Global cognitive automation market is estimated to be valued at USD 11.03 Billion in 2024 and is expected to reach USD 49.86 Billion by 2031, exhibiting a compound annual growth rate (CAGR) of 24% from 2024 to 2031.
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Global cognitive automation market growth is driven by increasing demand for automation across industries to enhance business process efficiency. Rapid technology advancement such as artificial intelligence, machine learning and natural language processing has enabled the development of intelligent software solutions that can automate routine tasks. Various enterprises are implementing cognitive automation to reduce labor costs and human errors. Moreover, growing need to analyze huge amounts of data efficiently can boost adoption of cognitive automation. Advancements in robotic technology can also integrate cognitive capabilities in robots, thus, driving the market growth in the near future.
Increasing demand for process automation and digital transformation
The pressures of digital transformation compel organizations across the globe to automate respective tasks and processes. Companies are recognizing the benefits that cognitive automation solutions can provide to increase efficiencies, improve customer experiences and fuel innovation. By leveraging technologies like robotic process automation, natural language processing and machine learning, cognitive tools are able to understand structured and unstructured data and use this to automate workflows. This allows previously manual tasks to be performed digitally without human intervention.
The ability of cognitive automation to work alongside humans rather than replace them can boost its adoption. Systems are designed to take over straightforward, rules-based activities and process high volumes of structured data, freeing up employee time and resources. Workers can focus on more complex and strategic responsibilities that require human judgment, problem-solving capabilities and creative thinking. In many sectors such as banking, insurance and telecommunications that rely on heavy transaction processing, cognitive automation is positively impacting productivity, turnaround times and customer satisfaction levels.
Organizations across industry verticals are facing pressures to modernize legacy systems and streamline disjointed processes that have accumulated over time. The flexibility and scalability of cognitive platforms allows companies to digitally transform at their own pace, starting with automating pieces of existing workflows end-to-end before expanding the scope of automation. This staged approach helps minimize disruption while maximizing return on investment. Forward-thinking businesses view cognitive automation not just as a cost-cutting exercise but rather as an opportunity to innovate new digital products, services and experiences for the digital native generation.
For instance, In June 2021, FPT Software, a global technology and IT services provider from Vietnam, announced its partnership with Sitecore, a leading digital experience software supplier in the United States. This collaboration aims to enhance Sitecore's digital marketing services for a wider range of enterprises in Japan by leveraging automated processes, digital transformation, and low-code solutions, ultimately benefiting numerous Japanese businesses.
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Growing adoption of artificial intelligence (AI) and machine learning (ML) technologies
Advancements in artificial intelligence, machine learning and related technologies have tremendously accelerated in recent years. This rapid innovation boosts expanding use cases for cognitive automation across industry verticals. AI and ML algorithms that previously required massive training datasets and computational power can now achieve high degrees of accuracy with smaller samples due to improvements in processing speeds, storage capacities and new deep learning techniques.
Vendors are harnessing these AI breakthroughs to develop new categories of cognitive automation software. Advanced natural language processing unlocks automation opportunities from various unstructured data sources like emails, documents and calls. Computer vision enabled by convolutional neural networks empower systems with visual recognition and object detection skills. Integration of knowledge graphs allows cognitive agents to store and understand relationships between entities for contextual responses.
Large technology companies are investing heavily in AI research and its real-world applications through acquisitions and in-house development. These are using their vast financial resources and innovative cultures to remain at the forefront of next generation ML technologies. Software providers seek to partner with or obtain these emerging capabilities to infuse cognitive automation platforms and keep them powered by the latest AI. Governments worldwide are also launching initiatives, programs and regulations to support AI advancement and ensure its safe, fair and responsible use.
Key Takeaways from Analyst:
With rising need for organizations to improve efficiency, reduce costs, and optimize business processes, there has been increase in use of cognitive technologies that can automate routine tasks. North America currently dominates the cognitive automation market and Asia Pacific emerges as the fastest growing regional market.
