AI-Powered Business Intelligence Market Size, Share, Opportunities, And Trends By Component (Hardware, Software), By Deployment (On-Premise, Cloud-Based), By End-User (Banking, Financial Services, and Insurance (BFSI), Retail and E-Commerce, Healthcare, Telecom, Government and Public Sector, Others), And By Geography – Forecasts From 2025 To 2030

AI-Powered Business Intelligence Market Size:

The AI-powered business intelligence market is expected to grow at a substantial pace during the forecast period.

The AI-powered business intelligence market is growing rapidly, due to the growing need for real-time analytics, data-driven decision-making, and automation across industries. Companies are adopting AI-enhanced BI tools. Industries like finance, healthcare, retail, manufacturing, and logistics are adopting AI tools to find hidden patterns, predict trends, and increase operational efficiency. Traditional BI systems are being transformed into AI  platforms due to the growth in volume of data. Scalable, user-friendly solutions, the growth of big data, and cloud adoption are driving the market growth. Businesses are also using AI-powered BI to improve customer experiences and decrease manual labour. Furthermore, the need for secure analytics and increased regulatory pressures are driving global investment in cutting-edge BI platforms.

AI-Powered Business Intelligence Market Overview & Scope:

The AI-powered business intelligence market is segmented by:

• Component: Software holds a significant share of the AI-powered business intelligence market. This is because it helps in enabling data analysis, visualisation, and decision-making. Business intelligence software can easily transform raw data into actionable insights. Business intelligence software is suitable for both small and large enterprises.
• Deployment: Cloud-based solutions hold a considerable growth driver in the AI-powered business intelligence market. This is due to their ability to deliver scalability, real-time collaboration, and cost-effective data management. Cloud infrastructure enables businesses to access advanced BI tools without heavy upfront infrastructure investments. These solutions also help in real-time data integration and collaboration across geographies.
• End User: Retail and e-commerce hold a major share of the AI-powered business intelligence market. It is due to their reliance on data-driven decision-making. This helps in enhancing customer experience, optimising operations, and increasing sales.AI powered tools help retailers to analyse various trends such as shopping patterns and behaviours. Features like real-time analytics allow businesses to easily respond to changing market trends.
• Region: The Asia-Pacific AI-powered business intelligence (BI) market is witnessing strong growth. This is due to rapid digital transformation and increasing enterprise data generation. Countries like India and China are adopting AI-driven BI tools across sectors such as finance, retail, healthcare, and manufacturing

Top Trends Shaping the AI-Powered Business Intelligence Market:

• Integration of Generative AI and Natural Language Processing (NLP): A trend in the AI-powered business intelligence market is the integration of generative AI and natural language processing. It helps users to interact with dashboards using simple language queries and enables non-technical users to generate reports
• Shift Toward Augmented Analytics- Another significant trend is the shift towards augmented analytics. Augmented analytics combines AI, machine learning, and automation. It is transforming how data is prepared, analysed, and visualised.
• Expansion of Cloud-Based BI Solutions: There has been an increase in the expansion of cloud-based business intelligence solutions. This is due to growing remote work and global data access needs. Cloud platforms offer scalability, seamless integration, and real-time collaboration

AI-Powered Business Intelligence Market Growth Drivers vs. Challenges:

Drivers:

• Rising Demand for Real-Time Data Analytics: One of the key drivers of the AI-powered business intelligence market is the rising demand for real-time data analytics. Organisations are seeking real-time insights to make faster and more informed decisions. AI-powered tools help in data monitoring, rapid trend identification, and predictive analytics. It also helps businesses to respond quickly to business changes and customer behaviour. According to Neontri, the potential benefit of real-time data analytics is that revenue can be increased by 28.1% which can be totalled $4,2 trillion.
• Growing Volume and Complexity of Data: Another key driver of the AI-powered business intelligence market is the growth in volume and complexity of data. AI-powered BI platforms can process and analyse massive datasets efficiently. They can also uncover hidden patterns and deliver deeper, actionable insights. It makes them an important tool to have for data-driven businesses. According to Oracle, data volumes are doubling every two years, and data scientists are spending 50 per cent to 80 per cent of their time curating and preparing data, even after the availability of so many tools in the market.

