Generative AI in Analytics Market Report 2026

The generative AI in analytics market size has grown exponentially in recent years. It will grow from $1.69 billion in 2025 to $2.21 billion in 2026 at a compound annual growth rate (CAGR) of 30.7%. The growth in the historic period can be attributed to growth in enterprise data volumes, limitations of traditional analytics, early adoption of machine learning models, increasing demand for business intelligence tools, rise of data-driven decision making.

The generative AI in analytics market size is expected to see exponential growth in the next few years. It will grow to $5.51 billion in 2030 at a compound annual growth rate (CAGR) of 25.7%. The growth in the forecast period can be attributed to widespread adoption of generative models, demand for real-time analytics, expansion of self-service analytics, increasing focus on predictive accuracy, integration of AI across enterprise workflows. Major trends in the forecast period include automated insight generation, synthetic data creation, predictive scenario modeling, conversational analytics interfaces, context-aware decision support.

The increasing demand for AI-generated content is anticipated to drive the growth of the generative AI in analytics market in the foreseeable future. AI-generated content refers to digital content, including text, images, or videos, that is produced using artificial intelligence algorithms and technologies. This rising demand for AI-generated content is fueled by its capacity to efficiently deliver personalized and relevant content on a large scale, thereby enhancing user engagement and reducing production costs for businesses. Generative AI models are capable of analyzing extensive datasets to identify patterns, trends, and insights that can be leveraged to create content such as articles, reports, and creative works. For example, in February 2024, DOIT Software, a US-based company specializing in business software and AI tools, reported that the generative AI platform ChatGPT had an estimated engagement of 57 million individuals in 2022, which surged to 100 million by January 2023. This surge in demand for AI-generated content is a key driver behind the growth of the generative AI in analytics market.

Major companies in the generative AI in analytics market are focusing on developing advanced solutions such as artificial intelligence (AI)-powered analytics platforms to meet the rising need for faster, more accurate data insights and improved decision-making capabilities. AI-powered analytics platforms use generative AI models to automatically analyze large datasets, produce predictive insights, and generate natural language summaries, offering a substantial improvement over traditional analytics tools that depend on manual queries and static reporting. For example, in March 2023, Salesforce, Inc., a U.S.-based cloud software company, introduced Tableau Einstein GPT, an AI-powered analytics platform that merges Tableau’s data visualization strengths with generative AI to deliver automated insights and recommendations. The platform embeds large language models directly into analytics workflows, allowing users to ask natural-language questions, generate AI-driven visualizations, and receive actionable insights instantly. Key features include real-time data interaction, predictive analytics, and AI-generated explanations of complex trends, helping streamline decision-making and enhance productivity across business functions. Tableau Einstein GPT is especially valuable for organizations aiming to democratize data access, minimize manual analysis, and improve the speed and accuracy of strategic decisions.

In March 2024, Databricks Inc., a US-based artificial intelligence company, completed the acquisition of Lilac AI for an undisclosed sum. This strategic acquisition by Databricks aims to streamline the evaluation of unstructured data for generative AI applications. Lilac AI offers a scalable and user-friendly tool for data scientists to search, cluster, and analyze text datasets with a focus on generative AI. Lilac AI, a US-based startup specializing in scalable tools for text data analysis in generative AI, provides valuable capabilities for exploring, clustering, and analyzing various types of text datasets, further enhancing Databricks' offerings in the AI space.

Major companies operating in the generative AI in analytics market are Amazon Inc.; Apple Inc.; Alphabet Inc.; Microsoft Corporation; Dell Technologies Inc.; Siemens AG; Accenture PLC; International Business Machines Corporation (IBM); Oracle Corporation; SAP SE; NVIDIA Corporation; Adobe Inc.; Block Inc.; Automatic Data Processing Inc.; ServiceNow Inc.; Workday Inc.; Atlassian Corporation; Slack Technologies Inc.; OpenAI; MongoDB Inc.; Box Inc.; SG Analytics Pvt. Ltd.; Decimal Point Analytics Pvt; Gramener Inc.; Anthropic PBC; Valiance Solutions Inc.

North America was the largest region in the generative AI in analytics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative AI in analytics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the generative AI in analytics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Tariffs have moderately influenced the Generative AI in Analytics market by increasing costs associated with high-performance computing hardware, data center infrastructure, and advanced semiconductors required for model training and deployment. These impacts are more visible in on-premise deployments and regions such as Asia-Pacific and North America, where cross-border sourcing of AI hardware is significant. Higher infrastructure costs have affected smaller enterprises and research institutions more than large cloud-backed organizations. On the positive side, tariffs have accelerated the shift toward cloud-based analytics platforms and optimized model architectures, encouraging software-centric innovation and reducing long-term dependency on physical infrastructure.

The generative AI in analytics market research report is one of a series of new reports that provides generative AI in analytics market statistics, including generative AI in analytics industry global market size, regional shares, competitors with a generative AI in analytics market share, detailed generative AI in analytics market segments, market trends and opportunities, and any further data you may need to thrive in the generative AI in analytics industry. This generative AI in analytics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

Generative AI in analytics encompasses a specialized domain within artificial intelligence aimed at developing models and algorithms capable of generating fresh and insightful data, analyses, or content by leveraging patterns and existing datasets. This approach harnesses data-driven insights to fuel innovation, streamline decision-making processes, and unveil latent patterns that may elude traditional analytical methods.

The primary technologies underpinning generative AI in analytics include machine learning, natural language processing, deep learning, computer vision, and robotic process automation. Machine learning, a core component, empowers computers to learn from data and enhance their performance on specific tasks without explicit programming. These technologies operate across cloud-based and on-premise platforms, serving diverse applications such as data augmentation, anomaly detection, text generation, simulation, and forecasting.

The generative AI in analytics market consists of revenues earned by providing services such as predictive modeling, anomaly detection, and data synthesis. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative AI in analytics market also includes sales of high-performance computing (HPC) systems, specialized processors such as graphical processing units (GPUs) or tensor processing units (TPUs). Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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