Cognitive Analytics Market Size & Share 2023 to 2032
Market Size by Component (Tools, Services [Managed, Professional]), Deployment (On-premise, Cloud), Enterprise Size (SME, Large Enterprise), Application, End User, Growth Prospects, Regional Outlook & Forecast.
Report ID: GMI7368
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Published Date: November 2023
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
Cognitive Analytics Market Size
Cognitive Analytics Market size was valued at USD 3.2 billion in 2022 and is estimated to register a CAGR of 34% between 2023 and 2032. The increasing funding in cognitive analytics startups is driving significant growth in the market. These investments provide startups with resources to develop innovative technologies and solutions, fostering advancements in artificial intelligence & data analytics.
Cognitive Analytics Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
For instance, in May 2023, Course5 Intelligence, a startup burgeoning in data analytics & AI, secured funding of USD 28 million from 360 ONE Asset Management. This investment will be used to improve the startup's context-conscious dialogue management along with cognitive semantic search abilities. The move also aims to allow users to interact with the structured and tabular data, enabling them to extract insights using natural language for swift decision-making.
The proliferation of Big Data, characterized by massive volumes of structured and unstructured information, serves as a foundational driver for the cognitive analytics market. Businesses are increasingly harnessing data to gain valuable insights, understand market trends, and make informed decisions. Cognitive analytics solutions excel in processing and analyzing this vast data pool, extracting meaningful patterns & correlations. As the volume of data continues to grow exponentially, the demand for advanced cognitive analytics tools rises, fueling market expansion and innovation in data-driven decision-making processes.
Data security and privacy concerns stand as significant challenges hindering the cognitive analytics industry growth. As businesses increasingly rely on sensitive data for analysis, ensuring the confidentiality and protection of this information becomes paramount. The risk of privacy breaches, data theft, and unauthorized access poses a barrier to widespread adoption. Companies need robust security measures and compliance with regulations to alleviate these concerns and build trust among users, stakeholders & regulatory bodies.
COVID-19 Impact
The COVID-19 pandemic has positively impacted the cognitive analytics market as businesses navigate unprecedented challenges. The need for real-time data analysis to understand rapidly changing consumer behavior and market trends surged. Cognitive analytics tools have played a vital role in helping companies adapt their strategies swiftly, optimize supply chains, and enhance customer experiences. As a result, the demand for cognitive analytics solutions has grown, fostering innovation, and accelerating the adoption of advanced data-driven decision-making processes.
Cognitive Analytics Market Trends
Platforms offering data-driven risk assessment insights for insurance companies are driving lucrative growth in the market. These solutions empower insurers with advanced analytics, enabling precise risk evaluation, fraud detection & personalized policy offerings. For instance, in July 2023, Verikai, Inc., a provider of advanced predictive analytics & AI-driven solutions for the insurance sector, launched an innovative platform that integrates robust data-driven risk assessment insights into an intuitive digital portal, transforming the entire underwriting process for insurance companies and enhancing their overall experience.
Advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies are pivotal in propelling the cognitive analytics market. These continuous innovations empower cognitive analytics tools to handle increasingly complex and diverse datasets. Machine learning algorithms, backed by AI, enable accurate predictive modeling, automated data analysis & real-time pattern recognition. As businesses seek more sophisticated insights and automation, the evolution of AI & ML techniques plays a crucial role, making cognitive analytics solutions indispensable for modern enterprises aiming to gain actionable intelligence from their data.
Cognitive Analytics Market Analysis
Based on component, the tools segment dominated around USD 2 billion revenue in 2022. Autonomy and control over analytics processes are driving the preference for cognitive analytics tools. Businesses seek self-reliance in data analysis, allowing them to customize, experiment & implement solutions independently. This control ensures confidentiality, agility, and the ability to adapt analytics to specific needs. With tools, organizations can make data-driven decisions in real time without relying on external expertise, promoting quicker, more efficient & personalized insights. This desire for independence propels the tools segment growth, offering businesses the freedom to harness data analytics according to their unique requirements.
Based on application, the customer analytics segment accounted for 28% of the cognitive analytics market share in 2022. The need to identify customer engagement levels is propelling the customer analytics segment growth. Businesses increasingly recognizing the importance of understanding customer behavior, preferences, and sentiments. Cognitive analytics tools empower organizations to accurately analyze vast datasets, discern patterns & predict customer engagement levels.
For instance, in August 2023, Twilio Segment launched an impactful tool, CustomerAI Predictions, which is crafted to convert customer data into actionable insights. This tool assists marketers in making precise predictions about the behavior of specific customer segments, empowering them to make informed decisions based on these accurate forecasts.
North America cognitive analytics market held over 33% of revenue share in 2022. Increasing investments in AI technology in the U.S. is a key factor propelling the market size. Companies in the U.S. are heavily investing in AI research, development & implementation, leading to the creation of advanced cognitive analytics solutions. These investments fuel innovation, enhance the capabilities of cognitive analytics tools, and drive their adoption across various industries. As a result, the North America market continues to experience significant growth, propelled by ongoing AI technology investments.
Cognitive Analytics Market Share
Major companies operating in the cognitive analytics industry are:
The cognitive analytics market is dominated by Google Inc., IBM Corporation, Oracle Corporation, and SAS Institute. Major companies are fiercely competing for market shares through continuous technological advancements, product innovation, strategic partnerships, global expansion, and aggressive marketing campaigns.
Cognitive Analytics Industry News
The cognitive analytics market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Million) from 2018 to 2032, for the following segments:
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Market, By Component
Market, By Deployment
Market, By Enterprise Size
Market, By Application
Market, By End User
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.
Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.
2. Primary research
Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.
3. Data mining & market analysis
Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.
5. Forecast model & key assumptions
Every forecast includes explicit documentation of:
✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
6. Validation & quality assurance
The final stages involve human validation, where domain experts manually review filtered data to identify nuances and contextual errors that automated systems might miss. This expert review adds a critical layer of quality assurance, ensuring data aligns with research objectives and domain-specific standards.
Our triple-layer validation process ensures maximum data reliability:
✓ Statistical Validation
✓ Expert Validation
✓ Market Reality Check
Trust & credibility
Verified data sources
Trade publications
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Industry databases
Proprietary and third-party market databases
Regulatory filings
Government procurement records and policy documents
Academic research
University studies and specialist institution reports
Company reports
Annual reports, investor presentations, and filings
Expert interviews
C-suite, procurement leads, and technical specialists
GMI archive
13,000+ published studies across 30+ industry verticals
Trade data
Import/export volumes, HS codes, and customs records
Parameters studied & evaluated
Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →