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市場調查報告書
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1959892

分析領域生成式人工智慧市場－全球產業規模、佔有率、趨勢、機會、預測：按部署、技術、應用、地區和競爭格局分類，2021-2031年

Generative AI in Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Deployment, By Technology, By Application, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球分析領域的生成式人工智慧市場預計將經歷顯著成長，從 2025 年的 13.9 億美元成長到 2031 年的 60.6 億美元，複合年成長率為 27.81%。

該領域利用先進的機器學習模型，透過自然語言介面自主解讀資料集，產生程式碼和洞見。其主要成長促進因素包括“數據民主化”，使業務用戶無需技術技能即可訪問複雜資訊；以及對非結構化數據處理的需求，以支援快速戰略規劃。這些並非曇花一現的趨勢，而是旨在滿足企業營運的基本需求，最大限度地縮短從企業資料中提取價值所需的時間。

市場概覽
預測期 2027-2031
市場規模：2025年 13.9億美元
市場規模：2031年 60.6億美元
複合年成長率：2026-2031年 27.81%
成長最快的細分市場 基於雲端的
最大的市場 北美洲

然而，市場在模型輸出的準確性和資料管治風險方面面臨著許多挑戰，這可能會削弱企業的信心。企業難以確保自動化洞察的可靠性足以支援關鍵業務運營，這往往阻礙了規模化發展。儘管有這些挑戰，業界的決心依然堅定不移。 IEEE 2024 年的報告顯示，65% 的技術主管將人工智慧（包括生成式人工智慧）列為首要任務。這項數據凸顯了業界克服現有障礙、推動未來應用的堅定決心。

市場促進因素

透過自然語言介面實現數據存取的民主化，正在從根本上重塑市場格局，降低高階分析的進入門檻。透過互動式提示對複雜資料集進行查詢，企業能夠讓非技術人員無需依賴專業的資料科學團隊即可獲得可操作的洞察。這種轉變加快了決策速度，並在各個業務職能部門中培養了以數據為中心的文化。根據Google雲端於2024年4月發布的《2024年數據與人工智慧趨勢報告》，84%的數據決策者認為生成式人工智慧將有助於更快地獲取洞察，這凸顯了建立更易於使用的分析框架的趨勢。

此外，分析和提取非結構化資料價值的能力顯著提升，是推動人工智慧發展的關鍵因素，使企業能夠利用以往無法獲得的資訊來源，例如客戶回饋、電子郵件和合約。生成式人工智慧模型能夠有效處理這些定性訊息，發現傳統結構化工具難以發現的模式和異常情況，從而直接提升業務績效。其影響是可以衡量的。凱捷研究院 (Capigemini Research Institute) 於 2024 年 9 月發布的報告《發揮生成式人工智慧的價值：第二版》顯示，採用該技術的組織生產力提高了 7.8%。此外，IBM 在 2024 年發布的報告顯示，42% 的企業級組織正在積極採用人工智慧，顯示這項技術正日益融入企業營運。

市場挑戰

全球生成式人工智慧分析市場的主要限制因素是模型輸出準確性的固有不確定性以及重大的資料管治風險。在商業分析領域，準確性對策略至關重要，而生成式模型往往會產生看似合理但不準確的資訊（即所謂的「幻覺」），這導致其可靠性嚴重不足。這種可靠性的缺失削弱了速度和自動化的價值，迫使企業實施嚴格且耗時的人工檢驗流程。此外，對資料外洩的擔憂以及缺乏透明的管治框架也阻礙了企業在敏感工作流程中應用這些工具，通常只能將其應用於試驗計畫，而無法進行全面部署。

行業數據顯示專家普遍擔憂，進一步加劇了這種擔憂。根據ISACA 2024年的調查，81%的數位可信度專家認為，假資訊和錯誤資訊是人工智慧面臨的最大風險。這種高度的不信任感阻礙了生成式分析技術在關鍵業務功能的應用。因此，由於企業優先考慮風險規避而非創新，在進行全公司範圍部署之前，他們會等待模型可信度和安全性標準得到確立，從而阻礙了市場成長。

