The size of the global cognitive operations market was worth USD 14.18 billion in 2023. The global market is predicted to reach USD 17.64 billion in 2024 and USD 101.17 billion in 2032, growing at a CAGR of 24.40% during the forecast period.
Cognitive operations allow organizations to automatically create predictive models by analyzing data collected from various IT tools and devices, optimizing IT operations, automating repetitive and manual tasks, and proactively responding to problems in real time. Cognitive operations use artificial intelligence to obtain information about potential problems through cognitive solutions in less time. Security analysis applications are expected to experience the fastest growth rate over the forecast period. Security analysis applications allow organizations to identify emerging security threats using evidence-based information. The demand for these applications will increase among companies to respond quickly to emerging threats.
Therefore, companies focus mainly on improving system performance and availability. Organizations are moving their core business applications to the cloud to maximize its benefits. The cloud deployment option offers several advantages, such as scalability, low cost, and ease of deployment. Additionally, organizations are migrating to the cloud due to increasing data storage requirements.
Cognitive services are strengthening the telecommunications industry to improve its core business tasks by automating assistive robots that interpret natural language and translate text. Ultimately, this helps transform the telecommunications administrative offices into a competent customer service team. Smart grid operations, also recognized as a cognitive network operations center, use artificial intelligence (AI), machine learning (ML), and advanced analytics to drive autonomous, self-healing, and self-repairing. To increase scalability, activity, and commercial performance, telecommunications operators are developing cognitive network operating centers based on a three-level framework: a cognitive computing engine with AI and ML, Scalable Data Infrastructure, intelligent operating applications, workflows, and dashboards.
Most organizations face problems related to a lack of analytical talent and experience when developing, implementing, and managing AI-based systems in IT operations. Organizations mainly face concerns about the lack of qualified employees and analytical talent. Machine learning systems are becoming crucial to analyze data from IT operations. Building machine learning models is complex and requires adequate skills, experience, and training. However, a lack of qualified professionals may hinder future market growth. On the other hand, a substantial market opportunity is emerging for gamers, primarily due to increasing demand to reduce operating costs and improve customer experience in various user industries.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2032 |
Base Year |
2023 |
Forecast Period |
2024 to 2032 |
CAGR |
24.4% |
Segments Covered |
By Component, Application, Organization Size, Deployment Type, Vertical, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
IBM (United States), Splunk (United States), CA Technologies (United States), Micro Focus (United Kingdom), VMware (United States), HCL Technologies (India), AppDynamics (United States), BMC Software (United States), New Relic (United States), Appnomic (India), CloudFabrix (United States), Loom Systems (United States), Dynatrace (United States), Zenoss (United States ), Ymor (United States), Devo (United States), Logz.io (United States), ServiceNow (United States), Corvil (Ireland), Interlink Software Services (United Kingdom), Correlata (Israel), ScienceLogic (United States ), Sumo Logic (United States), RISC Networks (United States) and Bay Dynamics (United States) and Others. |
Based on the application, the market is segmented into IT operations analysis, application performance management, infrastructure management, network analysis, security analysis, and more.
The market is classified into large companies and SMEs depending on the company's size. The market based on the type of implementation is classified as cloud-based and local.
The Asia-Pacific region is expected to experience the fastest growth in mandate during the forecast period. Significant growth factors for the APAC market include the increasing complexity of the IT environment and the increasing adoption of cognitive operations solutions in the telecommunications, banking, financial services, besides insurance (BFSI) sectors to streamline IT operations processes and increase delivery demand. A better customer experience is the primary vertical sector of the industry.
The telecommunications sector, which has a prominent share in the cognitive operations market, is expanding in the APAC area. For example, according to S&P Global, in 2019, mobile subscriptions in China increased to 1.6 billion compared to 1.23 billion in India and 332.5 million in Indonesia.
The Asia-Pacific region is expected to be the fastest-growing region for data governance, management, and analysis due to increased spending on technology in economies such as India, China, Singapore, and Australia. The rising call for cost-effective governance and data management solutions within small and medium-sized enterprises (SMEs) promotes the development of the cognitive operations market in the locale.
The major companies operating in the global cognitive operations market include IBM (United States), Splunk (United States), CA Technologies (United States), Micro Focus (United Kingdom), VMware (United States), HCL Technologies (India), AppDynamics (United States), BMC Software (United States), New Relic (United States), Appnomic (India), CloudFabrix (United States), Loom Systems (United States), Dynatrace (United States), Zenoss (United States ), Ymor (United States), Devo (United States), Logz.io (United States), ServiceNow (United States), Corvil (Ireland), Interlink Software Services (United Kingdom), Correlata (Israel), ScienceLogic (United States ), Sumo Logic (United States), RISC Networks (United States) and Bay Dynamics (United States).
BMC Software recently introduced its MC Helix Cognitive Service Management (CSM) to combine novel cognitive capacities like AI and machine learning in the existing IT service management (ITSM) solutions.
ServiceNow acquired Parlo, based in Silicon Valley, specializing in understanding workforce solutions in natural language and artificial intelligence. Following this acquisition, ServiceNow aims to strengthen its investments in AI to leverage the benefits of technology for its platforms, products, and solutions.
In March 2020, Nokia announced its new product, Nokia AVA 5G Cognitive Operations, a comprehensive AI service combining data science, machine learning, telecommunications, and cloud expertise to bring AI to life. Anticipate network and service outages with high precision and accuracy up to seven days before. Regarding failure, Nokia 5G Cognitive Operations can address issues 50% faster and analyze the influence on users and services.
By Component
By Application
By Organization Size
By Vertical
By Deployment Type
By Region
North America
The United States
Canada
Rest of North America
Europe
The United Kingdom
Spain
Germany
Italy
France
Rest of Europe
The Asia Pacific
India
Japan
China
Australia
Singapore
Malaysia
South Korea
New Zealand
Southeast Asia
Latin America
Brazil
Argentina
Mexico
Rest of LATAM
The Middle East and Africa
Saudi Arabia
UAE
Lebanon
Jordan
Cyprus
Frequently Asked Questions
Large enterprises are adopting cognitive operations to automate routine tasks, predict and prevent system failures, enhance customer experience, and optimize resource allocation. This results in increased operational efficiency and cost savings.
Cloud computing is a pivotal factor in the growth of the Cognitive Operations Market, facilitating scalable and cost-effective deployment of cognitive solutions. It allows businesses to access and analyze vast amounts of data in real-time, fostering agility and responsiveness.
The market is witnessing increased investments in developing robust security measures and compliance frameworks. Cognitive operations solutions are incorporating advanced encryption, authentication, and authorization protocols to ensure the confidentiality and integrity of sensitive data.
Trends such as explainable AI, autonomous operations, and the integration of cognitive technologies with edge computing are gaining prominence. These innovations aim to enhance the interpretability, autonomy, and efficiency of cognitive operations systems.
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