Cognitive Automation Market Analysis

Type (Robotic Process Automation, Intelligent Automation)

By 2036, the robotic process automation segment is projected to hold 68% of the global cognitive automation market share by 2036. The segment growth is predicted to be driven by various factors, such as the increasing demand to optimize operations for higher efficiency, and the integration of sophisticated technologies, to transform business processes. Robotic process automation (RPA) is highly efficient in automating monotonous, manual processes, such as data entry, form completion, validation, extraction, and simple computations. RPA bots replicate human interactions with user interfaces, allowing them to perform jobs with greater speed and precision.

In addition, enterprises can streamline intricate decision-making processes, analyze data, and manage unstructured data more efficiently by integrating RPA with cognitive capabilities. As an illustration, NASA has deployed an automated bot that generates procurement requests for the agency without requiring human intervention. This automates a monotonous and unproductive activity, enabling NASA procurement specialists to dedicate their attention to more significant tasks.

End use (BFSI, Pharma & Healthcare, Retail & Consumer Goods, Information Technology (IT) & Telecom)

In the projected timeframe, the BFSI segment in the cognitive automation market is anticipated to account for 25% of the revenue share. Cognitive process automation in the Banking, financial services, and insurance sectors improves risk management and fraud detection. AI algorithms have the capability to analyze vast quantities of data, equipping them to identify patterns and notify consumers of possible scams. The BFSI sector presents substantial prospects for enhancing operational efficiency, and client experiences and reducing risks through cognitive process automation.

WorkFusion estimates that over 60% of the manual tasks involved in the customer onboarding process at a bank can be automated to some extent. Approximately half of the reduction in work can be achieved by incorporating machine learning, digitization, and analytics in addition to robotic process automation (RPA).

Application (Machine learning, Natural language processing, biometrics)

The machine learning segment is expected to hold 28% share of the global cognitive automation market by 2036. Cognitive process automation employs machine learning algorithms to efficiently handle, examine, and extract valuable information from both organized and unorganized data. This empowers businesses to expand their operations and make well-informed choices by utilizing data analysis.

Furthermore, intelligent document processing employs machine learning techniques to automate the retrieval and examination of information from unorganized documents such as financial accounts, contracts, and invoices. Several businesses are employing cognitive process automation to implement machine learning in several industries. In 2018, NARA introduced its chatbot intending to address inquiries from the public and achieve the agency's strategic aim of connecting with customers.

Our in-depth analysis of the cognitive automation market includes the following segments: