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1833499

2032 年人工智慧和機器學習預測分析市場預測：按組件、部署類型、組織規模、技術、應用、最終用戶和地區進行的全球分析

AI & ML-powered Predictive Analytics Market Forecasts to 2032 - Global Analysis By Component (Solutions and Services), Deployment Mode, Organization Size, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧和機器學習預測分析市場預計在 2025 年達到 222 億美元，到 2032 年將達到 851 億美元，預測期內的複合年成長率為 21.1%。

由人工智慧和機器學習驅動的預測分析是指利用人工智慧和機器學習演算法來分析歷史和即時數據，識別模式並預測未來結果。這些技術透過實現自動化學習、自適應改進和對複雜資料集的更深入洞察，增強了傳統的預測模型。其應用涵蓋醫療保健、金融、零售和製造等行業，幫助企業預測客戶行為、最佳化營運並降低風險。透過基於新數據不斷改進預測，人工智慧和機器學習使企業能夠以更高的準確性、速度和擴充性做出主動的數據主導決策，從而改變策略規劃和競爭優勢。

巨量資料爆炸

跨產業巨量資料的激增是人工智慧和機器學習驅動的預測分析市場的主要驅動力。企業正在從數位平台、物聯網設備和企業系統產生大量結構化和非結構化資料。這種數據爆炸式成長需要先進的分析工具來提取有意義的洞察並預測趨勢。人工智慧和機器學習技術能夠實現即時處理和模式識別，幫助企業做出明智的決策，增強客戶參與，並提高跨部門的營運效率。

實施成本高

高昂的實施成本是人工智慧和機器學習驅動的預測分析發展的一個重大限制。部署這些技術需要在基礎設施、技術人員以及與現有系統的整合方面進行大量投資。中小企業通常面臨預算限制，這限制了他們採用預測解決方案的能力。此外，持續的維護、軟體升級和資料管理費用進一步增加了整體擁有成本，使企業難以有效且永續地擴展其分析舉措。

供應鏈最佳化

供應鏈最佳化為基於人工智慧和機器學習的預測分析提供了重要機會。這些技術透過分析歷史和即時數據，實現準確的需求預測、庫存管理和物流規劃，使企業能夠主動應對中斷、降低營運成本並提升交付績效。隨著全球供應鏈日益複雜，預測分析透過提高敏捷性、可視性和回應能力，提供了策略優勢。正因如此，製造業、零售業和分銷業正積極尋求提升競爭力和韌性。

資料隱私問題

資料隱私問題對市場構成了重大威脅。敏感的個人和企業資料的使用引發了道德和監管挑戰，尤其是在《一般資料保護規範》(GDPR) 和《健康保險流通與責任法案》(HIPAA) 等框架下。組織必須實施強力的資料管治和安全通訊協定，以防止資料外洩和濫用。不遵守規定可能會導致聲譽受損和法律處罰。這些風險可能會阻礙資料的應用，尤其是在處理敏感資訊的行業，例如醫療保健、金融和政府機構。

COVID-19的影響：

新冠疫情對市場產生了重大影響。企業紛紛採用預測工具來管理不確定性、預測需求波動並最佳化勞動力規劃。醫療保健系統利用分析技術追蹤病毒傳播並分配資源。然而，這場危機暴露了數據基礎設施的缺口，並加速了數位轉型。疫情過後，企業持續投資預測能力，以增強韌性、改善風險管理並適應不斷變化的消費行為，鞏固了分析作為核心策略資產的地位。

勞動力分析領域預計將成為預測期內最大的領域

由於對數據主導勞動力策略的需求不斷成長，勞動力分析領域預計將在預測期內佔據最大的市場佔有率。企業正在利用預測工具來加強招募、監控員工績效並降低人員離職率。人工智慧和機器學習模型有助於預測勞動力趨勢、最佳化人員配置並提高員工敬業度。隨著企業優先考慮營運效率和員工社會福利，勞動力分析已成為一個關鍵的應用領域，推動了顯著成長並促進了整體市場的擴張。

預測期內，機器學習將以最高的複合年成長率成長

預計機器學習領域將在預測期內實現最高成長率，因為機器學習演算法能夠持續從數據中學習，提高預測準確性並實現複雜決策流程的自動化。各行各業正在採用機器學習進行詐欺偵測、客戶行為建模、預測性維護和個人化行銷。機器學習的可擴展性和適應性使其成為動態環境的理想選擇。隨著企業尋求智慧、即時的洞察，機器學習已成為成長最快的領域，並以其變革性能力重塑預測分析格局。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率，因為快速的數位化、不斷擴大的工業基礎以及政府的支持政策正在推動中國、印度和日本等主要國家的採用。該地區數據生態系統的成長，加上醫療保健、零售和製造業對即時洞察日益成長的需求，正在推動市場成長。亞太地區對創新和技術的戰略重點使其成為分析領域的主導者。

複合年成長率最高的地區：

預計北美將在預測期內實現最高的複合年成長率，因為該地區受益於早期技術採用、強大的基礎設施以及主要分析供應商的強大影響力。金融、醫療保健和行銷領域對預測解決方案的旺盛需求將推動成長。監管支持和對人工智慧研究的投資將進一步推動市場擴張。北美對創新和數據主導決策的重視，正推動其在預測分析發展領域的領先地位。

提供免費客製化：

此報告的訂閱者可以使用以下免費自訂選項之一：

  • 公司簡介
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    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章 全球人工智慧和機器學習預測分析市場（按組件）

  • 解決方案
    • 資料探勘與資料管理
    • 統計建模工具
    • 視覺化和儀表板工具
  • 服務
    • 專業服務
    • 託管服務

第6章全球人工智慧和機器學習預測分析市場（按部署類型）

  • 本地部署
  • 雲端基礎
    • 公共雲端
    • 私有雲端
    • 混合雲端

第7章 全球人工智慧和機器學習預測分析市場（按組織規模）

  • 小型企業
  • 主要企業

第 8 章：全球 AI 和 ML 預測分析市場（按技術分類）

  • 機器學習
    • 監督學習
    • 無監督學習
    • 強化學習
  • 深度學習
  • 自然語言處理（NLP）
  • 電腦視覺
  • 巨量資料分析整合

第9章全球人工智慧和機器學習預測分析市場（按應用）

  • 風險管理和詐騙偵測
  • 客戶和行銷分析
  • 營運和供應鏈最佳化
  • 人力資源分析
  • 醫療保健和臨床決策支援
  • 財務預測與規劃
  • 預測性維護
  • 其他用途

第 10 章：全球 AI 和 ML 預測分析市場（按最終用戶分類）

  • 銀行、金融服務和保險（BFSI）
  • 醫療保健和生命科學
  • 零售與電子商務
  • 製造業
  • 資訊科技/通訊
  • 運輸/物流
  • 能源與公共產業
  • 政府/國防
  • 其他最終用戶

第 11 章全球基於人工智慧和機器學習的預測分析市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章：企業概況

  • IBM
  • DataRobot
  • Microsoft
  • HPE
  • Google
  • RapidMiner
  • Amazon Web Services（AWS）
  • Qlik
  • SAP
  • Alteryx
  • Oracle
  • TIBCO Software
  • SAS Institute
  • Teradata
  • Salesforce
Product Code: SMRC31332

According to Stratistics MRC, the Global AI & ML-powered Predictive Analytics Market is accounted for $22.2 billion in 2025 and is expected to reach $85.1 billion by 2032 growing at a CAGR of 21.1% during the forecast period. AI & ML-powered Predictive Analytics refers to the use of artificial intelligence and machine learning algorithms to analyze historical and real-time data, identify patterns, and forecast future outcomes. These technologies enhance traditional predictive models by enabling automated learning, adaptive improvements, and deeper insights across complex datasets. Applications span industries such as healthcare, finance, retail, and manufacturing, helping organizations anticipate customer behavior, optimize operations, and mitigate risks. By continuously refining predictions based on new data, AI and ML empower businesses to make proactive, data-driven decisions with greater accuracy, speed, and scalability, transforming strategic planning and competitive advantage.

