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
Description
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
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
Table of Contents
200 Pages
- 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.
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