As organizations across all industries seek to streamline operations through automation, there will be immense opportunities for cognitive tools that can manage high volumes of structured and unstructured data, identify patterns, and perform human-like decision making. Within manufacturing, cognitive process automation holds potential to drive productivity. The healthcare sector is another promising vertical as cognitive technologies can improve care quality and lower costs.
Integration challenges and concerns around job disruption can hamper the market growth. Successful adoption depend on how easily cognitive solutions can be deployed within existing IT ecosystems. Retraining the workforce and redesigning job roles will be critical to mitigate fears around technology replacing human jobs. Data privacy and regulatory compliance are other issues that vendors will need to address proactively.
As artificial intelligence advances, enabling machines to think and act more intuitively, the cognitive automation space will witness growth in the future.
Market Challenges: High implementation costs of cognitive automation solutions
Global cognitive automation market growth can be hampered due to high implementation costs associated with cognitive automation solutions. Developing advanced cognitive capabilities requires massive investments in research and development. Companies offering cognitive automation products and services need to employ teams of skilled AI engineers, data scientists, and other technical experts to build and maintain their cognitive platforms. These R&D costs are then passed on to customers. Integrating cognitive solutions with existing IT infrastructure of organizations also involves significant customization and support expenses. For many small and medium enterprises, the total cost of ownership of cognitive technologies acts as a barrier for adoption. While the long term savings potential of cognitive automation is huge, its upfront capital expenditure requirements are prohibitive for cost-sensitive businesses. This high variable cost structure poses a notable challenge for widespread commercialization of the cognitive automation in the near future.
Market Opportunities: Integration of Cognitive Automation with Emerging Technologies like IoT, robotics and blockchain
Integration of these solutions with other adjacent emerging technologies like IoT, robotics, and blockchain can offer market growth opportunities. As AI capabilities enhance to take inputs from a variety of connected devices and sensors, cognitive systems can leverage real-time data streams from IoT networks to automate decision making for industrial operations. Cognitive functionalities like computer vision, speech recognition and predictive analytics can empower robotics with more intelligent autonomy. The convergence of cognitive computing and blockchain holds promise for self-learning, transparent applications spanning finance, supply chain and healthcare. Seamless collaboration of cognitive platforms with IoT, robotics and distributed ledgers can spawn innovative automation use cases and significantly expand the scope of the market. With technology giants investing heavily in these combinational solutions, their market proliferation can drive major revenues for cognitive automation vendors.
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Insights, By Component - Solutions Segment Driving Growth through Expanding Functionalities
In terms of component, solutions segment is estimated to contribute the highest market share of 62.6% in 2024, owning to its extensive capabilities. Cognitive automation solutions have progressed significantly by adding new functionalities to cater to changing business requirements. Leading solution providers are focusing on enriching their platform's skillsets to enable automation of highly analytical and complex tasks. For example, advanced solutions now support multimedia data formats for applications like automated social media engagement and customer service chatbots. These also offer enhanced analytical functionalities for fraud detection and risk management. Integration of new digital skills allow organizations to derive more value from their automation projects. The wide range of functionalities available further makes solutions a preferred choice over traditional services. Continuous upgrades to address the dynamic needs of industries can drive the segment growth.
Insights, By Technology - Machine Learning Segment Enhanced Analytics Driving Progress
In terms of technology, machine learning segment is estimated to contribute the highest market share of 38.4% in 2024, owing to its invaluable role in data processing. Machine learning algorithms have revolutionized data analytics capabilities by enabling computers to learn from large volumes of structured and unstructured data. These are uniquely suited to identify complex patterns and hidden insights. Growing reliance on data-driven decision making across sectors can boost deployment of ML-powered cognitive automation technologies. Prominent applications include predictive maintenance, personalized marketing, medical diagnostics, and stock market analysis. Advancements in deep learning and neural networks have also expanded the scope of predictive analytics. Improvements in ML techniques will boost their usage for an ever-widening range of cognitive tasks.
