenges
3.1.2.1. Rise in cybersecurity threats
3.1.2.2. High cost of investment
3.1.3. Market Opportunities
3.1.3.1. Effective monitoring of data and fraud detection
3.1.3.2. Growing investment in IPA market
Chapter 4. Global Intelligent Process Automation 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
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Intelligent Process Automation Market, by Technology
6.1. Market Snapshot
6.2. Global Intelligent Process Automation Market by Technology, Performance – Potential Analysis
6.3. Global Intelligent Process Automation Market Estimates & Forecasts by Technology, 2018-2028 (USD Million)
6.4. Intelligent Process Automation Market, Sub Segment Analysis
6.4.1. Machine Learning
6.4.2. Natural Language Processing
6.4.3. Virtual Agents
6.4.4. Computer Vision
6.4.5. Others
Chapter 7. Global Intelligent Process Automation Market, by Component
7.1. Market Snapshot
7.2. Global Intelligent Process Automation Market by Component, Performance – Potential Analysis
7.3. Global Intelligent Process Automation Market Estimates & Forecasts by Component, 2018-2028 (USD Million)
7.4. Intelligent Process Automation Market, Sub Segment Analysis
7.4.1. Solution
7.4.2. Service
Chapter 8. Global Intelligent Process Automation Market, by Vertical
8.1. Market Snapshot
8.2. Global Intelligent Process Automation Market by Vertical, Performance – Potential Analysis
8.3. Global Intelligent Process Automation Market Estimates & Forecasts by Vertical, 2018-2028 (USD Million)
8.4. Intelligent Process Automation Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. Healthcare
8.4.3. Retail
8.4.4. IT & Telecom
8.4.5. Manufacturing
8.4.6. Others
Chapter 9. Global Intelligent Process Automation Market, Regional Analysis
9.1. Intelligent Process Automation Market, Regional Market Snapshot
9.2. North America Intelligent Process Automation Market
9.2.1. U.S. Intelligent Process Automation Market
9.2.1.1. Technology breakdown estimates & forecasts, 2018-2028
9.2.1.2. Component breakdown estimates & forecasts, 2018-2028
9.2.1.3. Vertical breakdown estimates & forecasts, 2018-2028
9.2.2. Canada Intelligent Process Automation Market
9.3. Europe Intelligent Process Automation Market Snapshot
9.3.1. U.K. Intelligent Process Automation Market
9.3.2. Germany Intelligent Process Automation Market
9.3.3. France Intelligent Process Automation Market
9.3.4. Spain Intelligent Process Automation Market
9.3.5. Italy Intelligent Process Automation Market
9.3.6. Rest of Europe Intelligent Process Automation Market
9.4. Asia-Pacific Intelligent Process Automation Market Snapshot
9.4.1. China Intelligent Process Automation Market
9.4.2. India Intelligent Process Automation Market
9.4.3. Japan Intelligent Process Automation Market
9.4.4. Australia Intelligent Process Automation Market
9.4.5. South Korea Intelligent Process Automation Market
9.4.6. Rest of Asia Pacific Intelligent Process Automation Market
9.5. Latin America Intelligent Process Automation Market Snapshot
9.5.1. Brazil Intelligent Process Automation Market
9.5.2. Mexico Intelligent Process Automation Market
9.6. Rest of The World Intelligent Process Automation Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. HCL Technologies Limited
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. IBM Corporation
10.2.3. Infosys Limited
10.2.4. Pegasystems Inc.
10.2.5. Atos Syntel Inc.
10.2.6. Tata Consultancy Services Limited
10.2.7. Tech Mahindra Limited
10.2.8. UiPath
10.2.9. Wipro Limited.
10.2.10. Virtual Operations
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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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.
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