市場趨勢

自主代理人工智慧的興起正在將分析從被動的報告工具​​轉變為主動的、自我糾錯的運作層。與每一步都依賴人工指令的傳統模型不同，這些代理能夠自主規劃、說明和執行程式碼來清理資料集，並迭代改進輸出以確保準確性。這種能力透過減少傳統複雜資料處理所需的人工監控，滿足了可靠自動化工作流程的需求。 Salesforce 於銷售團隊年 9 月發布的《基於代理的企業指數》清晰地反映了這項技術的快速普及，該指數顯示，早期採用者在今年上半年創建人工智慧代理的數量激增了 119%，表明企業正在向自動化決策系統轉型。

同時，合成資料的普及正在解決與隱私保護和模型訓練限制相關的關鍵瓶頸。隨著企業面臨日益嚴格的管治通訊協定，合成資料集能夠在不洩露敏感客戶資訊或智慧財產權的情況下訓練出強大的分析模型。這種方法不僅降低了合規風險，還彌補了歷史數據的不足，並有助於更全面的場景模擬。金融業是這項隱私增強技術的主要應用領域。根據英偉達於2025年2月發布的《金融服務業人工智慧現況》報告，46%的受訪機構已採用合成資料生成技術，凸顯了其在安全檢驗分析策略方面日益重要的角色。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：分析領域生成式人工智慧的全球市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 部署方式（雲端部署、本機部署）
    • 透過科技（自然語言處理、機器學習、深度學習等）
    • 依應用領域（預測、自動報告產生、異常檢測、個人化）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美分析領域生成式人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國別分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲分析領域生成式人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國別分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太地區分析領域生成式人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國別分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲分析​​領域生成式人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東與非洲：國別分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美分析領域生成式人工智慧市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國別分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進因素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 近期趨勢

第13章：全球生成式人工智慧分析市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的潛力
  • 供應商的議價能力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • OpenAI OpCo, LLC
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services, Inc.
  • NVIDIA Corporation
  • Salesforce, Inc.
  • SAP SE
  • Oracle Corporation
  • Palantir Technologies Inc.
  • DataRobot, Inc.
  • H2O.ai, Inc.

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 24916

The Global Generative AI in Analytics Market is projected to experience substantial growth, expanding from USD 1.39 Billion in 2025 to USD 6.06 Billion by 2031, reflecting a CAGR of 27.81%. This sector involves sophisticated machine learning models that utilize natural language interfaces to autonomously interpret datasets and generate code or insights. Growth is primarily driven by the push for data democratization, which enables business users to access complex information without technical skills, and the need to process unstructured data for rapid strategic planning. Rather than being fleeting trends, these drivers address the fundamental operational requirement of minimizing the time needed to extract value from enterprise information.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 1.39 Billion
Market Size 2031USD 6.06 Billion
CAGR 2026-203127.81%
Fastest Growing SegmentCloud Based
Largest MarketNorth America

However, the market faces significant hurdles related to the accuracy of model outputs and data governance risks, which threaten to undermine organizational trust. Enterprises struggle to ensure that automated insights are sufficiently reliable for critical business operations, often impeding expansion. Despite these challenges, industry commitment remains steadfast. As reported by the IEEE in 2024, 65% of technology executives identified artificial intelligence, including generative forms, as a top priority. This statistic highlights a strong intent to overcome existing barriers and drive future implementation.

Market Driver

The democratization of data access via natural language interfaces is fundamentally reshaping the market by reducing the entry barriers for advanced analytics. By allowing users to query complex datasets using conversational prompts, organizations empower non-technical staff to obtain actionable intelligence without depending on specialized data science teams. This transition accelerates decision-making and cultivates a data-centric culture across business functions. According to Google Cloud's 'Data and AI Trends Report 2024' from April 2024, 84% of data decision-makers believe generative AI will facilitate faster access to insights, confirming the momentum toward more accessible analytical frameworks.

