AI in Data Analytics Market Revenue to Attain USD 240.88 Bn by 2033

24 Oct 2025

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Table of Content

1. AI in Data Analytics Market Revenue and Trends 2025 to 2033 2. What Fuels Growth in AI Data Analytics? 3. Segmental Analysis 4. Regional Analysis 5. AI in Data Analytics  Market Coverage

AI in Data Analytics Market Revenue and Trends 2025 to 2033

The global AI in data analytics market revenue reached USD 31.22 billion in 2025 and is predicted to attain around USD 240.88 billion by 2033 with a CAGR of 29.10%. The AI in data analytics market is driven by increasing data volumes, automation demand, and adoption of advanced machine learning for decision-making efficiency.

What Fuels Growth in AI Data Analytics?

The AI in data analytics space is experiencing an explosive change mainly driven by the reality of organizations needing real-time data insights, automation, and predictability across all industries. As organizations seek to implement AI-driven analytics, the value of data-driven decisions has become more prevalent. Organizations are relying on AI technologies including machine learning, natural language processing, and deep learning to parse through massive and intricate data sets to identify meaningful trends and predictive intelligence.

Overall, organizations are experiencing substantial gains across healthcare, finance, retail, and manufacturing due to a variety of factors including digital transformation, the boom in computing power of and advancements in cloud computing, and the on-going emphasis on leveraging data as an imperative for remaining competitive and efficient.

Segmental Analysis

• By Segment- Software accounted for the largest market share in AI in data analytics as organizations increasingly adopted sophisticated analytical platforms and automation tools to harness data in seamless integration, visualizations, and real-time decision-making across industries.
• By Type- Predictive analytics represented the predominant sector as organizations were increasingly reliant on forecasting models and AI-based insights to anticipate trends, improve operations, and bolster business intelligence capabilities.
• By Industry Vertical- IT & telecommunications represented the largest market as organizations have increasingly relied on growing data generation, digital transformation projects, and AI-enriched analytics to improve network efficiency, customer engagement, and service performance.

Regional Analysis

North America is dominant due to its extensive technology infrastructure; high levels of investment in R&D, along with an extensive presence of significant AI players (e.g., cloud platforms, analytics companies). The sectors of finance, healthcare, and retail were some of the earliest industries to adopt AI- powered analysis tools. In addition, the region's regulatory structure supporting cloud as well as data privacy while promoting innovation contributes to success. North America also maintains a large share of revenue, as many of the large organizations in North America continue to implement AI in predictive, diagnostic and prescriptive analysis.

Asia-Pacific is the fastest growing region on the basis of government digitalization initiatives and support for strong start-up ecosystems as well as a rapidly increasing adoption of the cloud and population density of data users in countries like China, India, South Korea, Japan and Southeast Asia. Sectors like health care, agriculture, fin-tech, and smart cities are increasingly using AI- analytics. However, this has some caveats including gaps in infrastructure (especially data centers), diverse regulatory environments, and the demand for talent. But, with government and private investment and support, some of these challenges are evolving at a reasonable pace.

AI in Data Analytics  Market Coverage

Recent Developments

• In March 2025, Zoho Corporation launched Projects Plus, a flexible, collaborative new platform providing data- and intelligence-driven project management for mid-sized and large organizations. This work across 4 areas data democratization, AI, hybrid project management, and collaborative work management. 
  (Source: https://www.businesswire.com)

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