by The generative AI in analytics market size is poised to grow by USD 8,900.36 million by 2032 from USD 724.5 million in 2022, exhibiting a CAGR of 28.51% during the forecast period 2023-2032.
Key Takeaways:
- North America dominated the market with the largest revenue share of 49% in 2022.
- Asia Pacific is expected to expand at the fastest CAGR between 2023 and 2032.
- By deployment, the cloud-based segment dominated the market with the most significant revenue in 2022. On-premises segment is expected to boost at a significant rate during the forecast period.
- By technology, the machine learning segment dominated the market with the highest market share of 30% in 2022.
- By technology, the natural language processing segment is expected to grow substantially in market share during the anticipated timeframe.
- By application, the data augmentations segment dominated the market with the largest market share in 2022. The simulation and forecasting segment is expected to significantly increase its market share in 2022.
Precedence Research has conducted a comprehensive market study that provides valuable insights into the performance of the market during the forecast period. The study identifies significant trends that are shaping the growth of the Generative AI in analytics market. In this recently published report, essential dynamics such as drivers, restraints, and opportunities are highlighted for both established market players and emerging participants involved in production and supply.
To begin with, the Generative AI in analytics Market report features an executive summary that offers a concise overview of the marketplace. It outlines the key players and industry categories expected to have an impact on the market in the coming years. The executive summary provides an unbiased summary of the market.
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Generative AI in Analytics Market Report Scope
| Report Coverage | Details |
| Market Size in 2023 | USD 931.05 Million |
| Market Size by 2032 | USD 8,900.36 Million |
| Growth Rate from 2023 to 2032 | CAGR of 28.51% |
| Largest Market | North America |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Segments Covered | By Deployment, By Technology and By Application |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
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The empirical study on the global Generative AI in analytics market primarily focuses on the drivers in subsequent sections. It demonstrates how changing demographics are projected to influence the supply and demand dynamics in the Generative AI in analytics Market. Our market report for the Generative AI in analytics market also delves into the significant rules and regulations that are likely to impact the future growth of this sector. Moreover, in order to comprehend the underlying demand factors, industry experts have provided insights into its fundamental origins.
Regional Snapshot:
In 2022, the North American region emerged as the dominant player in the market, boasting the largest market share. Projections indicate that this regional dominance will persist throughout the forecast period. The key driver behind this market growth is the rapid adoption and integration of automated technologies in various sectors across North America.
Furthermore, the region’s ongoing industrialization process is expected to fuel the market’s expansion in the coming years, particularly emphasizing the significance of deploying artificial intelligence solutions. As industries continue to evolve and innovate, the demand for automation and data-driven technological solutions is expected to witness substantial growth.
Notably, there has been a notable surge in the adoption of generative AI technologies in countries like the United States and Canada. This increased adoption is anticipated to drive the demand for generative AI in the analytics market, further augmenting the overall growth of the North American market.
Top Key Players:
- Workday Inc
- OpenAI
- Microsoft
- Adobe
- NVIDIA
- ADP
- IBM
- SAP SE
- Oracle
- Other
Data Sources and Methodology
To gather comprehensive insights on the Global Generative AI in analytics Market, we relied on a range of data sources and followed a well-defined methodology. Our approach involved interactions with industry experts and key stakeholders across the market’s value chain, including management organizations, processing organizations, and analytics service providers.
We followed a rigorous data analysis process to ensure the quality and credibility of our research. The gathered information was carefully evaluated, and relevant quantitative data was subjected to statistical analysis. By employing robust analytical techniques, we were able to derive meaningful insights and present a comprehensive overview of the Global Generative AI in analytics Market.
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- The research report has been meticulously crafted to provide comprehensive knowledge on essential marketing strategies and a holistic understanding of crucial marketing plans spanning the forecasted period from 2023 to 2032.
Key Features of the Report:
- Comprehensive Coverage: The report extensively encompasses a detailed explanation of highly effective analytical marketing methods applicable to companies across all industry sectors.
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- Articulated R&D Approach: The report presents a well-defined approach to conducting research and development (R&D) activities, enabling accurate data acquisition on current and future marketing conditions.
Generative AI in Analytics Market Segmentation:
By Deployment
- Cloud-Based
- On-premise
By Technology
- Machine learning
- Natural Language Processing
- Deep learning
- Computer vision
- Robotic Process Automation
By Application
- Data Augmentation
- Anomaly Detection
- Text Generation
- Simulation and Forecasting
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and Africa
Reasons to Consider Purchasing the Report:
- Enhance your market research capabilities by accessing this comprehensive and precise report on the global Generative AI in analytics market.
- Gain a thorough understanding of the overall market landscape and be prepared to overcome challenges while ensuring robust growth.
- Benefit from in-depth research and analysis of the latest trends shaping the global Generative AI in analytics market.
- Obtain detailed insights into evolving market trends, current and future technologies, and strategic approaches employed by key players in the global Generative AI in analytics market.
- Receive valuable recommendations and guidance for both new entrants and established players seeking further market expansion.