Additionally, the enhanced capability to analyze and extract value from unstructured data is a vital driver, enabling enterprises to utilize previously inaccessible sources such as customer feedback, emails, and contracts. Generative AI models effectively process this qualitative information to uncover patterns and anomalies that traditional structured tools miss, leading to direct operational improvements. The impact is measurable; the Capgemini Research Institute's 'Harnessing the value of generative AI: 2nd edition' report from September 2024 noted a 7.8% productivity increase among implementing organizations. Furthermore, IBM reported in 2024 that 42% of enterprise-scale organizations have actively deployed AI, demonstrating the technology's widening operational integration.

Market Challenge

The primary obstacle constraining the Global Generative AI in Analytics Market is the inherent uncertainty regarding the accuracy of model outputs alongside significant data governance risks. In the realm of business analytics, where precision is vital for strategy, the tendency of generative models to produce plausible but incorrect information-known as hallucinations-creates a major trust deficit. This unreliability undermines the value of speed and automation, as organizations are compelled to institute rigorous, time-consuming human validation processes. Moreover, concerns over data leakage and the lack of transparent governance frameworks prevent enterprises from applying these tools in sensitive workflows, often limiting their use to pilot programs rather than full deployment.

This apprehension is reinforced by industry data showing widespread caution among professionals. According to ISACA in 2024, 81% of digital trust professionals cited misinformation and disinformation as the most significant risks associated with artificial intelligence. This high level of distrust causes companies to delay adopting generative analytics for essential business functions. Consequently, market growth is throttled as organizations prioritize risk mitigation over innovation, waiting for established standards of model reliability and security before committing to enterprise-wide implementation.

Market Trends

The rise of autonomous agentic AI is shifting analytics from a passive reporting tool into an active, self-correcting operational layer. Unlike traditional models that rely on human prompts for each step, these agents can autonomously devise plans, write and execute code to clean datasets, and iteratively refine their outputs to ensure precision. This capability meets the demand for reliable automated workflows by reducing the manual oversight previously necessary for complex data tasks. The rapid adoption of this technology is evident in Salesforce's 'Agentic Enterprise Index' from September 2025, which noted a 119% surge in AI agent creation among early adopters in the first half of the year, signaling a move toward automated decision-making systems.

Simultaneously, the widespread use of synthetic data is resolving key bottlenecks related to privacy preservation and model training limitations. As enterprises encounter stricter governance protocols, synthetic datasets enable the training of robust analytical models without exposing sensitive customer information or intellectual property. This method not only lowers compliance risks but also bridges gaps in historical data, facilitating more comprehensive scenario simulations. The financial sector is a leading adopter of this privacy-enhancing technique; according to NVIDIA's 'State of AI in Financial Services' report from February 2025, 46% of surveyed organizations have adopted synthetic data generation, underscoring its growing role in securely validating analytical strategies.

Key Market Players

  • OpenAI OpCo, LLC
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services, Inc.
  • NVIDIA Corporation
  • Salesforce, Inc.
  • SAP SE
  • Oracle Corporation
  • Palantir Technologies Inc.
  • DataRobot, Inc.
  • H2O.ai, Inc.

Report Scope

In this report, the Global Generative AI in Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Generative AI in Analytics Market, By Deployment

  • Cloud-based
  • On-premises

Generative AI in Analytics Market, By Technology

  • Natural Language Processing
  • Machine Learning
  • Deep Learning
  • Others

Generative AI in Analytics Market, By Application

  • Forecasting and Predictions
  • Automated Reporting
  • Anomaly Detection
  • Personalization

Generative AI in Analytics Market, By Region

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

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Generative AI in Analytics Market.

