PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1320170
PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1320170
Cognitive process automation market size was valued at USD 4,502.8 Million in 2022, expanding at a CAGR of 12.6% from 2023 to 2030.
Cognitive process automation uses artificial intelligence (AI) technologies to automate cognitive tasks including, machine learning, reasoning, and natural language processing. In addition, cognitive process automation aims to create these tasks faster and easier for machines or people to perform. Moreover, more efficient automated cognitive processes required a higher level of engineering skill. These use cases are typically controlled by an automation center or dedicated team of excellence that is educated with best practices for growing automated systems. Furthermore, this can minimize company risks like unanticipated cloud fees for systems that grew faster than intended.
The market growth is driven by the adoption of automation features in optimizing routine tasks which has resulted in reduced the operational cost and increased productivity. Additionally, cognitive robotic process automation software bots have been developed as a result of integrated cognitive abilities with the robotic process by automation service vendors. These features are often used in the healthcare sector, BFSI, IT, and telecom as they assist automate repetitive tasks and this boosts the market growth. However, in industries, the use of cognitive process automation technology needs high capital investments for installation, licensing, and setup, this may restrain the market growth over the forecast period. Moreover, the integration of cognitive capabilities into robotic process automation platforms has contributed to the creation of Cognitive Robotic Process Automation software bots, Furthermore, examples of technological breakthroughs are speech recognition, natural language processing, and machine learning that can help enterprises in judgment-based operations and automating perceptual. These tools result in the study of structured, semi-structured, and unstructured documents to extract, find, and structure data for future research. Thereby, all such factors are attributed to driving the market demand for the cognitive process automation market.
The global cognitive process automation market is segmented on the basis of type, services, application, industry vertical, and region.
The market is divided into two categories based on type: intelligent process automation and robotic process automation. The robotic process automation segment is likely to possess the largest revenue growth. Numerous factors including the rising requirement to optimize operations for maximum return & increased productivity, changing business processes across enterprises, and integrating advanced technologies are expected to drive segment growth. Additionally, robotic process automation (RPA) is especially effective in automating manual, repetitive tasks, including validation, data entry, basic calculations, form filling, and extraction. Moreover, by combining RPA with cognitive capabilities, organizations can automate more intricate decision-making processes, handling of unstructured data, and data analysis.
The market is divided into four categories based on services: HR, finance, IT operations, and procurement. The finance segment is expected to dominate the largest market share. Cognitive process automation helps customers with requests like credit assessments, loan approvals, and account openings that can be processed accurately and more quickly. Moreover, by reducing processing times and increasing data accuracy automation improves the overall customer experience, which raises customer satisfaction levels. The rising utilization of cognitive process automation to prevent and detect fraud in financial transactions fuels the segment's growth.
The market is divided into five categories based on application: biometrics, machine learning, pattern identification, optical character recognition, natural language processing, and others. The machine learning segment is likely to maintain its dominance during the forecast period. Machine learning is used by cognitive process automation to derive, process, and analyze insights from structured and unstructured data, make informed decisions based on data analysis, and allow businesses to scale their operations. Furthermore, intelligent document processing automates the analysis and extraction of data from unstructured documents like financial statements, invoices, and contracts by using machine learning.
The market is divided into eight categories based on industry vertical: BFSI, retail & e-commerce, IT & telecommunication, manufacturing, transportation & logistics, media & entertainment, energy & utilities, healthcare & life sciences, and others. The BFSI segment is attributed to holding the largest revenue share in the market. Cognitive process automation helps the BFSI industry enhance fraud detection and risk management. Moreover, the BFSI sector provides significant opportunities for improving customer experiences, mitigating risks, and increasing operational effectiveness through cognitive process automation. Furthermore, by using cognitive process automation banks and other financial institutions can streamline and automate customer on boarding procedures.
Geographically, this market is widespread into the regions of North America, Latin America, Europe, Asia Pacific, and the Middle East and Africa. These regions are further divided as per the nations bringing business.
In the cognitive process automation market, rapid technological advancements have emerged as the key trend gaining popularity. In the cognitive process automation market, numerous companies are developing innovative products to strengthen their market position. For instance, in May 2021, Kanverse.ai, a cognitive automation company announced the launch of a Next-Generation Cognitive Automation Platform and launched Intelligent Document Processing Product (IDP). Additionally, it combines AI with Optical Character Recognition (OCR), Business rule framework, and Automation to offer an end-to-end product that digitizes document processing for enterprises from classification, ingestion, extraction, and validation to filing.
For instance, in December 2021, Brillio acquired Cedrus Digital New York-based cloud consulting and digital transformation firm. In addition, to their strategic relationships in North America, this acquisition significantly strengthens Brillio's product & platform engineering, cloud security and digital infrastructure capabilities, and data analytics engineering, increasing Brillio's near-shore presence and proximity.