Challenges:

• Data Privacy and Regulatory Compliance: One of the major challenges of the AI-powered business intelligence market is data privacy and regulatory concerns Ai AI-powered BI is dependent on a vast amount of data. These data include sensitive personal, financial, or health information. Stringent regulations such as the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) ensure regulatory compliance. Regulatory compliances include acquiring proper user consent, enabling data anonymisation, and ensuring transparency in AI algorithms. Organisations should always ensure strict compliance with global data privacy standards while extracting data.

AI-Powered Business Intelligence Market Regional Analysis:

• North America: North America’s AI-powered business intelligence market is witnessing strong growth, as the region has technological leadership and a data-driven decision-making culture. Organisations in sectors like finance, healthcare, retail, and manufacturing are adopting AI-enhanced business intelligence tools. It will help them gain actionable insights, automate data preparation, and improve forecasting accuracy. The integration of artificial technologies is transforming the AI-powered business intelligence market. The growth in volume of data has made traditional analytics insufficient. Thus, there has been a push towards AI-driven solutions, and Cloud computing is also playing a huge role in the market. It is offering scalability, accessibility, and integration with other enterprise applications.

AI-Powered Business Intelligence Market Competitive Landscape:

The market has many notable players, including. Microsoft, Tableau, ThoughtSpot, IBM, SAP, Databricks, Qlik, Domo, GoodData, AlphaSense, among others.

• Partnership: In June 2025, Databricks announced its partnership with Microsoft. This strategic partnership is focused on providing organisations with cutting-edge data and AI capabilities. There have been other integrations between Azure and Databricks, like Azure AI Foundry and Microsoft Power Platform.
• Product Launch: In June 2024, Databricks announced the launch of Databricks AI/BI. It is a business intelligence product that aims to simplify data analysis for everyone in an organisation. It consists of Dashboards, an AI-powered, low-code interface, and Genie, a conversational interface for addressing ad-hoc and follow-up questions.

AI-Powered Business Intelligence Market Segmentation:

By Component

• Hardware
• Software

By Deployment

• On-Premise
• Cloud-Based

By End-User

• Banking, Financial Services, and Insurance (BFSI)
• Retail and E-Commerce
• Healthcare
• Telecom
• Government and Public Sector
• Others

By Region

• North America
  • USA
  • Canada
  • Mexico
• South America
  • Brazil
  • Argentina
  • Others
• Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Others
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Thailand
  • Others

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

2.1. Market Overview

2.2. Market Definition

2.3. Scope of the Study

2.4. Market Segmentation

3. BUSINESS LANDSCAPE

3.1. Market Drivers

3.2. Market Restraints

3.3. Market Opportunities

3.4. Porter’s Five Forces Analysis

3.5. Industry Value Chain Analysis

3.6. Policies and Regulations

3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. AI-Powered Business Intelligence Market by Component

5.1. Introduction

5.2. Hardware

5.3. Software

6. AI-Powered Business Intelligence Market BY Deployment

6.1. Introduction

6.2. On-Premise

6.3. Cloud-Based

7. AI-Powered Business Intelligence Market BY End-User

7.1. Introduction

7.2. Banking, Financial Services, and Insurance (BFSI)

7.3. Retail and E-Commerce

7.4. Healthcare

7.5. Telecom

7.6. Government

7.7. Others

8.  AI-Powered Business Intelligence Market BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. USA

8.2.2. Canada

8.2.3. Mexico

8.3. South America

8.3.1. Brazil

8.3.2. Argentina

8.3.3. Others

8.4. Europe

8.4.1. United Kingdom

8.4.2. Germany

8.4.3. France

8.4.4. Italy

8.4.5. Spain

8.4.6. Others

8.5. Middle East & Africa

8.5.1. Saudi Arabia

8.5.2. UAE

8.5.3. Others

8.6. Asia Pacific

8.6.1. China

8.6.2. India

8.6.3. Japan

8.6.4. South Korea

8.6.5. Thailand

8.6.6. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisitions, Agreements, and Collaborations

9.4. Competitive Dashboard

10. COMPANY PROFILES

10.1. Microsoft

10.2. Tableau

10.3. ThoughtSpot

10.4. IBM

10.5. SAP

10.6. Databricks

10.7. Qlik

10.8. Domo

10.9. GoodData

10.10. AlphaSense

11. APPENDIX

11.1. Currency

11.2. Assumptions

11.3. Base and Forecast Years Timeline

11.4. Key benefits for the stakeholders

11.5. Research Methodology

11.6. Abbreviations

Microsoft

Tableau

ThoughtSpot

IBM

SAP

Databricks

Qlik

Domo

GoodData

AlphaSense