- Discover not only the cutting-edge technological advancements in the global Generative AI in analytics market but also the strategic plans of industry leaders.
Table of Content
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Generative AI in Analytics Market
5.1. COVID-19 Landscape: Generative AI in Analytics Industry Impact
5.2. COVID 19 – Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Generative AI in Analytics Market, By Deployment
8.1. Generative AI in Analytics Market, by Deployment, 2023-2032
8.1.1 Cloud-Based
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. On-premise
8.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Analytics Market, By Technology
9.1. Generative AI in Analytics Market, by Technology, 2023-2032
9.1.1. Machine learning
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Natural Language Processing
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Deep learning
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Computer vision
9.1.4.1. Market Revenue and Forecast (2020-2032)
9.1.5. Robotic Process Automation
9.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Analytics Market, By Application
10.1. Generative AI in Analytics Market, by Application, 2023-2032
10.1.1. Data Augmentation
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Anomaly Detection
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Text Generation
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Simulation and Forecasting
10.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Generative AI in Analytics Market, Regional Estimates and Trend Forecast
11.1. North America
11.1.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.2. Market Revenue and Forecast, by Technology (2020-2032)
11.1.3. Market Revenue and Forecast, by Application (2020-2032)
11.1.4. U.S.
11.1.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.1.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.1.5. Rest of North America
11.1.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.1.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.1.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.2. Europe
11.2.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.2. Market Revenue and Forecast, by Technology (2020-2032)
11.2.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.4. UK
11.2.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.2.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.5. Germany
11.2.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.2.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.6. France
11.2.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.6.2. Market Revenue and Forecast, by Technology (2020-2032)
11.2.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.2.7. Rest of Europe
11.2.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.2.7.2. Market Revenue and Forecast, by Technology (2020-2032)
11.2.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.3. APAC
11.3.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.2. Market Revenue and Forecast, by Technology (2020-2032)
11.3.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.4. India
11.3.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.3.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.5. China
11.3.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.3.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.6. Japan
11.3.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.6.2. Market Revenue and Forecast, by Technology (2020-2032)
11.3.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.3.7. Rest of APAC
11.3.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.3.7.2. Market Revenue and Forecast, by Technology (2020-2032)
11.3.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.4. MEA
11.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.4. GCC
11.4.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.4.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.5. North Africa
11.4.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.4.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.6. South Africa
11.4.6.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.6.2. Market Revenue and Forecast, by Technology (2020-2032)
11.4.6.3. Market Revenue and Forecast, by Application (2020-2032)
11.4.7. Rest of MEA
11.4.7.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.4.7.2. Market Revenue and Forecast, by Technology (2020-2032)
11.4.7.3. Market Revenue and Forecast, by Application (2020-2032)
11.5. Latin America
11.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.5.3. Market Revenue and Forecast, by Application (2020-2032)
11.5.4. Brazil
11.5.4.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.4.2. Market Revenue and Forecast, by Technology (2020-2032)
11.5.4.3. Market Revenue and Forecast, by Application (2020-2032)
11.5.5. Rest of LATAM
11.5.5.1. Market Revenue and Forecast, by Deployment (2020-2032)
11.5.5.2. Market Revenue and Forecast, by Technology (2020-2032)
11.5.5.3. Market Revenue and Forecast, by Application (2020-2032)
Chapter 12. Company Profiles
12.1. Workday Inc
12.1.1. Company Overview
12.1.2. Product Offerings
12.1.3. Financial Performance
12.1.4. Recent Initiatives
12.2. OpenAI
12.2.1. Company Overview
12.2.2. Product Offerings
12.2.3. Financial Performance
12.2.4. Recent Initiatives
12.3. Microsoft
12.3.1. Company Overview
12.3.2. Product Offerings
12.3.3. Financial Performance
12.3.4. Recent Initiatives
12.4. Adobe
12.4.1. Company Overview
12.4.2. Product Offerings
12.4.3. Financial Performance
12.4.4. Recent Initiatives
12.5. Google
12.5.1. Company Overview
12.5.2. Product Offerings
12.5.3. Financial Performance
12.5.4. Recent Initiatives
12.6. NVIDIA
12.6.1. Company Overview
12.6.2. Product Offerings
12.6.3. Financial Performance
12.6.4. Recent Initiatives
12.7. ADP
12.7.1. Company Overview
12.7.2. Product Offerings
12.7.3. Financial Performance
12.7.4. Recent Initiatives
12.8. IBM
12.8.1. Company Overview
12.8.2. Product Offerings
12.8.3. Financial Performance
12.8.4. Recent Initiatives
12.9. SAP SE
12.9.1. Company Overview
12.9.2. Product Offerings
12.9.3. Financial Performance
12.9.4. Recent Initiatives
12.10. Oracle
12.10.1. Company Overview
12.10.2. Product Offerings
12.10.3. Financial Performance
12.10.4. Recent Initiatives
Chapter 13. Research Methodology
13.1. Primary Research
13.2. Secondary Research
13.3. Assumptions
Chapter 14. Appendix
14.1. About Us
14.2. Glossary of Terms
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