市場調查報告書
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1519664
2024-2032 年按技術、部署類型、企業規模、垂直產業和地區分類的認知運算市場報告Cognitive Computing Market Report by Technology, Deployment Type, Enterprise Size, Industry Vertical, and Region 2024-2032 |
IMARC Group年全球認知運算市場規模達410億美元。由於醫療保健領域的廣泛使用、人工智慧 (AI) 和機器學習 (ML) 技術的不斷進步,以及預測分析在風險評估和資源分配方面的利用率不斷提高,該市場正在經歷穩定成長。
市場成長與規模:近年來,在人工智慧和機器學習技術日益普及的推動下,全球認知運算市場穩步成長。
技術進步:更複雜的自然語言處理 (NLP) 演算法和改進的神經網路的開發不斷增加。此外,量子運算正在增強認知系統的能力。
產業應用:認知運算在各產業都有應用,包括醫療保健、金融、零售和製造業。在醫療保健領域,它有助於診斷和治療建議,並增強 BFSI 領域的詐欺檢測和風險評估。
地理趨勢:北美持續主導全球認知運算市場,在市場收入中佔據很大佔有率。儘管如此,由於對人工智慧和數位轉型計劃的投資不斷增加,亞太地區成為成長最快的新興市場之一。
競爭格局:市場領導者正在提供全面的認知解決方案並投資於研發 (R&D) 活動。
挑戰與機會:日益成長的資料隱私問題以及認知運算系統中對強大網路安全措施的需求不斷成長是市場的主要挑戰。然而,自動駕駛汽車和個人化行銷等不斷擴大的應用預計將克服這些挑戰並提供良好的市場前景。
未來展望:全球認知運算市場的未來似乎充滿希望,由於人工智慧的進步和對數據驅動洞察力的需求不斷增加,預計該市場將持續成長。此外,科技巨頭和新創公司之間不斷加強的合作可能會推動創新並促進市場成長。
人工智慧 (AI) 和機器學習 (ML) 的進步
人工智慧(AI)和機器學習(ML)技術的不斷進步是促進市場成長的主要因素之一。此外,這些技術的整合使認知運算系統能夠處理大量資料、識別模式並做出決策或建議,而無需明確程式設計。這種演變顯著提高了認知運算解決方案的準確性和速度,使它們更有效率和可靠。 NLP 是人工智慧的一個子集,它使機器能夠理解人類語言並與之互動。這導致了聊天機器人、虛擬助理和情緒分析工具的發展,這些工具在客戶服務、內容生成和市場研究中都有應用。此外,認知運算利用人工智慧和機器學習支援的預測分析來預測未來趨勢、識別潛在問題並最佳化決策。與此一致的是,預測分析在風險評估和資源分配中的使用不斷增加,正在加強市場的成長。
對數據驅動洞察力的需求不斷成長
對數據驅動的見解不斷成長的需求提供了有利的市場前景。此外,企業越來越意識到資料在做出明智決策、提高效率和獲得競爭優勢方面的重要性,這提供了有利的市場前景。來自社交媒體、物聯網 (IoT) 設備和感測器等不同來源的資料呈指數級成長,推動了對認知運算等先進工具的需求,以提取有意義的見解。這些見解可用於市場分析、客戶區隔和個人化行銷策略。同時,認知計算系統在醫療保健領域的廣泛使用來分析患者記錄、醫學影像和臨床資料,以協助疾病診斷、治療計劃和藥物發現,正在加強市場的成長。此外,BFSI 領域擴大採用認知運算解決方案來分析市場趨勢、檢測交易異常和管理風險,這正在刺激市場成長。
特定產業的應用與採用
由於認知運算能夠應對特定挑戰並提供量身定做的解決方案,因此其在各行業的應用不斷擴大,正在支持市場的成長。零售業擴大使用認知運算,為市場創造了積極的前景。認知運算為推薦引擎提供支持,增強顧客的購物體驗。此外,這些系統透過分析瀏覽和購買歷史記錄來推薦產品,從而提高銷售額和客戶滿意度。與此一致的是,認知運算在製造業中的廣泛採用正在對市場產生正面影響。認知運算透過預測設備維護需求、最佳化生產計劃和加強品質控制來改善製造流程,從而減少停機時間並節省成本。除此之外,能源產業也依賴認知運算來最佳化發電、預測設備故障和管理電網運作。這有助於提高能源供應的效率和可靠性。
The global cognitive computing market size reached US$ 41.0 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 254.8 Billion by 2032, exhibiting a growth rate (CAGR) of 21.8% during 2024-2032. The market is experiencing steady growth driven by the widespread use in the healthcare sector, continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies, and the rising utilization of predictive analytics for risk assessment and resource allocation.