Insights By End User - Banking, Financial Services, And Insurance (BFSI) Segment Tapping Financial Opportunities
In terms of end user, banking, financial services, and insurance (BFSI) segment is estimated to contribute the highest market share of 53.2% in 2024, owing to extensive automation needs. The BFSI industry handles immense amounts of customer transactions and financial data on a daily basis. This presents both opportunities as well as challenges in maintaining efficiency, managing risks, and improving customer experience. Cognitive automation technologies are helping BFSI players to derive valuable insights from such voluminous data sources. Solutions like intelligent chatbots, predictive fraud detection systems, and robo-advisors are reducing costs while enhancing service quality. Regulatory compliance activities also lend themselves well to automation. Furthermore, technology adoption in BFSI usually occurs at an advanced level as compared to other sectors. Considering these factors, the BFSI segment will likely remain the front runner in driving the cognitive automation market. Its unabated digital transformation will boost new deployments.
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North America dominates the cognitive automation market with an estimated market share of 40.1% in 2024, due to strong presence of technology giants and early adopters of emerging technologies in the U.S. and Canada. American companies have taken a lead in developing and applying cognitive automation solutions across industries such as healthcare, banking, retail and manufacturing. With higher technology adoption and experimentation with concepts like Industry 4.0, numerous startups are also entering this space with innovative solutions.
Strong in-house R&D capabilities of technology companies and generous funding for AI research from government organizations supports the development of new tools. There has been huge awareness and investment in cognitive automation from enterprises in this region. Industries are keen on implementing cognitive process automation to gain efficiencies and enhance customer experience. This has created a thriving ecosystem for vendors. The region also attracts huge foreign direct investments and business expansion plans of global cognitive automation players. This makes North America an attractive market for long term growth and partnership opportunities.
Asia Pacific region has emerged as the fastest growing regional market for cognitive automation. Countries like China, India, Japan and South Korea are actively experimenting and applying cognitive technologies. Governments in APAC are promoting initiatives that encourage research and implementation of emerging technologies. This includes schemes for setting up of centers of excellence and tax incentives.
Enterprises are keen on leveraging cognitive automation to improve productivity and expand operations. Industries like manufacturing, IT and business services that are major revenue contributors are at the forefront of adopting new technologies. Prominent global technology vendors and startups have established their Asia research and development centers in recent years. This increases focus on developing solutions customized for the Asia Pacific market. With strong economic outlook and government support, APAC offers huge market potential and is expected to witness growth in the near future.
Cognitive Automation Market Report Coverage
Report Coverage | Details | ||
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Base Year: | 2023 | Market Size in 2024: | US$ 11.03 Bn |
Historical Data for: | 2019 to 2023 | Forecast Period: | 2024 to 2031 |
Forecast Period 2024 to 2031 CAGR: | 24% | 2031 Value Projection: | US$ 49.86 Bn |
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Segments covered: |
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Companies covered: |
Accenture, Automation Anywhere, Blue Prism, Brain Corp, Cognizant, DataRobot, Google Cloud (Alphabet Inc.), IBM, Kofax, Microsoft, NICE Systems, Pegasystems, Salesforce, SAP, and UiPath |
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Growth Drivers: |
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Restraints & Challenges: |
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*Definition: Global cognitive automation market refers to the use of artificial intelligence, machine learning and natural language processing technologies to automate workplace tasks and processes. It allows organizations to leverage cognitive technologies to gain insights from large, complex data sets. Cognitive automation mimics human thought processes to perform tasks like analyzing text, visual content and spoken words.
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About Author
Suraj Bhanudas Jagtap
Suraj Bhanudas Jagtap is a seasoned Senior Management Consultant with over 7 years of experience. He has served Fortune 500 companies and startups, helping clients with cross broader expansion and market entry access strategies. He has played significant role in offering strategic viewpoints and actionable insights for various client’s projects including demand analysis, and competitive analysis, identifying right channel partner among others.
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