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Generative AI in Data Analytics Market Trends

ID: MRFR/ICT/10663-HCR
128 Pages
Aarti Dhapte
October 2025

Generative AI in Data Analytics Market Research Report: Information 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 Region (North America, Europe, Asia-Pacific, Middle East and Africa and South America) - Forecast Till 2035.

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Market Trends

Key Emerging Trends in the Generative AI in Data Analytics Market

Generative AI, a subset of synthetic intelligence, has been making considerable strides within the data analytics market. Its capability to generate new content, pictures, and even tunes has captured the attention of businesses looking to gain insights from vast amounts of statistics. One of the distinguished market traits of Generative AI is its growing adoption across various industries. Moreover, Generative AI is revolutionizing the way corporations approach facts analysis by permitting them to generate artificial information. This artificial reality may be used to teach system learning fashions, validate algorithms, and conduct thorough testing without compromising the privacy and security of facts. As a result, the demand for Generative AI solutions in the data analytics market is on the upward thrust, with groups in search of innovative approaches to harness the energy of artificial records for progressed insights and selection-making. Another brilliant trend is the combination of Generative AI with natural language processing (NLP) for textual content generation and summarization. This integration permits corporations to system and examine unstructured textual content records extra successfully, mainly through superior sentiment analysis, content era, and automated report summarization. Furthermore, the emergence of generative hostile networks (GANs) has considerably influenced the market trends of Generative AI in data analytics. GANs, a class of gadgets gaining knowledge of structures, pit neural networks against each other to generate new records. This is indistinguishable from actual information. This era has discovered applications in statistics augmentation, anomaly detection, and picture synthesis, offering companies a powerful tool to enhance their data analytics capabilities. As a result, the adoption of GANs and comparable Generative AI strategies is reshaping the data analytics panorama, riding the demand for more robust and versatile Generative AI answers. Additionally, the market traits of Generative AI in data analytics replicate a developing emphasis on the moral and accountable use of AI-generated content material. With the capability to misuse and manipulate generated content, agencies are increasingly prioritizing ethical issues and transparency in their use of Generative AI. This fashion has led to the improvement of suggestions and first-class practices for the ethical deployment of Generative AI in data analytics, making sure that businesses leverage this generation responsibly while retaining records integrity and privacy.

Author
Aarti Dhapte
Team Lead - Research

She holds an experience of about 6+ years in Market Research and Business Consulting, working under the spectrum of Information Communication Technology, Telecommunications and Semiconductor domains. Aarti conceptualizes and implements a scalable business strategy and provides strategic leadership to the clients. Her expertise lies in market estimation, competitive intelligence, pipeline analysis, customer assessment, etc.

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FAQs

What is the projected market valuation for the Generative AI in Data Analytics Market by 2035?

The projected market valuation for the Generative AI in Data Analytics Market by 2035 is 857.4 USD Million.

What was the overall market valuation in 2024?

The overall market valuation for the Generative AI in Data Analytics Market was 5.143 USD Million in 2024.

What is the expected CAGR for the Generative AI in Data Analytics Market from 2025 to 2035?

The expected CAGR for the Generative AI in Data Analytics Market during the forecast period 2025 - 2035 is 59.22%.

Which companies are considered key players in the Generative AI in Data Analytics Market?

Key players in the market include OpenAI, Google, Microsoft, IBM, Salesforce, Amazon, NVIDIA, Palantir Technologies, and DataRobot.

Market Summary

As per MRFR analysis, the Generative AI in Data Analytics Market Size was estimated at 5.143 USD Million in 2024. The Generative AI in Data Analytics industry is projected to grow from 8.188 USD Million in 2025 to 857.4 USD Million by 2035, exhibiting a compound annual growth rate (CAGR) of 59.22 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The Generative AI in Data Analytics Market is experiencing robust growth driven by technological advancements and increasing demand for data insights.

  • North America remains the largest market for Generative AI in Data Analytics Market, showcasing a strong inclination towards cloud-based solutions. Asia-Pacific is emerging as the fastest-growing region, with a notable rise in on-premise deployment of data analytics tools. Natural Language Processing continues to dominate the market, while Machine Learning is rapidly gaining traction as a key segment. The rising demand for data-driven insights and advancements in machine learning algorithms are pivotal drivers propelling market expansion.

Market Size & Forecast

2024 Market Size 5.143 (USD Million)
2035 Market Size 857.4 (USD Million)
CAGR (2025 - 2035) 59.22%
Largest Regional Market Share in 2024 North America

Major Players

<p>OpenAI (US), Google (US), Microsoft (US), IBM (US), Salesforce (US), Amazon (US), NVIDIA (US), Palantir Technologies (US), DataRobot (US)</p>

Market Trends

The Generative AI in Data Analytics Market is currently experiencing a transformative phase, characterized by the integration of advanced algorithms and machine learning techniques. This evolution appears to enhance the ability of organizations to derive actionable insights from vast datasets. As businesses increasingly recognize the value of data-driven decision-making, the demand for generative AI solutions is likely to grow. Companies are exploring innovative applications, which may lead to improved efficiency and effectiveness in various sectors, including finance, healthcare, and marketing. Furthermore, the collaboration between data scientists and AI technologies seems to foster a more dynamic analytical environment, potentially reshaping traditional methodologies. In addition, the Generative AI in Data Analytics Market is witnessing a surge in interest from small and medium-sized enterprises. These organizations are beginning to adopt generative AI tools to level the playing field against larger competitors. The accessibility of cloud-based solutions and user-friendly interfaces may facilitate this trend, allowing smaller firms to harness the power of data analytics without extensive resources. As the landscape evolves, it is essential to monitor how these developments influence market dynamics and the competitive landscape.

Increased Adoption of Cloud Solutions

The shift towards cloud-based platforms is becoming more pronounced in the Generative AI in Data Analytics Market. Organizations are increasingly leveraging cloud infrastructure to enhance scalability and flexibility in their data analytics processes. This trend may enable businesses to access advanced generative AI tools without the burden of significant upfront investments.

Focus on Ethical AI Practices

There is a growing emphasis on ethical considerations within the Generative AI in Data Analytics Market. Stakeholders are becoming more aware of the implications of AI-generated insights, leading to a demand for transparency and accountability. This focus on ethical practices could shape the development and deployment of generative AI technologies.

Integration with IoT Technologies

The convergence of generative AI and Internet of Things (IoT) technologies is emerging as a notable trend. This integration may facilitate real-time data analysis and predictive modeling, enhancing decision-making processes across various industries. As IoT devices proliferate, the potential for generative AI to analyze and interpret data from these sources appears promising.

Generative AI in Data Analytics Market Market Drivers

Rising Demand for Data-Driven Insights

The Generative AI in Data Analytics Market is experiencing a notable surge in demand for data-driven insights. Organizations across various sectors are increasingly recognizing the value of data analytics in driving strategic decision-making. According to recent estimates, the market for data analytics is projected to reach USD 274 billion by 2025, indicating a compound annual growth rate of approximately 30%. This growth is largely fueled by the need for businesses to harness vast amounts of data to gain competitive advantages. Generative AI technologies are particularly well-suited for this purpose, as they can analyze complex datasets and generate actionable insights. Consequently, the integration of generative AI into data analytics is becoming a critical component for organizations aiming to enhance their operational efficiency and market positioning.

Expansion of Use Cases Across Industries

The Generative AI in Data Analytics Market is characterized by the expansion of use cases across various industries. From healthcare to finance, organizations are increasingly leveraging generative AI to enhance their data analytics capabilities. For instance, in healthcare, generative AI is utilized for predictive analytics to improve patient outcomes, while in finance, it aids in risk assessment and fraud detection. This diversification of applications is driving market growth, with projections indicating that the adoption of generative AI in data analytics could lead to a market value of USD 30 billion by 2026. As industries continue to explore innovative applications of generative AI, the demand for advanced data analytics solutions is likely to increase.

Growing Importance of Real-Time Analytics

The Generative AI in Data Analytics Market is witnessing a growing emphasis on real-time analytics. In an era where timely decision-making is paramount, organizations are increasingly seeking solutions that provide immediate insights from their data. Generative AI technologies facilitate real-time data processing and analysis, enabling businesses to respond swiftly to market changes and customer needs. This shift towards real-time analytics is reflected in market trends, with a projected increase in demand for real-time data solutions expected to reach USD 15 billion by 2025. As organizations strive to enhance their agility and responsiveness, the integration of generative AI into data analytics is becoming essential for maintaining a competitive edge.

Advancements in Machine Learning Algorithms

The Generative AI in Data Analytics Market is significantly influenced by advancements in machine learning algorithms. These innovations enable more sophisticated data analysis techniques, allowing organizations to extract deeper insights from their data. Recent developments in deep learning and neural networks have enhanced the capabilities of generative AI, making it possible to analyze unstructured data more effectively. As a result, businesses are increasingly adopting these technologies to improve their data analytics processes. The market for machine learning in data analytics is expected to grow substantially, with projections indicating a potential increase to USD 20 billion by 2026. This trend suggests that organizations are prioritizing investments in generative AI solutions to leverage the full potential of their data.

Increased Focus on Data Privacy and Security

The Generative AI in Data Analytics Market is also shaped by an increased focus on data privacy and security. As organizations collect and analyze vast amounts of data, concerns regarding data breaches and compliance with regulations have intensified. Generative AI technologies can play a pivotal role in addressing these concerns by providing advanced security measures and ensuring data integrity. The market for data privacy solutions is projected to grow significantly, with estimates suggesting a potential value of USD 12 billion by 2025. This trend indicates that organizations are prioritizing the implementation of generative AI solutions that not only enhance data analytics capabilities but also safeguard sensitive information.

Market Segment Insights

By Deployment: Cloud-Based (Largest) vs. On-premise (Fastest-Growing)

<p>In the Generative AI in Data Analytics Market, the deployment segment showcases a clear distinction in market share distribution. The Cloud-Based deployment model holds a substantial share, primarily due to its scalability, cost efficiency, and the ability to leverage vast computational resources in real-time. This trend is driven by the increasing number of businesses that prefer flexible solutions over traditional infrastructure, making Cloud-Based analytics a mainstream choice for many organizations.</p>

<p>Deployment: Cloud-Based (Dominant) vs. On-premise (Emerging)</p>

<p>The Cloud-Based deployment model is the dominant player in the Generative AI in Data Analytics Market due to its extensive adoption driven by ease of use and rapid deployment capabilities. Cloud solutions enable organizations to access and analyze large datasets without investing heavily in physical infrastructure. On the other hand, the On-premise deployment is emerging, often preferred by organizations with stringent data security and compliance requirements. Companies adopting On-premise solutions are increasingly looking to adopt AI capabilities, driven by the need for tailored analytics capabilities and control over their data. As both segments evolve, the balance between convenience and control remains a key factor for businesses.</p>

By Technology: Natural Language Processing (Largest) vs. Machine Learning (Fastest-Growing)

<p>The Generative AI in Data Analytics Market displays a significant market share distribution among its core technologies. Natural Language Processing (NLP) holds the largest share, driven by the increasing demand for enhanced communication and data interpretation. NLP's ability to understand and generate human-like language has made it a crucial component in data analytics solutions. In contrast, Machine Learning is rapidly gaining traction, emerging as the fastest-growing segment. Its capacity to analyze vast datasets and provide predictive insights makes it indispensable in today's data-driven landscape.</p>

<p>Technology: NLP (Dominant) vs. Machine Learning (Emerging)</p>

<p>Natural Language Processing (NLP) is the dominant technology in the Generative AI in Data Analytics Market, renowned for its ability to facilitate seamless interaction between humans and machines. Organizations leverage NLP to convert vast amounts of textual data into actionable insights, enhancing decision-making processes and customer engagement. On the other hand, Machine Learning is positioned as an emerging technology, showcasing remarkable potential for growth. It enables systems to learn from data patterns, making predictive analysis more efficient and accurate. The synergy between NLP and Machine Learning is pivotal, as both technologies complement each other to unlock new capabilities and drive innovation across industries.</p>

By Application: Anomaly Detection (Largest) vs. Data Augmentation (Fastest-Growing)

<p>In the Generative AI in Data Analytics Market, anomaly detection holds the largest share, serving as a cornerstone for industries seeking to maintain data integrity and security. Data augmentation, while currently smaller in share, is rapidly gaining traction as organizations increasingly rely on diverse datasets to enhance model training and predictive accuracy. Other applications, such as text generation and simulation and forecasting, also contribute to the segment's robustness, but they represent a smaller portion of the overall market share. Growth trends indicate that demand for <a href="https://www.marketresearchfuture.com/reports/anomaly-detection-market-5756">anomaly detection</a> is driven by the need for real-time insights and fraud prevention, especially in finance and cybersecurity sectors. On the other hand, data augmentation's growth is fueled by the surge in machine learning applications, where quality datasets are essential for model performance. As businesses leverage generative AI capabilities across their analytics processes, both segments are poised for significant development in the coming years.</p>

<p>Data Augmentation (Emerging) vs. Anomaly Detection (Dominant)</p>

<p>Data augmentation is emerging as a critical tool in the Generative AI in Data Analytics Market, enabling organizations to improve training processes for machine learning models by expanding and diversifying datasets without requiring additional data collection. In contrast, anomaly detection remains dominant, essential for organizations needing immediate identification of unusual patterns that could indicate threats or inefficiencies. While data augmentation is capturing investor interest and experiencing rapid adoption as its capabilities become more recognized, anomaly detection continues to benefit from clear use cases in various industries, solidifying its position as a foundational element in data analytics strategy.</p>

Get more detailed insights about Generative AI in Data Analytics Market Research Report – Forecast till 2035

Regional Insights

North America : Innovation and Leadership Hub

North America is the largest market for Generative AI in Data Analytics Market, holding approximately 45% of the global market share. The region's growth is driven by rapid technological advancements, high investment in AI research, and a strong presence of tech giants. Regulatory support for AI innovation further fuels demand, with initiatives aimed at fostering responsible AI development and deployment. The United States leads the market, with key players like OpenAI, Google, and Microsoft driving innovation. Canada also plays a significant role, focusing on AI ethics and governance. The competitive landscape is characterized by continuous advancements in AI capabilities, with companies investing heavily in R&D to maintain their edge in the market. The presence of major tech firms ensures a robust ecosystem for AI development.

Europe : Emerging AI Powerhouse

Europe is rapidly emerging as a significant player in the Generative AI in Data Analytics Market, holding around 30% of the global market share. The region's growth is propelled by increasing demand for AI-driven insights across various sectors, coupled with strong regulatory frameworks that promote ethical AI use. The European Union's initiatives to enhance digital transformation and AI adoption are key catalysts for market expansion. Leading countries include Germany, France, and the UK, each fostering a vibrant AI ecosystem. The competitive landscape features both established firms and innovative startups, with companies like SAP and Siemens investing in AI capabilities. The presence of regulatory bodies ensures that AI development aligns with ethical standards, further enhancing consumer trust and market growth.

Asia-Pacific : Rapid Growth and Adoption

Asia-Pacific is witnessing rapid growth in the Generative AI in Data Analytics Market, accounting for approximately 20% of the global market share. The region's expansion is driven by increasing digitalization, a growing number of startups, and significant investments in AI technologies. Countries like China and India are at the forefront, with government initiatives aimed at fostering AI innovation and adoption across various industries. China is leading the charge, supported by major tech companies like Alibaba and Tencent, while India is emerging as a hub for AI talent and innovation. The competitive landscape is diverse, with a mix of established players and new entrants. The region's focus on AI research and development is expected to further enhance its market position in the coming years, making it a key player in the global AI landscape.

Middle East and Africa : Resource-Rich Frontier

The Middle East and Africa region is gradually emerging in the Generative AI in Data Analytics Market, holding about 5% of the global market share. The growth is driven by increasing investments in technology and a rising demand for data-driven decision-making across various sectors. Governments in the region are actively promoting digital transformation initiatives, which are crucial for fostering AI adoption and innovation. Countries like the UAE and South Africa are leading the way, with significant investments in AI infrastructure and talent development. The competitive landscape is evolving, with both local and international players entering the market. The region's unique challenges and opportunities present a dynamic environment for AI growth, making it an area to watch in the coming years.

Key Players and Competitive Insights

The Generative AI in Data Analytics Market is currently characterized by a dynamic competitive landscape, driven by rapid technological advancements and increasing demand for data-driven insights across various sectors. Major players such as OpenAI (US), Google (US), and Microsoft (US) are at the forefront, leveraging their extensive resources and expertise to innovate and expand their offerings. OpenAI (US) focuses on enhancing its AI models to provide more accurate predictive analytics, while Google (US) emphasizes integrating generative AI capabilities into its cloud services, thereby enhancing user experience and operational efficiency. Microsoft (US) is strategically positioning itself through partnerships and acquisitions, aiming to embed AI functionalities into its existing software ecosystem, which collectively shapes a competitive environment that is increasingly reliant on innovation and strategic collaborations.

The market structure appears moderately fragmented, with a mix of established players and emerging startups. Key business tactics such as localizing services and optimizing supply chains are becoming prevalent as companies seek to enhance their operational efficiency and responsiveness to market demands. The collective influence of these major players is significant, as they not only set industry standards but also drive the pace of technological adoption and innovation within the sector.

In August 2025, OpenAI (US) announced a partnership with a leading financial services firm to develop AI-driven analytics tools aimed at improving risk assessment and decision-making processes. This strategic move underscores OpenAI's commitment to applying generative AI in practical, high-stakes environments, potentially revolutionizing how financial institutions leverage data analytics for competitive advantage. The collaboration is likely to enhance OpenAI's credibility in the financial sector, opening avenues for further partnerships and applications.

In September 2025, Google (US) unveiled a new suite of generative AI tools designed specifically for small and medium-sized enterprises (SMEs). This initiative reflects Google's strategy to democratize access to advanced analytics capabilities, enabling SMEs to harness the power of AI without substantial investment. By targeting this segment, Google not only expands its market reach but also fosters innovation among smaller players, which could lead to a more diverse competitive landscape.

In October 2025, Microsoft (US) launched an AI-driven analytics platform that integrates seamlessly with its existing cloud services, aimed at enhancing data visualization and predictive capabilities for businesses. This launch is indicative of Microsoft's strategy to create a comprehensive ecosystem that supports businesses in their digital transformation journeys. By providing integrated solutions, Microsoft positions itself as a leader in the generative AI space, likely increasing customer loyalty and market share.

As of October 2025, current competitive trends in the Generative AI in Data Analytics Market are heavily influenced by digitalization, sustainability, and the integration of AI technologies. Strategic alliances are increasingly shaping the landscape, as companies recognize the value of collaboration in driving innovation and expanding their capabilities. Looking ahead, competitive differentiation is expected to evolve, with a notable shift from price-based competition to a focus on innovation, technological advancement, and supply chain reliability. This transition suggests that companies that prioritize these elements will likely emerge as leaders in the market.

Key Companies in the Generative AI in Data Analytics Market market include

Industry Developments

  • Q2 2024: Databricks acquires Tabular to expand data lakehouse and AI capabilities Databricks announced the acquisition of Tabular, a data management startup, to enhance its data lakehouse platform and strengthen its generative AI and analytics offerings.
  • Q2 2024: Snowflake and Nvidia Partner to Bring Generative AI to Enterprise Data Snowflake and Nvidia announced a partnership to integrate Nvidia’s NeMo platform with Snowflake’s Data Cloud, enabling enterprises to build custom generative AI models using their proprietary data.
  • Q2 2024: Dataiku raises $200M in Series F funding to accelerate generative AI analytics Dataiku secured $200 million in Series F funding to further develop its generative AI-powered data analytics platform and expand its global operations.
  • Q3 2024: Microsoft launches Copilot for Power BI, bringing generative AI to business analytics Microsoft introduced Copilot for Power BI, a generative AI assistant designed to help users create data visualizations and insights using natural language queries.
  • Q3 2024: Google Cloud unveils Gemini AI for BigQuery to automate data analytics Google Cloud launched Gemini AI for BigQuery, a generative AI tool that automates data analysis and report generation for enterprise customers.
  • Q3 2024: Alteryx Appoints Suresh Vittal as Chief Product Officer to Drive Generative AI Strategy Alteryx announced the appointment of Suresh Vittal as Chief Product Officer, tasking him with leading the company’s generative AI and analytics product roadmap.
  • Q4 2024: ThoughtSpot acquires Mode Analytics to boost AI-driven data analytics ThoughtSpot completed the acquisition of Mode Analytics, aiming to enhance its generative AI capabilities for business intelligence and data analytics.
  • Q4 2024: Qlik launches Qlik Staige, a generative AI platform for enterprise analytics Qlik announced the launch of Qlik Staige, a new generative AI platform designed to help enterprises automate data analysis and generate insights using natural language.
  • Q1 2025: SAP and OpenAI announce partnership to embed generative AI in SAP Analytics Cloud SAP and OpenAI revealed a strategic partnership to integrate OpenAI’s generative AI models into SAP Analytics Cloud, enabling advanced data analysis and reporting features.
  • Q1 2025: Oracle launches AI-powered analytics suite for enterprise customers Oracle introduced a new suite of AI-powered analytics tools, leveraging generative AI to automate data preparation, analysis, and visualization for business users.
  • Q2 2025: Palantir launches AIP Data Analyst, a generative AI tool for enterprise analytics Palantir announced the launch of AIP Data Analyst, a generative AI-powered tool designed to help enterprises automate data exploration and generate actionable insights.
  • Q2 2025: Salesforce unveils Einstein Copilot for Tableau, bringing generative AI to data visualization Salesforce launched Einstein Copilot for Tableau, a generative AI assistant that enables users to create data visualizations and dashboards using conversational queries.

Future Outlook

Generative AI in Data Analytics Market Future Outlook

<p>The Generative AI in Data Analytics Market is projected to grow at a 59.22% CAGR from 2024 to 2035, driven by advancements in machine learning, increased data generation, and demand for real-time insights.</p>

New opportunities lie in:

  • <p>Development of AI-driven predictive analytics tools for retail optimization.</p><p>Creation of customized generative AI solutions for healthcare data management.</p><p>Integration of generative AI in financial forecasting platforms for enhanced decision-making.</p>

<p>By 2035, the market is expected to be a cornerstone of data-driven decision-making across industries.</p>

Market Segmentation

Generative AI in Data Analytics Market Deployment Outlook

  • Cloud-Based
  • On-premise

Generative AI in Data Analytics Market Technology Outlook

  • Natural Language Processing
  • Machine learning
  • Computer vision
  • Deep learning
  • Robotic Process Automation

Generative AI in Data Analytics Market Application Outlook

  • Data Augmentation
  • Text Generation
  • Anomaly Detection
  • Simulation and Forecasting

Report Scope

MARKET SIZE 20245.143(USD Million)
MARKET SIZE 20258.188(USD Million)
MARKET SIZE 2035857.4(USD Million)
COMPOUND ANNUAL GROWTH RATE (CAGR)59.22% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Million
Key Companies ProfiledMarket analysis in progress
Segments CoveredMarket segmentation analysis in progress
Key Market OpportunitiesIntegration of Generative AI enhances predictive analytics capabilities, driving efficiency in data-driven decision-making.
Key Market DynamicsRising demand for advanced analytics drives competition and innovation in the Generative AI in Data Analytics Market.
Countries CoveredNorth America, Europe, APAC, South America, MEA

FAQs

What is the projected market valuation for the Generative AI in Data Analytics Market by 2035?

The projected market valuation for the Generative AI in Data Analytics Market by 2035 is 857.4 USD Million.

What was the overall market valuation in 2024?

The overall market valuation for the Generative AI in Data Analytics Market was 5.143 USD Million in 2024.

What is the expected CAGR for the Generative AI in Data Analytics Market from 2025 to 2035?

The expected CAGR for the Generative AI in Data Analytics Market during the forecast period 2025 - 2035 is 59.22%.

Which companies are considered key players in the Generative AI in Data Analytics Market?

Key players in the market include OpenAI, Google, Microsoft, IBM, Salesforce, Amazon, NVIDIA, Palantir Technologies, and DataRobot.

  1. SECTION I: EXECUTIVE SUMMARY AND KEY HIGHLIGHTS
    1. EXECUTIVE SUMMARY
      1. Market Overview
      2. Key Findings
      3. Market Segmentation
      4. Competitive Landscape
      5. Challenges and Opportunities
      6. Future Outlook 2
  2. SECTION II: SCOPING, METHODOLOGY AND MARKET STRUCTURE
    1. MARKET INTRODUCTION
      1. Definition
      2. Scope of the study
    2. RESEARCH METHODOLOGY
      1. Overview
      2. Data Mining
      3. Secondary Research
      4. Primary Research
      5. Forecasting Model
      6. Market Size Estimation
      7. Data Triangulation
      8. Validation 3
  3. SECTION III: QUALITATIVE ANALYSIS
    1. MARKET DYNAMICS
      1. Overview
      2. Drivers
      3. Restraints
      4. Opportunities
    2. MARKET FACTOR ANALYSIS
      1. Value chain Analysis
      2. Porter's Five Forces Analysis
      3. COVID-19 Impact Analysis
  4. SECTION IV: QUANTITATIVE ANALYSIS
    1. Information and Communications Technology, BY Deployment (USD Million)
      1. Cloud-Based
      2. On-premise
    2. Information and Communications Technology, BY Technology (USD Million)
      1. Natural Language Processing
      2. Machine learning
      3. Computer vision
      4. Deep learning
      5. Robotic Process Automation
    3. Information and Communications Technology, BY Application (USD Million)
      1. Data Augmentation
      2. Text Generation
      3. Anomaly Detection
      4. Simulation and Forecasting
    4. Information and Communications Technology, BY Region (USD Million)
      1. North America
      2. Europe
      3. APAC
      4. South America
      5. MEA
  5. SECTION V: COMPETITIVE ANALYSIS
    1. Competitive Landscape
      1. Overview
      2. Competitive Analysis
      3. Market share Analysis
      4. Major Growth Strategy in the Information and Communications Technology
      5. Competitive Benchmarking
      6. Leading Players in Terms of Number of Developments in the Information and Communications Technology
      7. Key developments and growth strategies
      8. Major Players Financial Matrix
    2. Company Profiles
      1. OpenAI (US)
      2. Google (US)
      3. Microsoft (US)
      4. IBM (US)
      5. Salesforce (US)
      6. Amazon (US)
      7. NVIDIA (US)
      8. Palantir Technologies (US)
      9. DataRobot (US)
    3. Appendix
      1. References
      2. Related Reports 6 LIST OF FIGURES
    4. MARKET SYNOPSIS
    5. NORTH AMERICA MARKET ANALYSIS
    6. US MARKET ANALYSIS BY DEPLOYMENT
    7. US MARKET ANALYSIS BY TECHNOLOGY
    8. US MARKET ANALYSIS BY APPLICATION
    9. CANADA MARKET ANALYSIS BY DEPLOYMENT
    10. CANADA MARKET ANALYSIS BY TECHNOLOGY
    11. CANADA MARKET ANALYSIS BY APPLICATION
    12. EUROPE MARKET ANALYSIS
    13. GERMANY MARKET ANALYSIS BY DEPLOYMENT
    14. GERMANY MARKET ANALYSIS BY TECHNOLOGY
    15. GERMANY MARKET ANALYSIS BY APPLICATION
    16. UK MARKET ANALYSIS BY DEPLOYMENT
    17. UK MARKET ANALYSIS BY TECHNOLOGY
    18. UK MARKET ANALYSIS BY APPLICATION
    19. FRANCE MARKET ANALYSIS BY DEPLOYMENT
    20. FRANCE MARKET ANALYSIS BY TECHNOLOGY
    21. FRANCE MARKET ANALYSIS BY APPLICATION
    22. RUSSIA MARKET ANALYSIS BY DEPLOYMENT
    23. RUSSIA MARKET ANALYSIS BY TECHNOLOGY
    24. RUSSIA MARKET ANALYSIS BY APPLICATION
    25. ITALY MARKET ANALYSIS BY DEPLOYMENT
    26. ITALY MARKET ANALYSIS BY TECHNOLOGY
    27. ITALY MARKET ANALYSIS BY APPLICATION
    28. SPAIN MARKET ANALYSIS BY DEPLOYMENT
    29. SPAIN MARKET ANALYSIS BY TECHNOLOGY
    30. SPAIN MARKET ANALYSIS BY APPLICATION
    31. REST OF EUROPE MARKET ANALYSIS BY DEPLOYMENT
    32. REST OF EUROPE MARKET ANALYSIS BY TECHNOLOGY
    33. REST OF EUROPE MARKET ANALYSIS BY APPLICATION
    34. APAC MARKET ANALYSIS
    35. CHINA MARKET ANALYSIS BY DEPLOYMENT
    36. CHINA MARKET ANALYSIS BY TECHNOLOGY
    37. CHINA MARKET ANALYSIS BY APPLICATION
    38. INDIA MARKET ANALYSIS BY DEPLOYMENT
    39. INDIA MARKET ANALYSIS BY TECHNOLOGY
    40. INDIA MARKET ANALYSIS BY APPLICATION
    41. JAPAN MARKET ANALYSIS BY DEPLOYMENT
    42. JAPAN MARKET ANALYSIS BY TECHNOLOGY
    43. JAPAN MARKET ANALYSIS BY APPLICATION
    44. SOUTH KOREA MARKET ANALYSIS BY DEPLOYMENT
    45. SOUTH KOREA MARKET ANALYSIS BY TECHNOLOGY
    46. SOUTH KOREA MARKET ANALYSIS BY APPLICATION
    47. MALAYSIA MARKET ANALYSIS BY DEPLOYMENT
    48. MALAYSIA MARKET ANALYSIS BY TECHNOLOGY
    49. MALAYSIA MARKET ANALYSIS BY APPLICATION
    50. THAILAND MARKET ANALYSIS BY DEPLOYMENT
    51. THAILAND MARKET ANALYSIS BY TECHNOLOGY
    52. THAILAND MARKET ANALYSIS BY APPLICATION
    53. INDONESIA MARKET ANALYSIS BY DEPLOYMENT
    54. INDONESIA MARKET ANALYSIS BY TECHNOLOGY
    55. INDONESIA MARKET ANALYSIS BY APPLICATION
    56. REST OF APAC MARKET ANALYSIS BY DEPLOYMENT
    57. REST OF APAC MARKET ANALYSIS BY TECHNOLOGY
    58. REST OF APAC MARKET ANALYSIS BY APPLICATION
    59. SOUTH AMERICA MARKET ANALYSIS
    60. BRAZIL MARKET ANALYSIS BY DEPLOYMENT
    61. BRAZIL MARKET ANALYSIS BY TECHNOLOGY
    62. BRAZIL MARKET ANALYSIS BY APPLICATION
    63. MEXICO MARKET ANALYSIS BY DEPLOYMENT
    64. MEXICO MARKET ANALYSIS BY TECHNOLOGY
    65. MEXICO MARKET ANALYSIS BY APPLICATION
    66. ARGENTINA MARKET ANALYSIS BY DEPLOYMENT
    67. ARGENTINA MARKET ANALYSIS BY TECHNOLOGY
    68. ARGENTINA MARKET ANALYSIS BY APPLICATION
    69. REST OF SOUTH AMERICA MARKET ANALYSIS BY DEPLOYMENT
    70. REST OF SOUTH AMERICA MARKET ANALYSIS BY TECHNOLOGY
    71. REST OF SOUTH AMERICA MARKET ANALYSIS BY APPLICATION
    72. MEA MARKET ANALYSIS
    73. GCC COUNTRIES MARKET ANALYSIS BY DEPLOYMENT
    74. GCC COUNTRIES MARKET ANALYSIS BY TECHNOLOGY
    75. GCC COUNTRIES MARKET ANALYSIS BY APPLICATION
    76. SOUTH AFRICA MARKET ANALYSIS BY DEPLOYMENT
    77. SOUTH AFRICA MARKET ANALYSIS BY TECHNOLOGY
    78. SOUTH AFRICA MARKET ANALYSIS BY APPLICATION
    79. REST OF MEA MARKET ANALYSIS BY DEPLOYMENT
    80. REST OF MEA MARKET ANALYSIS BY TECHNOLOGY
    81. REST OF MEA MARKET ANALYSIS BY APPLICATION
    82. KEY BUYING CRITERIA OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
    83. RESEARCH PROCESS OF MRFR
    84. DRO ANALYSIS OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
    85. DRIVERS IMPACT ANALYSIS: INFORMATION AND COMMUNICATIONS TECHNOLOGY
    86. RESTRAINTS IMPACT ANALYSIS: INFORMATION AND COMMUNICATIONS TECHNOLOGY
    87. SUPPLY / VALUE CHAIN: INFORMATION AND COMMUNICATIONS TECHNOLOGY
    88. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY DEPLOYMENT, 2024 (% SHARE)
    89. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY DEPLOYMENT, 2024 TO 2035 (USD Million)
    90. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY TECHNOLOGY, 2024 (% SHARE)
    91. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY TECHNOLOGY, 2024 TO 2035 (USD Million)
    92. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY APPLICATION, 2024 (% SHARE)
    93. INFORMATION AND COMMUNICATIONS TECHNOLOGY, BY APPLICATION, 2024 TO 2035 (USD Million)
    94. BENCHMARKING OF MAJOR COMPETITORS 7 LIST OF TABLES
    95. LIST OF ASSUMPTIONS
    96. North America MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    97. US MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    98. Canada MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    99. Europe MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    100. Germany MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    101. UK MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    102. France MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    103. Russia MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    104. Italy MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    105. Spain MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    106. Rest of Europe MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    107. APAC MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    108. China MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    109. India MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    110. Japan MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    111. South Korea MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    112. Malaysia MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    113. Thailand MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    114. Indonesia MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    115. Rest of APAC MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    116. South America MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    117. Brazil MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    118. Mexico MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    119. Argentina MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    120. Rest of South America MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    121. MEA MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    122. GCC Countries MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    123. South Africa MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    124. Rest of MEA MARKET SIZE ESTIMATES; FORECAST
      1. BY DEPLOYMENT, 2025-2035 (USD Million)
      2. BY TECHNOLOGY, 2025-2035 (USD Million)
      3. BY APPLICATION, 2025-2035 (USD Million)
    125. PRODUCT LAUNCH/PRODUCT DEVELOPMENT/APPROVAL
    126. ACQUISITION/PARTNERSHIP

Generative AI in Data Analytics Market Segmentation

Market Segmentation Overview

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  • Comprehensive analysis by multiple parameters
  • Regional and country-level breakdowns
  • Market size forecasts by segment
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