Market Growth and Size: The global cognitive computing market has witnessed steady growth in recent years, driven by the increasing adoption of AI and ML technologies.
Technological Advancements: There is a rise in the development of more sophisticated natural language processing (NLP) algorithms and improved neural networks. Additionally, quantum computing is enhancing the capabilities of cognitive systems.
Industry Applications: Cognitive computing finds applications in various industries, including healthcare, finance, retail, and manufacturing. In healthcare, it aids in diagnosis and treatment recommendations, and enhances fraud detection and risk assessment in the BFSI sector.
Geographical Trends: North America continues to dominate the global cognitive computing market, with a significant share of the market revenue. Nonetheless, Asia-Pacific is one of the fastest-emerging markets on account of the increasing investments in AI and digital transformation initiatives.
Competitive Landscape: Leading players in the market are offering comprehensive cognitive solutions and investing in research and development (R&D) activities.
Challenges and Opportunities: The growing data privacy concerns and the rising need for robust cybersecurity measures in cognitive computing systems are the major challenges of the market. However, the expanding applications, such as in autonomous vehicles and personalized marketing, are projected to overcome these challenges and offer a favorable market outlook.
Future Outlook: The future of the global cognitive computing market appears promising, with continued growth expected due to advancements in AI and increasing demand for data-driven insights. In addition, the rising collaborations between technology giants and startups are likely to drive innovation and contribute to the market growth.
Advancements in Artificial Intelligence (AI) and Machine Learning (ML)
Continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies represent one of the primary factors facilitating the market growth. In addition, the integration of these technologies enables cognitive computing systems to process vast amounts of data, recognize patterns, and make decisions or recommendations without explicit programming. This evolution is significantly the accuracy and speed of cognitive computing solutions, making them more efficient and reliable. NLP, a subset of AI, enables machines to understand and interact with human language. This is leading to the development of chatbots, virtual assistants, and sentiment analysis tools, which find applications in customer service, content generation, and market research. In addition, cognitive computing leverages predictive analytics powered by AI and ML to forecast future trends, identify potential issues, and optimize decision-making. In line with this, the rising utilization of predictive analytics for risk assessment and resource allocation is strengthening the growth of the market.
Growing Demand for Data-driven Insights
The escalating demand for data-driven insights is offering a favorable market outlook. In addition, the increasing awareness among businesses about the importance of data in making informed decisions, improving efficiency, and gaining a competitive edge is offering a favorable market outlook. The exponential growth of data from diverse sources, including social media, the Internet of Things (IoT) devices, and sensors, is driving the need for advanced tools like cognitive computing to extract meaningful insights. These insights can be used for market analysis, customer segmentation, and personalized marketing strategies. Along with this, the widespread use of cognitive computing systems in the healthcare sector to analyze patient records, medical images, and clinical data to assist in disease diagnosis, treatment planning, and drug discovery is strengthening the growth of the market. Furthermore, the rising adoption of cognitive computing solutions in the BFSI sector to analyze market trends, detect anomalies in transactions, and manage risk is stimulating the market growth.
Industry-specific Applications and Adoption
The expanding applications of cognitive computing in various industries due to its ability to address specific challenges and deliver tailored solutions are supporting the growth of the market. The increasing use of cognitive computing in the retail sector is creating a positive outlook for the market. Cognitive computing powers recommendation engines that enhance the shopping experience for customers. In addition, these systems suggest products by analyzing browsing and purchase history, leading to higher sales and customer satisfaction. In line with this, the widespread adoption of cognitive computing in the manufacturing industry is influencing the market positively. Cognitive computing improves manufacturing processes by predicting equipment maintenance needs, optimizing production schedules, and enhancing quality control, which results in reduced downtime and cost savings. Apart from this, the energy sector is relying on cognitive computing to optimize power generation, predict equipment failures, and manage grid operations. This contributes to increased efficiency and reliability of energy supply.
IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global, regional, and country levels for 2024-2032. Our report has categorized the market based on technology, deployment type, enterprise size, and industry vertical.
Natural Language Processing
Machine Learning
Automated Reasoning
Others
Natural language processing accounts for the majority of the market share
The report has provided a detailed breakup and analysis of the market based on the technology. This includes natural language processing, machine learning, automated reasoning, and others. According to the report, natural language processing represented the largest segment.
Natural language processing (NLP) empowers machines to understand, interpret, and generate human language, facilitating seamless communication between humans and computers. Its applications span a wide spectrum, ranging from chatbots that engage people in natural conversations to sentiment analysis tools that gauge public opinions and feedback. Furthermore, NLP underpins content generation and automated translation services, which drives its demand across the globe.
Machine learning (ML) constitutes a substantial portion of the cognitive computing market and continues to grow in importance. This technology empowers systems to learn from data, adapt, and make predictions or recommendations autonomously. In fields like finance, healthcare, and e-commerce, ML algorithms drive personalized recommendations, fraud detection, and predictive analytics. Its versatility and ability to uncover hidden patterns within vast datasets make it an asset.
Automated reasoning focuses on logical inference and problem-solving, enabling expert systems and decision support. It finds numerous applications in medical diagnoses or complex logistical planning. In addition, it contributes valuable capabilities to cognitive computing by ensuring the reliability and accuracy of automated decisions.
On-premises
Cloud-based
Cloud-based holds the largest share in the industry
A detailed breakup and analysis of the market based on the deployment type have also been provided in the report. This includes on-premises and cloud-based. According to the report, cloud-based accounted for the largest market share.
On-premises deployment of cognitive computing solutions remains a significant choice for businesses, particularly those with stringent data security and compliance requirements. Organizations that opt for on-premises solutions have full control over their infrastructure and data, allowing them to customize and fine-tune cognitive systems to their specific needs. In addition, on-premises solutions are widely used in healthcare, finance, and government sectors for enhanced safety and data privacy.
Cloud-based deployment has gained immense popularity in the cognitive computing market due to its scalability, flexibility, and cost-effectiveness. It offers reduced infrastructure costs, rapid scalability, and access to cutting-edge cognitive technologies. Apart from this, cloud solutions also facilitate remote collaboration and data sharing, making them well-suited for businesses with a distributed workforce. They are especially favored by startups and smaller enterprises looking to quickly adopt cognitive computing capabilities without significant upfront investments.
Small and Medium-sized Enterprises
Large Enterprises
Large enterprises represent the leading market segment
The report has provided a detailed breakup and analysis of the market based on the enterprise size. This includes small and medium-sized enterprises and large enterprises. According to the report, large enterprises represented the largest segment.
Large enterprises harness cognitive technologies to optimize various aspects of their operations, from supply chain management and customer relationship management to human resources and financial analysis. Large enterprises leverage big data analytics and machine learning to gain actionable insights from vast datasets, enabling them to make informed decisions and drive innovation. Additionally, they invest in custom-built cognitive solutions tailored to their specific needs.
Small and medium-sized enterprises are increasingly recognizing the value of cognitive computing in improving efficiency and competitiveness. Cognitive technologies empower SMEs to automate repetitive tasks, analyze customer data for personalized marketing, and enhance decision-making processes. The affordability of cloud-based cognitive solutions has made these technologies accessible to SMEs without the need for extensive infrastructure investments.
Healthcare
BFSI
Retail
Government
IT and Telecom
Energy and Power
Others
Healthcare accounts for the majority of the market share
A detailed breakup and analysis of the market based on the industry vertical have also been provided in the report. This includes healthcare, BFSI, retail, government, IT and telecom, energy and power, and others. According to the report, healthcare holds the largest market share.
Cognitive computing technologies are widely used in the healthcare sector to enable advanced diagnostic systems, personalized treatment recommendations, and drug discovery processes. These innovations are improving patient outcomes, reducing medical errors, and optimizing healthcare operations. Furthermore, the rising focus of the industry on offering data-driven decision-making and the delivery of more effective and efficient healthcare services is facilitating the market growth.
The BFSI sector holds a significant share in the cognitive computing market, driven by the need for enhanced risk assessment, fraud detection, and customer service. Cognitive computing systems in this industry are used to analyze vast volumes of financial data, predict market trends, and automate routine tasks like customer inquiries and document processing. Additionally, they aid in optimizing investment portfolios and ensuring regulatory compliance.
The retail industry has embraced cognitive computing to provide personalized shopping experiences, optimize supply chain management, and enhance customer engagement. Cognitive systems analyze consumer behavior and preferences to offer tailored product recommendations, making online and in-store shopping more efficient and enjoyable.
Government agencies are increasingly adopting cognitive computing to improve public services, enhance cybersecurity, and streamline administrative processes. Cognitive systems assist in data analysis for policy-making, aid in threat detection and prevention, and automate routine tasks, allowing government employees to focus on higher-value activities.