Available Customizations:

Global Generative AI in Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Generative AI in Analytics Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Deployment (Cloud-based, On-premises)
    • 5.2.2. By Technology (Natural Language Processing, Machine Learning, Deep Learning, Others)
    • 5.2.3. By Application (Forecasting and Predictions, Automated Reporting, Anomaly Detection, Personalization)
    • 5.2.4. By Region
    • 5.2.5. By Company (2025)
  • 5.3. Market Map

6. North America Generative AI in Analytics Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Deployment
    • 6.2.2. By Technology
    • 6.2.3. By Application
    • 6.2.4. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States Generative AI in Analytics Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Deployment
        • 6.3.1.2.2. By Technology
        • 6.3.1.2.3. By Application
    • 6.3.2. Canada Generative AI in Analytics Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Deployment
        • 6.3.2.2.2. By Technology
        • 6.3.2.2.3. By Application
    • 6.3.3. Mexico Generative AI in Analytics Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Deployment
        • 6.3.3.2.2. By Technology
        • 6.3.3.2.3. By Application

7. Europe Generative AI in Analytics Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Deployment
    • 7.2.2. By Technology
    • 7.2.3. By Application
    • 7.2.4. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany Generative AI in Analytics Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Deployment
        • 7.3.1.2.2. By Technology
        • 7.3.1.2.3. By Application
    • 7.3.2. France Generative AI in Analytics Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Deployment
        • 7.3.2.2.2. By Technology
        • 7.3.2.2.3. By Application
    • 7.3.3. United Kingdom Generative AI in Analytics Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Deployment
        • 7.3.3.2.2. By Technology
        • 7.3.3.2.3. By Application
    • 7.3.4. Italy Generative AI in Analytics Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Deployment
        • 7.3.4.2.2. By Technology
        • 7.3.4.2.3. By Application
    • 7.3.5. Spain Generative AI in Analytics Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Deployment
        • 7.3.5.2.2. By Technology
        • 7.3.5.2.3. By Application

8. Asia Pacific Generative AI in Analytics Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Deployment
    • 8.2.2. By Technology
    • 8.2.3. By Application
    • 8.2.4. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China Generative AI in Analytics Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Deployment
        • 8.3.1.2.2. By Technology
        • 8.3.1.2.3. By Application
    • 8.3.2. India Generative AI in Analytics Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Deployment
        • 8.3.2.2.2. By Technology
        • 8.3.2.2.3. By Application
    • 8.3.3. Japan Generative AI in Analytics Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Deployment
        • 8.3.3.2.2. By Technology
        • 8.3.3.2.3. By Application
    • 8.3.4. South Korea Generative AI in Analytics Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Deployment
        • 8.3.4.2.2. By Technology
        • 8.3.4.2.3. By Application
    • 8.3.5. Australia Generative AI in Analytics Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Deployment
        • 8.3.5.2.2. By Technology
        • 8.3.5.2.3. By Application

9. Middle East & Africa Generative AI in Analytics Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Deployment
    • 9.2.2. By Technology
    • 9.2.3. By Application
    • 9.2.4. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia Generative AI in Analytics Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Deployment
        • 9.3.1.2.2. By Technology
        • 9.3.1.2.3. By Application
    • 9.3.2. UAE Generative AI in Analytics Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Deployment
        • 9.3.2.2.2. By Technology
        • 9.3.2.2.3. By Application
    • 9.3.3. South Africa Generative AI in Analytics Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Deployment
        • 9.3.3.2.2. By Technology
        • 9.3.3.2.3. By Application

10. South America Generative AI in Analytics Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Deployment
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Generative AI in Analytics Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Deployment
        • 10.3.1.2.2. By Technology
        • 10.3.1.2.3. By Application
    • 10.3.2. Colombia Generative AI in Analytics Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Deployment
        • 10.3.2.2.2. By Technology
        • 10.3.2.2.3. By Application
    • 10.3.3. Argentina Generative AI in Analytics Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Deployment
        • 10.3.3.2.2. By Technology
        • 10.3.3.2.3. By Application

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global Generative AI in Analytics Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. OpenAI OpCo, LLC
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. IBM Corporation
  • 15.3. Microsoft Corporation
  • 15.4. Google LLC
  • 15.5. Amazon Web Services, Inc.
  • 15.6. NVIDIA Corporation
  • 15.7. Salesforce, Inc.
  • 15.8. SAP SE
  • 15.9. Oracle Corporation
  • 15.10. Palantir Technologies Inc.
  • 15.11. DataRobot, Inc.
  • 15.12. H2O.ai, Inc.

16. Strategic Recommendations

17. About Us & Disclaimer