Cognitive Automation Market size was over USD 12.2 billion in 2023 and is projected to reach USD 41.06 billion by the end of 2036, expanding at a CAGR of 12.1% during the forecast period, i.e., 2024-2036. In 2024, the industry size of cognitive automation is assessed at USD 13.4 billion.
Partially or fully cognitive automated machines are gaining traction in electronics and automotive manufacturing, metal fabrication, food and beverage industry, warehousing, and logistics to improve productivity while relieving human workers from life-threatening or mundane tasks. Cognitive automation robots are primarily used in production lines for assembling basic components and metal-cutting activities. The commercial demand for smart and more interactive machines has led to the development of collaborative robots that work with humans in shared environments. Cognitive automation is projected to bridge the labor shortage in heavy-duty industries and commercial spaces.
Growth Drivers
Challenges
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Base Year |
2023 |
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Forecast Year |
2024-2036 |
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CAGR |
12.1% |
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Base Year Market Size (2023) |
USD 12.2 billion |
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Forecast Year Market Size (2036) |
USD 41.06 billion |
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Regional Scope |
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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:
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Type |
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End use |
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Application |
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North America Market Statistics
North America cognitive automation market is anticipated to hold the highest revenue share, accounting for 42% of the revenue in the forecast period. The North America cognitive process automation market is witnessing substantial growth as a result of the increasing usage of artificial intelligence technology and the need for enterprises to automate cognitive functions. Intelligent virtual assistants, such as those employed for customer care and sales assistance, are commonly utilized for interactions in North America. These virtual assistants utilize cognitive process automation to understand and address client inquiries, do activities, and improve customer experiences.
The U.S. in 2023, held the largest revenue share owing to the growth of the automobile sector. Furthermore, the presence of prominent players including Blue Prism, IBM, IPsoft, and Kryon Systems is fostering market growth in the U.S.
The Canada market is driven by the rapid scaling of robotics & cognitive automation (R&CA) capabilities and ongoing investment in exponential technologies such as ML and chatbots. For instance, in November 2022, Sanctuary Cognitive Systems received USD 30 million in SIF funding from the Government of Canada to support its mission of building automation to address labor shortages. It is expected to help position Canada in the global knowledge-based economy.
APAC Market Analysis
Asia Pacific cognitive automation market is predicted to experience the highest CAGR of 38% during the forecast period, owing to rapid digitization and a surge in interest in automation and artificial intelligence (AI) technology. Organizations are implementing cognitive process automation to enhance productivity, save expenses, and optimize operations. China, India, Japan, and South Korea, play a pivotal role by actively investing in AI research, development, and innovation support. As a result, the market for market is poised for significant growth.
The prominent players in the India cognitive automation market are keen on introducing intelligent process automation (IPA), digital process automation (DPA), intelligent business process automation, and hyper-automation to fill gaps between programming interface tools and RPA, in tandem with low-code applications. TCS’ Cognitive Automation Platform has widespread adoption in front- and back offices, particularly catering to the BFSI sector. The domestic launch of advanced solutions by leveraging pre-trained models and configurations is aiding to rapid market expansion.
Cognitive automation market in China held a significant revenue share in 2023. The number of new units of automated robots installed annually reached 290,258 in 2022. To cater to the ever-changing demands of this thriving market, both local and global manufacturers of robots have set up production facilities in China and consistently expanded their production capabilities. The average annual growth rate of robot installations from 2017 to 2022 is 13%.
The number of cognitive automated robot installations in Japan increased by 9% to reach 50,413 units, surpassing the pre-pandemic level of 49,908 units recorded in 2019. Japan holds the dominant position in the global robot manufacturing industry, accounting for 46% of the total global robot production.
Automation is becoming increasingly prevalent in various fields, ranging from home automation to industrial automation, and even in the form of virtual assistants like "Alexa" and "Google Assistant". This trend indicates that automation will continue to shape the future. Moreover, the cognitive automation market is primarily dominated by prominent industry players who are gaining momentum in the marketplace via the implementation of various strategies, such as mergers and acquisitions.
Author Credits: Richa Gupta
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