Market Dynamics:

Driver:

Explosion of Big Data

The proliferation of big data across industries is a key driver of the AI & ML-powered Predictive Analytics Market. Organizations are generating vast volumes of structured and unstructured data from digital platforms, IoT devices, and enterprise systems. This data explosion necessitates advanced analytics tools to extract meaningful insights and forecast trends. AI and ML technologies enable real-time processing and pattern recognition, empowering businesses to make informed decisions, enhance customer engagement, and improve operational efficiency across sectors.

Restraint:

High Implementation Costs

High implementation costs pose a significant restraint to the growth of AI & ML-powered Predictive Analytics. Deploying these technologies requires substantial investment in infrastructure, skilled personnel, and integration with existing systems. Small and medium enterprises often struggle with budget constraints, limiting their ability to adopt predictive solutions. Additionally, ongoing maintenance, software upgrades, and data management expenses further increase the total cost of ownership, making it challenging for organizations to scale analytics initiatives effectively and sustainably.

Opportunity:

Supply Chain Optimization

Supply chain optimization presents a major opportunity for AI & ML-powered Predictive Analytics. These technologies enable accurate demand forecasting, inventory management, and logistics planning by analyzing historical and real-time data. Businesses can proactively address disruptions, reduce operational costs, and enhance delivery performance. As global supply chains become increasingly complex, predictive analytics offers a strategic advantage by improving agility, visibility, and responsiveness. This drives adoption across manufacturing, retail, and distribution sectors seeking competitive edge and resilience.

Threat:

Data Privacy Concerns

Data privacy concerns represent a critical threat to the market. The use of sensitive personal and enterprise data raises ethical and regulatory challenges, especially under frameworks like GDPR and HIPAA. Organizations must implement robust data governance and security protocols to prevent breaches and misuse. Failure to comply can result in reputational damage and legal penalties. These risks may deter adoption, particularly in sectors handling confidential information, such as healthcare, finance, and government.

Covid-19 Impact:

The Covid-19 pandemic significantly influenced the market. Organizations turned to predictive tools to manage uncertainty, forecast demand fluctuations, and optimize workforce planning. Healthcare systems used analytics to track virus spread and allocate resources. However, the crisis also exposed gaps in data infrastructure and accelerated digital transformation. Post-pandemic, businesses continue investing in predictive capabilities to build resilience, improve risk management, and adapt to evolving consumer behavior, solidifying analytics as a core strategic asset.

The workforce analytics segment is expected to be the largest during the forecast period

The workforce analytics segment is expected to account for the largest market share during the forecast period due to rising demand for data-driven human resource strategies. Organizations are leveraging predictive tools to enhance recruitment, monitor employee performance, and reduce turnover. AI & ML models help forecast workforce trends, optimize talent allocation, and improve engagement. As companies prioritize operational efficiency and employee well-being, workforce analytics becomes a vital application area, driving significant growth and contributing to overall market expansion.

The machine learning segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the machine learning segment is predicted to witness the highest growth rate as ML algorithms continuously learn from data, improving prediction accuracy and automating complex decision-making processes. Industries are adopting ML for fraud detection, customer behavior modeling, predictive maintenance, and personalized marketing. Its scalability and adaptability make it ideal for dynamic environments. As businesses seek intelligent, real-time insights, machine learning emerges as the fastest-growing segment, reshaping the predictive analytics landscape with transformative capabilities.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to rapid digitalization, expanding industrial base, and supportive government initiatives drive adoption across key economies like China, India, and Japan. The region's growing data ecosystem, coupled with increasing demand for real-time insights in healthcare, retail, and manufacturing, fuels market growth. Asia Pacific's strategic focus on innovation and technology positions it as a dominant force in analytics.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR owing to region benefits from early technology adoption, strong infrastructure, and a robust presence of leading analytics vendors. High demand for predictive solutions in finance, healthcare, and marketing accelerates growth. Regulatory support and investment in AI research further enhance market expansion. North America's emphasis on innovation and data-driven decision-making drives its leadership in predictive analytics development.

Key players in the market

Some of the key players in AI & ML-powered Predictive Analytics Market include IBM, DataRobot, Microsoft, HPE, Google, RapidMiner, Amazon Web Services (AWS), Qlik, SAP, Alteryx, Oracle, TIBCO Software, SAS Institute, Teradata and Salesforce.

Key Developments:

In January 2025, PwC and Microsoft have announced a strategic collaboration to transform industries through AI agents. This partnership aims to harness AI's potential to drive business value, enhance customer engagem ent, and streamline operations across various sectors.

In January 2025, Microsoft and OpenAI have expanded their strategic partnership to accelerate the next phase of artificial intelligence. This collaboration includes exclusive rights for Microsoft to utilize OpenAI's intellectual property in products like Copilot, ensuring customer's access to advanced AI models.

Components Covered:

  • Solutions
  • Services

Deployment Modes Covered:

  • On-Premises
  • Cloud-Based

Organization Sizes Covered:

  • Small & Medium Enterprises (SMEs)
  • Large Enterprises

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Big Data Analytics Integration

Applications Covered:

  • Risk Management & Fraud Detection
  • Customer & Marketing Analytics
  • Operations & Supply Chain Optimization
  • Workforce Analytics
  • Healthcare & Clinical Decision Support
  • Financial Forecasting & Planning
  • Predictive Maintenance
  • Other Applications

End Users Covered:

  • Banking, Financial Services & Insurance (BFSI)
  • Healthcare & Life Sciences
  • Retail & E-commerce
  • Manufacturing
  • IT & Telecommunications
  • Transportation & Logistics
  • Energy & Utilities
  • Government & Defense
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI & ML-powered Predictive Analytics Market, By Component

  • 5.1 Introduction
  • 5.2 Solutions
    • 5.2.1 Data Mining & Data Management
    • 5.2.2 Statistical Modeling Tools
    • 5.2.3 Visualization & Dashboarding Tools
  • 5.3 Services
    • 5.3.1 Professional Services
    • 5.3.2 Managed Services

6 Global AI & ML-powered Predictive Analytics Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 On-Premises
  • 6.3 Cloud-Based
    • 6.3.1 Public Cloud
    • 6.3.2 Private Cloud
    • 6.3.3 Hybrid Cloud

7 Global AI & ML-powered Predictive Analytics Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Small & Medium Enterprises (SMEs)
  • 7.3 Large Enterprises

8 Global AI & ML-powered Predictive Analytics Market, By Technology

  • 8.1 Introduction
  • 8.2 Machine Learning
    • 8.2.1 Supervised Learning
    • 8.2.2 Unsupervised Learning
    • 8.2.3 Reinforcement Learning
  • 8.3 Deep Learning
  • 8.4 Natural Language Processing (NLP)
  • 8.5 Computer Vision
  • 8.6 Big Data Analytics Integration

9 Global AI & ML-powered Predictive Analytics Market, By Application

  • 9.1 Introduction
  • 9.2 Risk Management & Fraud Detection
  • 9.3 Customer & Marketing Analytics
  • 9.4 Operations & Supply Chain Optimization
  • 9.5 Workforce Analytics
  • 9.6 Healthcare & Clinical Decision Support
  • 9.7 Financial Forecasting & Planning
  • 9.8 Predictive Maintenance
  • 9.9 Other Applications

10 Global AI & ML-powered Predictive Analytics Market, By End User

  • 10.1 Introduction
  • 10.2 Banking, Financial Services & Insurance (BFSI)
  • 10.3 Healthcare & Life Sciences
  • 10.4 Retail & E-commerce
  • 10.5 Manufacturing
  • 10.6 IT & Telecommunications
  • 10.7 Transportation & Logistics
  • 10.8 Energy & Utilities
  • 10.9 Government & Defense
  • 10.10 Other End Users

11 Global AI & ML-powered Predictive Analytics Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 IBM
  • 13.2 DataRobot
  • 13.3 Microsoft
  • 13.4 HPE
  • 13.5 Google
  • 13.6 RapidMiner
  • 13.7 Amazon Web Services (AWS)
  • 13.8 Qlik
  • 13.9 SAP
  • 13.10 Alteryx
  • 13.11 Oracle
  • 13.12 TIBCO Software
  • 13.13 SAS Institute
  • 13.14 Teradata
  • 13.15 Salesforce