The IT and telecom industry leverages cognitive computing to enhance network management, customer support, and data security. Cognitive systems analyze network performance, detect anomalies, and predict potential issues, leading to improved service quality. In customer support, chatbots powered by cognitive technologies offer quick and efficient assistance.
In the energy and power sector, cognitive computing contributes to more efficient energy management, predictive maintenance of power plants, and grid optimization. These technologies analyze vast datasets from sensors and equipment, helping prevent downtime and reduce energy waste. Cognitive systems also assist in forecasting energy demand and optimizing the distribution of renewable energy sources, aligning with sustainability goals and cost-effectiveness.
North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
North America leads the market, accounting for the largest cognitive computing market share
The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia-Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.
North America continues to lead the cognitive computing market due to its advanced technological infrastructure and substantial investments in artificial intelligence (AI) and cognitive technologies. The United States, being a global technology hub, plays a pivotal role in driving innovation and adoption. Additionally, key industries in the U.S., such as healthcare, finance, and manufacturing, heavily rely on cognitive computing for improving operational efficiency and decision-making.
The Asia-Pacific region is experiencing rapid growth in the cognitive computing market. China and Japan are standout leaders, driving innovation in AI and cognitive technologies. The continuous government support and robust tech ecosystem in China are propelling it to the forefront, with applications spanning manufacturing, healthcare, and finance. Additionally, the software development prowess and the increasing adoption of cognitive computing customer service and data analytics are driving the regional market. South Korea and Australia continue to invest heavily in AI research and development, while Indonesia is emerging as a market with growth potential across diverse sectors.
Europe represents a mature but steadily growing market for cognitive computing. Germany and France excel in manufacturing and aerospace, employing cognitive solutions to enhance productivity and quality control. The United Kingdom is a leader, particularly in financial services, where cognitive computing helps manage risk and improve customer experiences. Italy and Spain are expanding their use of cognitive computing in healthcare and retail.
Latin America is gradually embracing cognitive computing, with Brazil taking the lead, particularly in agriculture and finance. Furthermore, the growing tech sector and government initiatives in Brazil are leading to increased adoption of cognitive solutions. Mexico is also incorporating cognitive computing in manufacturing and logistics to enhance operational efficiency.
The Middle East and Africa are at an early stage of cognitive computing adoption. The UAE and South Africa are pioneers, using cognitive computing in financial services and healthcare to improve decision-making and customer experiences. In addition, as businesses and governments recognize the value of cognitive computing, opportunities across diverse industries are expected to emerge gradually, driving market expansion in this region.
The key players in the market are continually enhancing their cognitive computing platforms and services. They invest heavily in research and development to improve natural language processing (NLP), machine learning, and automated reasoning capabilities. Additionally, they are tailoring their offerings to meet the unique needs of sectors such as healthcare, finance, retail, and more. They are also collaborating with industry experts to develop specialized solutions, enabling customers to derive maximum value from their cognitive systems. Moreover, the key players are promoting cloud-based cognitive services to make them more accessible and scalable. They are expanding their cloud infrastructure globally, enabling businesses of all sizes to leverage cognitive computing without the need for significant hardware investments.
Acuiti Group
Cisco Systems Inc.
Enterra Solutions LLC
Expert .AI
e-Zest Solutions Ltd
Google LLC (Alphabet Inc.)
International Business Machines Corporation
Marlabs LLC
Microsoft Corporation
Red Skios Ltd.
Sas Institute Inc.
Tata Consultancy Services Ltd.
Vantage Labs LLC
Virtusa Corporation
(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)
September 15, 2021: Enterra Solutions, LLC, a leading provider of Autonomous Decision Sciences(TM) technologies, announced the opening of a new office in Cambridge, Massachusetts. The new office located in Kendall Square will expand the business footprint and position of the company in a worldwide hub for technology innovation as it continues to drive development to the advanced artificial intelligence offerings that bridge the commercial sector, academia, and governing agencies.
March 14, 2023: Tata Consultancy Services Ltd. announced the launch of its 5G-enabled solution, TCS Cognitive Plant Operations Adviser for the Microsoft Azure Private Mobile Edge Computing (PMEC) platform, to help industries like manufacturing, oil and gas, consumer packaged goods, and pharmaceuticals transform production, harnessing AI and machine learning to make it more intelligent, agile and resilient.
November 29, 2023: Sas Institute Inc. a global leader in artificial intelligence (AI) and analytics, announced today that it has signed a strategic collaboration agreement (SCA) with Amazon Web Services (AWS) to help customers extract maximum value and performance from their data in the cloud.