According to a new report published by Introspective Market Research, titled, “Generative AI in Analytics Market by Component, Deployment, Application, and End-User,” The Global Generative AI in Analytics Market Size Was Valued at USD 1.54 Billion in 2024 and is Projected to Reach USD 20.19 Billion by 2035, Growing at a CAGR of 26.36% From 2025–2035.
The Generative AI in Analytics market represents a transformative force in the business intelligence and data analysis landscape. This technology leverages advanced machine learning models to autonomously generate insights, narratives, forecasts, and data visualizations from raw datasets. Unlike traditional analytics, which often requires manual hypothesis testing and rigid query structures, Generative AI can uncover complex, non-obvious patterns, simulate scenarios, and create natural-language explanations, dramatically accelerating the path from data to decision. The primary advantage of this market lies in its ability to democratize advanced analytics, enabling users across technical skill levels to conduct sophisticated data exploration through intuitive conversational interfaces. Major industries such as BFSI, retail, healthcare, and manufacturing are rapidly adopting these solutions. Key applications include automated report generation, predictive forecasting, synthetic data creation for model training, and dynamic dashboards that adapt to user queries in real time, driving unprecedented efficiency and strategic agility.
The primary growth driver for the Generative AI in Analytics market is the overwhelming volume and complexity of modern enterprise data. Organizations are inundated with data from diverse sources but struggle to derive timely, actionable insights using conventional tools. Generative AI directly addresses this challenge by automating the analysis process, translating complex data sets into comprehensible narratives and visualizations without requiring deep technical expertise. This capability allows businesses to make faster, data-driven decisions, optimize operations, and uncover hidden opportunities, creating a critical demand for intelligent, autonomous analytics solutions across all sectors.
A significant market opportunity lies in the rising demand for personalized customer experiences and hyper-targeted marketing. Generative AI in Analytics can synthesize customer data from multiple touchpoints to generate dynamic customer segments, predict individual behavior, and create personalized content or product recommendations at scale. For industries like retail, e-commerce, and financial services, this ability to move beyond generic segmentation to truly individualized engagement represents a powerful competitive edge, driving increased customer loyalty, conversion rates, and lifetime value, and opening a substantial revenue avenue for analytics providers.
Generative AI in Analytics Market, Segmentation
The Generative AI in Analytics Market is segmented on the basis of Component, Deployment Mode, Application, and End-User.
Component
The Component segment is further classified into Software and Services. Among these, the Software sub-segment accounted for the highest market share in 2024. This dominance is attributed to the core role of Generative AI platforms and integrated analytics suites that provide the foundational algorithms, user interfaces, and model training environments. The software encompasses everything from standalone generative analytics tools to embedded AI capabilities within existing business intelligence platforms, forming the essential technological backbone that enables automated insight generation and is the primary investment focus for enterprises.
Deployment Mode
The Deployment Mode segment is further classified into Cloud and On-Premises. Among these, the Cloud sub-segment accounted for the highest market share in 2024. The cloud deployment model’s dominance is driven by its scalability, lower upfront costs, and ease of integration with other cloud-native data sources and services. It allows organizations of all sizes, particularly SMEs, to rapidly deploy and experiment with powerful Generative AI analytics capabilities without significant infrastructure investment, while also facilitating seamless updates and access to the latest AI model improvements from providers.
Some of The Leading/Active Market Players Are-
• Microsoft Corporation (US)
• IBM Corporation (US)
• Google LLC (US)
• Salesforce, Inc. (US)
• SAS Institute Inc. (US)
• Oracle Corporation (US)
• Amazon Web Services, Inc. (US)
• SAP SE (Germany)
• Alteryx, Inc. (US)
• Databricks, Inc. (US)
• TIBCO Software Inc. (US)
• QlikTech International AB (US)
• ThoughtSpot, Inc. (US)
• Tellius, Inc. (US)
other active players.
Key Industry Developments
In February 2024, Salesforce launched its Einstein 1 Studio, integrating powerful generative AI capabilities directly into its Tableau analytics platform. This allows users to create calculated fields, build visualizations, and generate narrative summaries using natural language prompts, deeply embedding generative analytics into the workflow of business users.
In November 2023, IBM announced the integration of its watsonx.ai generative AI platform with IBM Cognos Analytics and Planning Analytics. This development enables enterprises to use conversational language for complex financial forecasting, automated reporting, and scenario generation, significantly enhancing the strategic planning capabilities of finance and analytics teams.
Key Findings of the Study
The software component and cloud deployment mode segments dominated the market share in 2024.
North America held the leading regional revenue share, fueled by strong technological adoption and presence of key players.
The exponential growth of enterprise data and the need for democratized analytics are the key growth drivers.
A major trend is the integration of Generative AI into existing business intelligence and data science platforms.