List of Tables

  • Table 1 Global AI & ML-powered Predictive Analytics Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI & ML-powered Predictive Analytics Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI & ML-powered Predictive Analytics Market Outlook, By Solutions (2024-2032) ($MN)
  • Table 4 Global AI & ML-powered Predictive Analytics Market Outlook, By Data Mining & Data Management (2024-2032) ($MN)
  • Table 5 Global AI & ML-powered Predictive Analytics Market Outlook, By Statistical Modeling Tools (2024-2032) ($MN)
  • Table 6 Global AI & ML-powered Predictive Analytics Market Outlook, By Visualization & Dashboarding Tools (2024-2032) ($MN)
  • Table 7 Global AI & ML-powered Predictive Analytics Market Outlook, By Services (2024-2032) ($MN)
  • Table 8 Global AI & ML-powered Predictive Analytics Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 9 Global AI & ML-powered Predictive Analytics Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 10 Global AI & ML-powered Predictive Analytics Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 11 Global AI & ML-powered Predictive Analytics Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 12 Global AI & ML-powered Predictive Analytics Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 13 Global AI & ML-powered Predictive Analytics Market Outlook, By Public Cloud (2024-2032) ($MN)
  • Table 14 Global AI & ML-powered Predictive Analytics Market Outlook, By Private Cloud (2024-2032) ($MN)
  • Table 15 Global AI & ML-powered Predictive Analytics Market Outlook, By Hybrid Cloud (2024-2032) ($MN)
  • Table 16 Global AI & ML-powered Predictive Analytics Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 17 Global AI & ML-powered Predictive Analytics Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 18 Global AI & ML-powered Predictive Analytics Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 19 Global AI & ML-powered Predictive Analytics Market Outlook, By Technology (2024-2032) ($MN)
  • Table 20 Global AI & ML-powered Predictive Analytics Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 21 Global AI & ML-powered Predictive Analytics Market Outlook, By Supervised Learning (2024-2032) ($MN)
  • Table 22 Global AI & ML-powered Predictive Analytics Market Outlook, By Unsupervised Learning (2024-2032) ($MN)
  • Table 23 Global AI & ML-powered Predictive Analytics Market Outlook, By Reinforcement Learning (2024-2032) ($MN)
  • Table 24 Global AI & ML-powered Predictive Analytics Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 25 Global AI & ML-powered Predictive Analytics Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 26 Global AI & ML-powered Predictive Analytics Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 27 Global AI & ML-powered Predictive Analytics Market Outlook, By Big Data Analytics Integration (2024-2032) ($MN)
  • Table 28 Global AI & ML-powered Predictive Analytics Market Outlook, By Application (2024-2032) ($MN)
  • Table 29 Global AI & ML-powered Predictive Analytics Market Outlook, By Risk Management & Fraud Detection (2024-2032) ($MN)
  • Table 30 Global AI & ML-powered Predictive Analytics Market Outlook, By Customer & Marketing Analytics (2024-2032) ($MN)
  • Table 31 Global AI & ML-powered Predictive Analytics Market Outlook, By Operations & Supply Chain Optimization (2024-2032) ($MN)
  • Table 32 Global AI & ML-powered Predictive Analytics Market Outlook, By Workforce Analytics (2024-2032) ($MN)
  • Table 33 Global AI & ML-powered Predictive Analytics Market Outlook, By Healthcare & Clinical Decision Support (2024-2032) ($MN)
  • Table 34 Global AI & ML-powered Predictive Analytics Market Outlook, By Financial Forecasting & Planning (2024-2032) ($MN)
  • Table 35 Global AI & ML-powered Predictive Analytics Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 36 Global AI & ML-powered Predictive Analytics Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 37 Global AI & ML-powered Predictive Analytics Market Outlook, By End User (2024-2032) ($MN)
  • Table 38 Global AI & ML-powered Predictive Analytics Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2024-2032) ($MN)
  • Table 39 Global AI & ML-powered Predictive Analytics Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 40 Global AI & ML-powered Predictive Analytics Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 41 Global AI & ML-powered Predictive Analytics Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 42 Global AI & ML-powered Predictive Analytics Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
  • Table 43 Global AI & ML-powered Predictive Analytics Market Outlook, By Transportation & Logistics (2024-2032) ($MN)
  • Table 44 Global AI & ML-powered Predictive Analytics Market Outlook, By Energy & Utilities (2024-2032) ($MN)
  • Table 45 Global AI & ML-powered Predictive Analytics Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 46 Global AI & ML-powered Predictive Analytics Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.