Intelligent Process Automation Market Size, Share, Growth Analysis

Intelligent Process Automation Market Analysis (2023 - 2030)

As per our research report, the global intelligent process automation market size was valued at $8.1 Billion in 2021 and is projected to reach $20.73 Billion by 2027. This market is witnessing a healthy CAGR of 11.5% from 2022 to 2027. Rising adoption of intelligent process automation in various industries, increasing investment in digitalization, and favourable government initiatives are majorly driving the growth of the market.

The global epidemic of COVID-19 is sending shockwaves across financial markets, disrupting supply chains and goods availability, and having a huge impact on how we conduct everyday business. Early adopters should have a significant competitive advantage over late adopters. IPA solutions can help firms successfully drive value during these trying times, as well as the opportunity they bring.

During the COVID-19 lockdown, they were confronted with inefficiencies in legacy systems and insufficient capacity. Organizations are pursuing digital transformation, with an emphasis on robotic process automation (RPA) and hyper-automation, in order to accelerate market growth following the COVID-19 epidemic. For most sector verticals, such as travel and hospitality, manufacturing and logistics, and retail, the COVID-19 lockdown has resulted in a financial pressure. Organizations will aim to spend strategically following COVID-19, not spending much on new operations, even after acknowledging the necessity for automation and digitalization to drive job efficiency and time consumption.

Key Market Insights:

• The majority of industry verticals are experiencing operational delays and challenges in employee supervision as a result of the work from home scenario, necessitating the need for a more efficient operational model based on digitization and automation. It is predicted to have an impact on the IPA solutions market as demand grows as more businesses adopt digitalization and automation. Enterprises must become more digital, making digitalization a primary motivation for diverse organisations to adopt the IA process. Other advantages include increased operational efficiency and time management, which are driving IPA tool use. In numerous enterprises, applications such as digital help using bots are being used to answer client questions. Organizations will expand digital innovations in the face of COVID-19 by emphasising digital channels in order to maintain operational consistency.
• Intelligent process automation is built on a foundation of machine learning, autonomics, natural language processing, and machine vision, among other things. Machine learning refers to a computer system's ability to enhance its performance without having to follow instructions by exposing it to data. The term "autonomics" refers to systems that are designed to conduct human-like duties and operations. It's utilised in back office centres to handle high-volume, rule-based operations. The ability of computers to recognise objects and actions in photographs is referred to as natural language processing. To examine the photos, it employs a series of image processing techniques. Machine vision, on the other hand, is the ability of computers to read human language and take appropriate action.
• While the outbreak was concentrated in China, the economic impact was felt throughout Asia. The most affected countries in the region are India, Iran, and China. Organizations have been forced to operate with a smaller personnel due to the increased threat of infection. Leading technology hubs are located in Beijing, China, and Bangalore, India, and a big number of vendors are attempting to take advantage of this opportunity to promote IA adoption. In March 2020, China-based Encootech raised $30 million from Sequoia Capital, GSR Ventures, and Future Capital. Similarly, Automation Anywhere announced a three-year investment of USD 100 million in its Bangalore, India, Research and Development (R&D) facility.
• Intelligent process automation solutions are increasingly being adopted by the telecoms and IT industries to reduce operating costs, improve operational efficiency, and increase customer satisfaction. Centralization and consolidation of request management systems for greater efficiency, transparency, and visibility for service functions; automation of Service Level Agreement (SLA) reporting; and elimination of human efforts are all advantages of IPA solutions. Advancements in technologies such as 5G, IoT, AI, and ML have helped the telecoms and IT industries the most. As these technologies have evolved, the demand for increasing infrastructure and automating processes in the telecoms and IT sphere has increased.
• On-premises deployment refers to the installation of software and hardware at a client's location. When compared to the cloud model, it is more expensive. The typical method of delivering the IPA solution in businesses is through on-premises deployment. The on-premises IPA solution gives businesses complete control over their apps, platforms, data, and systems, which are all handled and managed by their own IT professionals.

Market Segmentation

By Technology:

• Natural Language Processing
• Machine and Deep Learning
• Neutral Networks
• Mini bots and RPA
• Computer Vision
• Virtual Agents
• Biometrics
• Sensor Processing
• Others

By Component:

• Solutions
  • Software Tools
  • Platforms
• Services
  • Professional Services
  • Advisory/Consulting
  • Design and Implementation
  • Training
  • Support and Maintenance
• Managed Services

By Deployment:

• On-Premise

• Cloud-Based

By Application:

• IT Operations
• Business Process Automation
• Application Management
• Content Management
• Security
• Human Resource Management
• Service Orchestration
• Robotic Process Automation
• Others

By End-User Industry:

• Banking, Financial Services, and Insurance (BFSI)
• Telecommunications and IT                                                                      
• Transport and Logistics
• Media and Entertainment
• Retail and e-commerce
• Manufacturing
• Healthcare and Life Sciences
• Travel and Hospitality
• Government and Public Sector
• Education
• Agriculture
• Automotive
• Others

By Region:

• North America
• Europe
• Asia-Pacific
• Rest of the World

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