Exploring novel growth opportunities on computer vision, “Explainable AI Market Size, Share & Trends Analysis Report by Component (Solutions, Services), Deployment Mode, Technology, Model Type, Enterprise Size, Function, Application, Industry Vertical and Geography (North America, Europe, Asia Pacific, Middle East, Africa, and South America) – Global Industry Data, Trends, and Forecasts, 2026–2035” A holistic view of the market pathways in the explainable AI market underscores revenue acceleration through three key levers scalable product line extensions, high‑maturity strategic partnerships.
Global Explainable AI Market Forecast 2035:
According to the report, the global explainable AI market is likely to grow from USD 12.7 Billion in 2025 to USD 62.7 Billion in 2035 at a highest CAGR of 17.3% during the time period. The explainable AI (XAI) market is rapidly expanding due to the increasing application of artificial intelligence in industry and the demand for transparency and trust in AI-assisted decision-making. Organizations are using explainable AI solutions to improve regulatory compliance, efficiency, and stakeholder confidence by making AI models explainable, understandable, and accountable. Governments and enterprises in particular sectors, such as financial services, health care, and public services, are utilizing explainable AI when deploying AI systems to reflect the ethical and legal accountability at the use of such AI systems.
Furthermore, the financial services industry is increasingly using explainable AI to provide more transparency to the models used in credit scoring, fraud detection, and risk assessment activities. In healthcare, explainable AI is widely used to assist, and increase log users, in understanding diagnostic and treatment recommendations provided by AI as well as provide for better interpretability of predictive analytics through a clinician level user interface.
Sectors including retail, logistics, and energy are also using explainable AI to improve, automate, and explain AI-generated recommendations and insights to non-technical end users. All of these innovations enable businesses and end-users to interactively respond to requests and questions in real-time, audit, and trust in insights that are produced by AI, as well as have a model for continual growth and new innovations.
“Key Driver, Restraint, and Growth Opportunity Shaping the Global Explainable AI Market”
The global explainable AI market will continue to benefit from the growing use of AI, specifically in high-stakes decision-making sectors such as finance, healthcare, and legal services. Organizations are already using explainable AI to provide transparency into what is happening in AI-supported decision-making to help their stakeholders comprehend how models reach predictions while simultaneously building trust and accountability. For example, in high-stakes decisions around automated loan approval, insurance claims processing, and medical diagnosis and treatment, being able to interpret and understand reasoning around a model prediction is necessary and can directly influence outcomes and regulatory compliance.
However, providing meaningful explanations for complex AI models such as deep learning or ensemble models continues to pose a challenge. Actionable insight from these models can be technically difficult to provide, which limits scaling in companies that have heterogeneous and unstructured data sources once they move out of the pilot phase and into enterprise implementations.
Another area that has a large potential is explainable AI integration into autonomous systems and IoT applications, in which AI is already being used for real-time decision-making. Explainable AI can address predictive maintenance alerts in IoT, smart cities, industrial automation, and other autonomous system applications, ultimately leading to safer, more reliable, and less intimidating systems for humans to audit and manage.
Expansion of Global Explainable AI Market
“AI Transparency, Model Interpretability, and Regulatory Compliance Driving Global Explainable AI Expansion”
- The anonymous explainable AI market is growing due to increased demand for interpretable and transparent AI models across sectors such as finance, health care, and legal services. The rise of organizations integrating explainable AI solutions reflects stakeholders desire for understanding, a higher degree of trust in AI-based decisions improved accountability, reduced biased, and ethical AI applications.
- In addition, AI regulations and ethical guidelines emerging in regions such as the EU, North America, and Asia-Pacific are pushing a faster adoption of explainable AI. Clear guidelines around explainability in credit scoring, risk assessments, and healthcare diagnostic assessments, are compelling enterprises to integrate solutions that provide clear insight into how these companies' large language models (LLM) behave.
- Finally, as there is convergence around AI model interpretability tools/capabilities, cloud-based AI platforms, and enterprise adoption of AI in the verticals above, enterprises can now incorporate explainable AI at scale; enabling them to audit, monitor, and explain AI-based decisions in live, real time, promoting trust and transparency, as well as reducing regulatory burdens, opening up further adoption into other verticals.
Regional Analysis of Global Explainable AI Market
- North America leads the explainable AI market owing to advanced AI infrastructure, increasing enterprise adoption, and existing regulatory frameworks. Enterprises in particular in the areas of finance, healthcare, and government are adopting explainable AI solutions to provide transparency, fairness, and accountability in AI-supported decision-making. Strict regulations on AI ethics, model explainability, and data privacy, as well as a high level of digital trust in North America, showcase the U.S. as the leading model for global organizations seeking to adopt explainable AI.
- Within the next 3–5 years, the Asia-Pacific region is projected to be the fastest growing market from wider adoption of AI in smart cities (government), manufacturing automation to aid workforce efficiency, and improved healthcare. Overall, domestic government initiatives to facilitate AI transparency overall as well as enterprise investment to determine the role of AI in interpretable models, will accelerate growth across the region with considerable investment in the economy.
- Europe continues to show gradual growth, is moving towards AI transparency regulation, open standards with AI, and thus moving the industry towards further collaboration across industries. In the Middle East and Africa, explainable AI is growing due to government programs of digitalization; AI ethics initiatives; and partnerships with enterprises further encourage transparency, trust, and accountability across sectors.
Prominent players operating in the global explainable AI market include prominent companies such as Aible, Inc., Amazon Web Services, Inc., Arthur AI, DarwinAI Corp., DataRobot, Inc., Fiddler AI, Google LLC (Alphabet Inc.), H2O.ai, Inc., IBM Corporation, IBM Watson Studio, Intel Corporation, Kyndi, Inc., Microsoft Corporation, NVIDIA Corporation, Oracle Corporation, Pymetrics Inc., Salesforce, Inc., SAP SE, SAS Institute Inc., Zest AI, and several other key players.
The global explainable AI market has been segmented as follows:
Global Explainable AI Market Analysis, by Component
- Solutions
- Explainable Machine Learning Platforms
- Model Interpretability Tools
- Visualization and Reporting Dashboards
- Data Preprocessing and Feature Analysis Tools
- Model Monitoring and Validation Systems
- Automated Decision Transparency Solutions
- Explainable Deep Learning Frameworks
- Others
- Services
- Consulting Services
- AI Strategy and Governance Consulting
- Model Explainability Assessment
- Compliance and Regulatory Advisory
- Others
- Integration & Deployment
- Custom Model Integration
- Deployment of Explainable AI Systems
- API and Software Integration Support
- Others
- Support & Maintenance
- Model Performance Monitoring
- System Upgrades and Optimization
- Technical Support and Troubleshooting
- Others
Global Explainable AI Market Analysis, by Deployment Mode
- Cloud-Based
- On-Premises
Global Explainable AI Market Analysis, by Technology
- Machine Learning
- Natural Language Processing (NLP)
- Deep Learning
- Computer Vision
- Others
Global Explainable AI Market Analysis, by Model Type
- Global Models
- Local Models
Global Explainable AI Market Analysis, by Enterprise Size
- Small and Medium Enterprises (SMEs)
- Large Enterprises
Global Explainable AI Market Analysis, by Function
- Data Scientists and Engineers
- Business Executives and Managers
- Compliance Officers
- Research and Development Teams
- Others
Global Explainable AI Market Analysis, by Application
- Model Monitoring and Management
- Data Visualization and Analysis
- Risk Management and Compliance
- Fraud and Anomaly Detection
- Predictive Analytics
- Customer Experience Optimization
- Others
Global Explainable AI Market Analysis, by Industry Vertica
- lBFSI
- Healthcare and Life Sciences
- Retail and E-commerce
- Manufacturing
- IT & Telecommunications
- Government and Defense
- Energy and Utilities
- Transportation and Logistics
- Others
Global Explainable AI Market Analysis, by Region
About Us
MarketGenics is a global market research and management consulting company empowering decision makers from startups, Fortune 500 companies, non-profit organizations, universities and government institutions. Our main goal is to assist and partner organizations to make lasting strategic improvements and realize growth targets. Our industry research reports are designed to provide granular quantitative information, combined with key industry insights, aimed at assisting sustainable organizational development.
We serve clients on every aspect of strategy, including product development, application modeling, exploring new markets and tapping into niche growth opportunities.
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Table of Contents
- 1. Research Methodology and Assumptions
- 1.1. Definitions
- 1.2. Research Design and Approach
- 1.3. Data Collection Methods
- 1.4. Base Estimates and Calculations
- 1.5. Forecasting Models
- 1.5.1. Key Forecast Factors & Impact Analysis
- 1.6. Secondary Research
- 1.6.1. Open Sources
- 1.6.2. Paid Databases
- 1.6.3. Associations
- 1.7. Primary Research
- 1.7.1. Primary Sources
- 1.7.2. Primary Interviews with Stakeholders across Ecosystem
- 2. Executive Summary
- 2.1. Global Explainable AI Market Outlook
- 2.1.1. Explainable AI Market Size (Value - US$ Bn), and Forecasts, 2021-2035
- 2.1.2. Compounded Annual Growth Rate Analysis
- 2.1.3. Growth Opportunity Analysis
- 2.1.4. Segmental Share Analysis
- 2.1.5. Geographical Share Analysis
- 2.2. Market Analysis and Facts
- 2.3. Supply-Demand Analysis
- 2.4. Competitive Benchmarking
- 2.5. Go-to- Market Strategy
- 2.5.1. Customer/ End-use Industry Assessment
- 2.5.2. Growth Opportunity Data, 2026-2035
- 2.5.2.1. Regional Data
- 2.5.2.2. Country Data
- 2.5.2.3. Segmental Data
- 2.5.3. Identification of Potential Market Spaces
- 2.5.4. GAP Analysis
- 2.5.5. Potential Attractive Price Points
- 2.5.6. Prevailing Market Risks & Challenges
- 2.5.7. Preferred Sales & Marketing Strategies
- 2.5.8. Key Recommendations and Analysis
- 2.5.9. A Way Forward
- 2.1. Global Explainable AI Market Outlook
- 3. Industry Data and Premium Insights
- 3.1. Global Information Technology & Media Ecosystem Overview, 2025
- 3.1.1. Information Technology & Media Industry Analysis
- 3.1.2. Key Trends for Information Technology & Media Industry
- 3.1.3. Regional Distribution for Information Technology & Media Industry
- 3.2. Supplier Customer Data
- 3.3. Technology Roadmap and Developments
- 3.1. Global Information Technology & Media Ecosystem Overview, 2025
- 4. Market Overview
- 4.1. Market Dynamics
- 4.1.1. Drivers
- 4.1.1.1. Rising demand for transparent and interpretable AI models
- 4.1.1.2. Growing adoption of XAI solutions across high-stakes industries like finance and healthcare
- 4.1.1.3. Increasing regulatory requirements for AI explainability, accountability, and ethical compliance
- 4.1.2. Restraints
- 4.1.2.1. High implementation and integration costs of Explainable AI solutions
- 4.1.2.2. Challenges in aligning XAI tools with legacy AI models and existing IT infrastructures
- 4.1.1. Drivers
- 4.2. Key Trend Analysis
- 4.3. Regulatory Framework
- 4.3.1. Key Regulations, Norms, and Subsidies, by Key Countries
- 4.3.2. Tariffs and Standards
- 4.3.3. Impact Analysis of Regulations on the Market
- 4.4. Value Chain Analysis
- 4.4.1. Data/ Algorithms Providers
- 4.4.2. System Integrators/ Technology Providers
- 4.4.3. Explainable AI Solution Providers
- 4.4.4. End Users
- 4.5. Cost Structure Analysis
- 4.5.1. Parameter’s Share for Cost Associated
- 4.5.2. COGP vs COGS
- 4.5.3. Profit Margin Analysis
- 4.6. Pricing Analysis
- 4.6.1. Regional Pricing Analysis
- 4.6.2. Segmental Pricing Trends
- 4.6.3. Factors Influencing Pricing
- 4.7. Porter’s Five Forces Analysis
- 4.8. PESTEL Analysis
- 4.9. Global Explainable AI Market Demand
- 4.9.1. Historical Market Size –Value (US$ Bn), 2020-2024
- 4.9.2. Current and Future Market Size –Value (US$ Bn), 2026–2035
- 4.9.2.1. Y-o-Y Growth Trends
- 4.9.2.2. Absolute $ Opportunity Assessment
- 4.1. Market Dynamics
- 5. Competition Landscape
- 5.1. Competition structure
- 5.1.1. Fragmented v/s consolidated
- 5.2. Company Share Analysis, 2025
- 5.2.1. Global Company Market Share
- 5.2.2. By Region
- 5.2.2.1. North America
- 5.2.2.2. Europe
- 5.2.2.3. Asia Pacific
- 5.2.2.4. Middle East
- 5.2.2.5. Africa
- 5.2.2.6. South America
- 5.3. Product Comparison Matrix
- 5.3.1. Specifications
- 5.3.2. Market Positioning
- 5.3.3. Pricing
- 5.1. Competition structure
- 6. Global Explainable AI Market Analysis, by Component
- 6.1. Key Segment Analysis
- 6.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Component, 2021-2035
- 6.2.1. Solutions
- 6.2.1.1. Explainable Machine Learning Platforms
- 6.2.1.2. Model Interpretability Tools
- 6.2.1.3. Visualization and Reporting Dashboards
- 6.2.1.4. Data Preprocessing and Feature Analysis Tools
- 6.2.1.5. Model Monitoring and Validation Systems
- 6.2.1.6. Automated Decision Transparency Solutions
- 6.2.1.7. Explainable Deep Learning Frameworks
- 6.2.1.8. Others
- 6.2.2. Services
- 6.2.2.1. Consulting Services
- 6.2.2.1.1. AI Strategy and Governance Consulting
- 6.2.2.1.2. Model Explainability Assessment
- 6.2.2.1.3. Compliance and Regulatory Advisory
- 6.2.2.1.4. Others
- 6.2.2.2. Integration & Deployment
- 6.2.2.2.1. Custom Model Integration
- 6.2.2.2.2. Deployment of Explainable AI Systems
- 6.2.2.2.3. API and Software Integration Support
- 6.2.2.2.4. Others
- 6.2.2.3. Support & Maintenance
- 6.2.2.3.1. Model Performance Monitoring
- 6.2.2.3.2. System Upgrades and Optimization
- 6.2.2.3.3. Technical Support and Troubleshooting
- 6.2.2.3.4. Others
- 6.2.2.1. Consulting Services
- 6.2.1. Solutions
- 7. Global Explainable AI Market Analysis, by Deployment Mode
- 7.1. Key Segment Analysis
- 7.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Deployment Mode, 2021-2035
- 7.2.1. Cloud-Based
- 7.2.2. On-Premises
- 8. Global Explainable AI Market Analysis, by Technology
- 8.1. Key Segment Analysis
- 8.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Technology, 2021-2035
- 8.2.1. Machine Learning
- 8.2.2. Natural Language Processing (NLP)
- 8.2.3. Deep Learning
- 8.2.4. Computer Vision
- 8.2.5. Others
- 9. Global Explainable AI Market Analysis, by Model Type
- 9.1. Key Segment Analysis
- 9.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Model Type, 2021-2035
- 9.2.1. Global Models
- 9.2.2. Local Models
- 10. Global Explainable AI Market Analysis, by Enterprise Size
- 10.1. Key Segment Analysis
- 10.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Enterprise Size, 2021-2035
- 10.2.1. Small and Medium Enterprises (SMEs)
- 10.2.2. Large Enterprises
- 11. Global Explainable AI Market Analysis, by Function
- 11.1. Key Segment Analysis
- 11.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Function, 2021-2035
- 11.2.1. Data Scientists and Engineers
- 11.2.2. Business Executives and Managers
- 11.2.3. Compliance Officers
- 11.2.4. Research and Development Teams
- 11.2.5. Others
- 12. Global Explainable AI Market Analysis, by Application
- 12.1. Key Segment Analysis
- 12.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Application, 2021-2035
- 12.2.1. Model Monitoring and Management
- 12.2.2. Data Visualization and Analysis
- 12.2.3. Risk Management and Compliance
- 12.2.4. Fraud and Anomaly Detection
- 12.2.5. Predictive Analytics
- 12.2.6. Customer Experience Optimization
- 12.2.7. Others
- 13. Global Explainable AI Market Analysis, by Industry Vertical
- 13.1. Key Segment Analysis
- 13.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Industry Vertical, 2021-2035
- 13.2.1. BFSI
- 13.2.2. Healthcare and Life Sciences
- 13.2.3. Retail and E-commerce
- 13.2.4. Manufacturing
- 13.2.5. IT & Telecommunications
- 13.2.6. Government and Defense
- 13.2.7. Energy and Utilities
- 13.2.8. Transportation and Logistics
- 13.2.9. Others
- 14. Global Explainable AI Market Analysis and Forecasts, by Region
- 14.1. Key Findings
- 14.2. Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, by Region, 2021-2035
- 14.2.1. North America
- 14.2.2. Europe
- 14.2.3. Asia Pacific
- 14.2.4. Middle East
- 14.2.5. Africa
- 14.2.6. South America
- 15. North America Explainable AI Market Analysis
- 15.1. Key Segment Analysis
- 15.2. Regional Snapshot
- 15.3. North America Explainable AI Market Size Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 15.3.1. Component
- 15.3.2. Deployment Mode
- 15.3.3. Technology
- 15.3.4. Model Type
- 15.3.5. Enterprise Size
- 15.3.6. Function
- 15.3.7. Application
- 15.3.8. Industry Vertical
- 15.3.9. Country
- 15.3.9.1. USA
- 15.3.9.2. Canada
- 15.3.9.3. Mexico
- 15.4. USA Explainable AI Market
- 15.4.1. Country Segmental Analysis
- 15.4.2. Component
- 15.4.3. Deployment Mode
- 15.4.4. Technology
- 15.4.5. Model Type
- 15.4.6. Enterprise Size
- 15.4.7. Function
- 15.4.8. Application
- 15.4.9. Industry Vertical
- 15.5. Canada Explainable AI Market
- 15.5.1. Country Segmental Analysis
- 15.5.2. Component
- 15.5.3. Deployment Mode
- 15.5.4. Technology
- 15.5.5. Model Type
- 15.5.6. Enterprise Size
- 15.5.7. Function
- 15.5.8. Application
- 15.5.9. Industry Vertical
- 15.6. Mexico Explainable AI Market
- 15.6.1. Country Segmental Analysis
- 15.6.2. Component
- 15.6.3. Deployment Mode
- 15.6.4. Technology
- 15.6.5. Model Type
- 15.6.6. Enterprise Size
- 15.6.7. Function
- 15.6.8. Application
- 15.6.9. Industry Vertical
- 16. Europe Explainable AI Market Analysis
- 16.1. Key Segment Analysis
- 16.2. Regional Snapshot
- 16.3. Europe Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 16.3.1. Component
- 16.3.2. Deployment Mode
- 16.3.3. Technology
- 16.3.4. Model Type
- 16.3.5. Enterprise Size
- 16.3.6. Function
- 16.3.7. Application
- 16.3.8. Industry Vertical
- 16.3.9. Country
- 16.3.9.1. Germany
- 16.3.9.2. United Kingdom
- 16.3.9.3. France
- 16.3.9.4. Italy
- 16.3.9.5. Spain
- 16.3.9.6. Netherlands
- 16.3.9.7. Nordic Countries
- 16.3.9.8. Poland
- 16.3.9.9. Russia & CIS
- 16.3.9.10. Rest of Europe
- 16.4. Germany Explainable AI Market
- 16.4.1. Country Segmental Analysis
- 16.4.2. Component
- 16.4.3. Deployment Mode
- 16.4.4. Technology
- 16.4.5. Model Type
- 16.4.6. Enterprise Size
- 16.4.7. Function
- 16.4.8. Application
- 16.4.9. Industry Vertical
- 16.5. United Kingdom Explainable AI Market
- 16.5.1. Country Segmental Analysis
- 16.5.2. Component
- 16.5.3. Deployment Mode
- 16.5.4. Technology
- 16.5.5. Model Type
- 16.5.6. Enterprise Size
- 16.5.7. Function
- 16.5.8. Application
- 16.5.9. Industry Vertical
- 16.6. France Explainable AI Market
- 16.6.1. Country Segmental Analysis
- 16.6.2. Component
- 16.6.3. Deployment Mode
- 16.6.4. Technology
- 16.6.5. Model Type
- 16.6.6. Enterprise Size
- 16.6.7. Function
- 16.6.8. Application
- 16.6.9. Industry Vertical
- 16.7. Italy Explainable AI Market
- 16.7.1. Country Segmental Analysis
- 16.7.2. Component
- 16.7.3. Deployment Mode
- 16.7.4. Technology
- 16.7.5. Model Type
- 16.7.6. Enterprise Size
- 16.7.7. Function
- 16.7.8. Application
- 16.7.9. Industry Vertical
- 16.8. Spain Explainable AI Market
- 16.8.1. Country Segmental Analysis
- 16.8.2. Component
- 16.8.3. Deployment Mode
- 16.8.4. Technology
- 16.8.5. Model Type
- 16.8.6. Enterprise Size
- 16.8.7. Function
- 16.8.8. Application
- 16.8.9. Industry Vertical
- 16.9. Netherlands Explainable AI Market
- 16.9.1. Country Segmental Analysis
- 16.9.2. Component
- 16.9.3. Deployment Mode
- 16.9.4. Technology
- 16.9.5. Model Type
- 16.9.6. Enterprise Size
- 16.9.7. Function
- 16.9.8. Application
- 16.9.9. Industry Vertical
- 16.10. Nordic Countries Explainable AI Market
- 16.10.1. Country Segmental Analysis
- 16.10.2. Component
- 16.10.3. Deployment Mode
- 16.10.4. Technology
- 16.10.5. Model Type
- 16.10.6. Enterprise Size
- 16.10.7. Function
- 16.10.8. Application
- 16.10.9. Industry Vertical
- 16.11. Poland Explainable AI Market
- 16.11.1. Country Segmental Analysis
- 16.11.2. Component
- 16.11.3. Deployment Mode
- 16.11.4. Technology
- 16.11.5. Model Type
- 16.11.6. Enterprise Size
- 16.11.7. Function
- 16.11.8. Application
- 16.11.9. Industry Vertical
- 16.12. Russia & CIS Explainable AI Market
- 16.12.1. Country Segmental Analysis
- 16.12.2. Component
- 16.12.3. Deployment Mode
- 16.12.4. Technology
- 16.12.5. Model Type
- 16.12.6. Enterprise Size
- 16.12.7. Function
- 16.12.8. Application
- 16.12.9. Industry Vertical…
- 16.13. Rest of Europe Explainable AI Market
- 16.13.1. Country Segmental Analysis
- 16.13.2. Component
- 16.13.3. Deployment Mode
- 16.13.4. Technology
- 16.13.5. Model Type
- 16.13.6. Enterprise Size
- 16.13.7. Function
- 16.13.8. Application
- 16.13.9. Industry Vertical……..
- 17. Asia Pacific Explainable AI Market Analysis
- 17.1. Key Segment Analysis
- 17.2. Regional Snapshot
- 17.3. Asia Pacific Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 17.3.1. Component
- 17.3.2. Deployment Mode
- 17.3.3. Technology
- 17.3.4. Model Type
- 17.3.5. Enterprise Size
- 17.3.6. Function
- 17.3.7. Application
- 17.3.8. Industry Vertical
- 17.3.9. Country
- 17.3.9.1. China
- 17.3.9.2. India
- 17.3.9.3. Japan
- 17.3.9.4. South Korea
- 17.3.9.5. Australia and New Zealand
- 17.3.9.6. Indonesia
- 17.3.9.7. Malaysia
- 17.3.9.8. Thailand
- 17.3.9.9. Vietnam
- 17.3.9.10. Rest of Asia Pacific
- 17.4. China Explainable AI Market
- 17.4.1. Country Segmental Analysis
- 17.4.2. Component
- 17.4.3. Deployment Mode
- 17.4.4. Technology
- 17.4.5. Model Type
- 17.4.6. Enterprise Size
- 17.4.7. Function
- 17.4.8. Application
- 17.4.9. Industry Vertical
- 17.5. India Explainable AI Market
- 17.5.1. Country Segmental Analysis
- 17.5.2. Component
- 17.5.3. Deployment Mode
- 17.5.4. Technology
- 17.5.5. Model Type
- 17.5.6. Enterprise Size
- 17.5.7. Function
- 17.5.8. Application
- 17.5.9. Industry Vertical
- 17.6. Japan Explainable AI Market
- 17.6.1. Country Segmental Analysis
- 17.6.2. Component
- 17.6.3. Deployment Mode
- 17.6.4. Technology
- 17.6.5. Model Type
- 17.6.6. Enterprise Size
- 17.6.7. Function
- 17.6.8. Application
- 17.6.9. Industry Vertical
- 17.7. South Korea Explainable AI Market
- 17.7.1. Country Segmental Analysis
- 17.7.2. Component
- 17.7.3. Deployment Mode
- 17.7.4. Technology
- 17.7.5. Model Type
- 17.7.6. Enterprise Size
- 17.7.7. Function
- 17.7.8. Application
- 17.7.9. Industry Vertical
- 17.8. Australia and New Zealand Explainable AI Market
- 17.8.1. Country Segmental Analysis
- 17.8.2. Component
- 17.8.3. Deployment Mode
- 17.8.4. Technology
- 17.8.5. Model Type
- 17.8.6. Enterprise Size
- 17.8.7. Function
- 17.8.8. Application
- 17.8.9. Industry Vertical
- 17.9. Indonesia Explainable AI Market
- 17.9.1. Country Segmental Analysis
- 17.9.2. Component
- 17.9.3. Deployment Mode
- 17.9.4. Technology
- 17.9.5. Model Type
- 17.9.6. Enterprise Size
- 17.9.7. Function
- 17.9.8. Application
- 17.9.9. Industry Vertical
- 17.10. Malaysia Explainable AI Market
- 17.10.1. Country Segmental Analysis
- 17.10.2. Component
- 17.10.3. Deployment Mode
- 17.10.4. Technology
- 17.10.5. Model Type
- 17.10.6. Enterprise Size
- 17.10.7. Function
- 17.10.8. Application
- 17.10.9. Industry Vertical
- 17.11. Thailand Explainable AI Market
- 17.11.1. Country Segmental Analysis
- 17.11.2. Component
- 17.11.3. Deployment Mode
- 17.11.4. Technology
- 17.11.5. Model Type
- 17.11.6. Enterprise Size
- 17.11.7. Function
- 17.11.8. Application
- 17.11.9. Industry Vertical
- 17.12. Vietnam Explainable AI Market
- 17.12.1. Country Segmental Analysis
- 17.12.2. Component
- 17.12.3. Deployment Mode
- 17.12.4. Technology
- 17.12.5. Model Type
- 17.12.6. Enterprise Size
- 17.12.7. Function
- 17.12.8. Application
- 17.12.9. Industry Vertical
- 17.13. Rest of Asia Pacific Explainable AI Market
- 17.13.1. Country Segmental Analysis
- 17.13.2. Component
- 17.13.3. Deployment Mode
- 17.13.4. Technology
- 17.13.5. Model Type
- 17.13.6. Enterprise Size
- 17.13.7. Function
- 17.13.8. Application
- 17.13.9. Industry Vertical
- 18. Middle East Explainable AI Market Analysis
- 18.1. Key Segment Analysis
- 18.2. Regional Snapshot
- 18.3. Middle East Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 18.3.1. Component
- 18.3.2. Deployment Mode
- 18.3.3. Technology
- 18.3.4. Model Type
- 18.3.5. Enterprise Size
- 18.3.6. Function
- 18.3.7. Application
- 18.3.8. Industry Vertical
- 18.3.9. Country
- 18.3.9.1. Turkey
- 18.3.9.2. UAE
- 18.3.9.3. Saudi Arabia
- 18.3.9.4. Israel
- 18.3.9.5. Rest of Middle East
- 18.4. Turkey Explainable AI Market
- 18.4.1. Country Segmental Analysis
- 18.4.2. Component
- 18.4.3. Deployment Mode
- 18.4.4. Technology
- 18.4.5. Model Type
- 18.4.6. Enterprise Size
- 18.4.7. Function
- 18.4.8. Application
- 18.4.9. Industry Vertical
- 18.5. UAE Explainable AI Market
- 18.5.1. Country Segmental Analysis
- 18.5.2. Component
- 18.5.3. Deployment Mode
- 18.5.4. Technology
- 18.5.5. Model Type
- 18.5.6. Enterprise Size
- 18.5.7. Function
- 18.5.8. Application
- 18.5.9. Industry Vertical
- 18.6. Saudi Arabia Explainable AI Market
- 18.6.1. Country Segmental Analysis
- 18.6.2. Component
- 18.6.3. Deployment Mode
- 18.6.4. Technology
- 18.6.5. Model Type
- 18.6.6. Enterprise Size
- 18.6.7. Function
- 18.6.8. Application
- 18.6.9. Industry Vertical
- 18.7. Israel Explainable AI Market
- 18.7.1. Country Segmental Analysis
- 18.7.2. Component
- 18.7.3. Deployment Mode
- 18.7.4. Technology
- 18.7.5. Model Type
- 18.7.6. Enterprise Size
- 18.7.7. Function
- 18.7.8. Application
- 18.7.9. Industry Vertical
- 18.8. Rest of Middle East Explainable AI Market
- 18.8.1. Country Segmental Analysis
- 18.8.2. Component
- 18.8.3. Deployment Mode
- 18.8.4. Technology
- 18.8.5. Model Type
- 18.8.6. Enterprise Size
- 18.8.7. Function
- 18.8.8. Application
- 18.8.9. Industry Vertical
- 19. Africa Explainable AI Market Analysis
- 19.1. Key Segment Analysis
- 19.2. Regional Snapshot
- 19.3. Africa Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 19.3.1. Component
- 19.3.2. Deployment Mode
- 19.3.3. Technology
- 19.3.4. Model Type
- 19.3.5. Enterprise Size
- 19.3.6. Function 0
- 19.3.7. Application
- 19.3.8. Industry Vertical
- 19.3.9. Country
- 19.3.9.1. South Africa
- 19.3.9.2. Egypt
- 19.3.9.3. Nigeria
- 19.3.9.4. Algeria
- 19.3.9.5. Rest of Africa
- 19.4. South Africa Explainable AI Market
- 19.4.1. Country Segmental Analysis
- 19.4.2. Component
- 19.4.3. Deployment Mode
- 19.4.4. Technology
- 19.4.5. Model Type
- 19.4.6. Enterprise Size
- 19.4.7. Function
- 19.4.8. Application
- 19.4.9. Industry Vertical
- 19.5. Egypt Explainable AI Market
- 19.5.1. Country Segmental Analysis
- 19.5.2. Component
- 19.5.3. Deployment Mode
- 19.5.4. Technology
- 19.5.5. Model Type
- 19.5.6. Enterprise Size
- 19.5.7. Function
- 19.5.8. Application
- 19.5.9. Industry Vertical
- 19.6. Nigeria Explainable AI Market
- 19.6.1. Country Segmental Analysis
- 19.6.2. Component
- 19.6.3. Deployment Mode
- 19.6.4. Technology
- 19.6.5. Model Type
- 19.6.6. Enterprise Size
- 19.6.7. Function
- 19.6.8. Application
- 19.6.9. Industry Vertical
- 19.7. Algeria Explainable AI Market
- 19.7.1. Country Segmental Analysis
- 19.7.2. Component
- 19.7.3. Deployment Mode
- 19.7.4. Technology
- 19.7.5. Model Type
- 19.7.6. Enterprise Size
- 19.7.7. Function
- 19.7.8. Application
- 19.7.9. Industry Vertical
- 19.8. Rest of Africa Explainable AI Market
- 19.8.1. Country Segmental Analysis
- 19.8.2. Component
- 19.8.3. Deployment Mode
- 19.8.4. Technology
- 19.8.5. Model Type
- 19.8.6. Enterprise Size
- 19.8.7. Function
- 19.8.8. Application
- 19.8.9. Industry Vertical
- 20. South America Explainable AI Market Analysis
- 20.1. Key Segment Analysis
- 20.2. Regional Snapshot
- 20.3. South America Explainable AI Market Size (Value - US$ Bn), Analysis, and Forecasts, 2021-2035
- 20.3.1. Component
- 20.3.2. Deployment Mode
- 20.3.3. Technology
- 20.3.4. Model Type
- 20.3.5. Enterprise Size
- 20.3.6. Function
- 20.3.7. Application
- 20.3.8. Industry Vertical
- 20.3.9. Country
- 20.3.9.1. Brazil
- 20.3.9.2. Argentina
- 20.3.9.3. Rest of South America
- 20.4. Brazil Explainable AI Market
- 20.4.1. Country Segmental Analysis
- 20.4.2. Component
- 20.4.3. Deployment Mode
- 20.4.4. Technology
- 20.4.5. Model Type
- 20.4.6. Enterprise Size
- 20.4.7. Function
- 20.4.8. Application
- 20.4.9. Industry Vertical
- 20.5. Argentina Explainable AI Market
- 20.5.1. Country Segmental Analysis
- 20.5.2. Component
- 20.5.3. Deployment Mode
- 20.5.4. Technology
- 20.5.5. Model Type
- 20.5.6. Enterprise Size
- 20.5.7. Function
- 20.5.8. Application
- 20.5.9. Industry Vertical
- 20.6. Rest of South America Explainable AI Market
- 20.6.1. Country Segmental Analysis
- 20.6.2. Component
- 20.6.3. Deployment Mode
- 20.6.4. Technology
- 20.6.5. Model Type
- 20.6.6. Enterprise Size
- 20.6.7. Function
- 20.6.8. Application
- 20.6.9. Industry Vertical
- 21. Key Players/ Company Profile
- 21.1. Aible, Inc.
- 21.1.1. Company Details/ Overview
- 21.1.2. Company Financials
- 21.1.3. Key Customers and Competitors
- 21.1.4. Business/ Industry Portfolio
- 21.1.5. Product Portfolio/ Specification Details
- 21.1.6. Pricing Data
- 21.1.7. Strategic Overview
- 21.1.8. Recent Developments
- 21.2. Amazon Web Services, Inc.
- 21.3. Arthur AI
- 21.4. DarwinAI Corp.
- 21.5. DataRobot, Inc.
- 21.6. Fiddler AI
- 21.7. Google LLC (Alphabet Inc.)
- 21.8. H2O.ai, Inc.
- 21.9. IBM Corporation
- 21.10. IBM Watson Studio
- 21.11. Intel Corporation
- 21.12. Kyndi, Inc.
- 21.13. Microsoft Corporation
- 21.14. NVIDIA Corporation
- 21.15. Oracle Corporation
- 21.16. Pymetrics Inc.
- 21.17. Salesforce, Inc.
- 21.18. SAP SE
- 21.19. SAS Institute Inc.
- 21.20. Zest AI
- 21.21. Others Key Players
- 21.1. Aible, Inc.
Note* - This is just tentative list of players. While providing the report, we will cover more number of players based on their revenue and share for each geography
Our research design integrates both demand-side and supply-side analysis through a balanced combination of primary and secondary research methodologies. By utilizing both bottom-up and top-down approaches alongside rigorous data triangulation methods, we deliver robust market intelligence that supports strategic decision-making.
MarketGenics' comprehensive research design framework ensures the delivery of accurate, reliable, and actionable market intelligence. Through the integration of multiple research approaches, rigorous validation processes, and expert analysis, we provide our clients with the insights needed to make informed strategic decisions and capitalize on market opportunities.
MarketGenics leverages a dedicated industry panel of experts and a comprehensive suite of paid databases to effectively collect, consolidate, and analyze market intelligence.
Our approach has consistently proven to be reliable and effective in generating accurate market insights, identifying key industry trends, and uncovering emerging business opportunities.
Through both primary and secondary research, we capture and analyze critical company-level data such as manufacturing footprints, including technical centers, R&D facilities, sales offices, and headquarters.
Our expert panel further enhances our ability to estimate market size for specific brands based on validated field-level intelligence.
Our data mining techniques incorporate both parametric and non-parametric methods, allowing for structured data collection, sorting, processing, and cleaning.
Demand projections are derived from large-scale data sets analyzed through proprietary algorithms, culminating in robust and reliable market sizing.
The bottom-up approach builds market estimates by starting with the smallest addressable market units and systematically aggregating them to create comprehensive market size projections.
This method begins with specific, granular data points and builds upward to create the complete market landscape.
Customer Analysis → Segmental Analysis → Geographical Analysis
The top-down approach starts with the broadest possible market data and systematically narrows it down through a series of filters and assumptions to arrive at specific market segments or opportunities.
This method begins with the big picture and works downward to increasingly specific market slices.
TAM → SAM → SOM
While analysing the market, we extensively study secondary sources, directories, and databases to identify and collect information useful for this technical, market-oriented, and commercial report. Secondary sources that we utilize are not only the public sources, but it is combination of Open Source, Associations, Paid Databases, MG Repository & Knowledgebase and Others.
- Company websites, annual reports, financial reports, broker reports, and investor presentations
- National government documents, statistical databases and reports
- News articles, press releases and web-casts specific to the companies operating in the market, Magazines, reports, and others
- We gather information from commercial data sources for deriving company specific data such as segmental revenue, share for geography, product revenue, and others
- Internal and external proprietary databases (industry-specific), relevant patent, and regulatory databases
- Governing Bodies, Government Organizations
- Relevant Authorities, Country-specific Associations for Industries
We also employ the model mapping approach to estimate the product level market data through the players product portfolio
Primary research/ interviews is vital in analyzing the market. Most of the cases involves paid primary interviews. Primary sources includes primary interviews through e-mail interactions, telephonic interviews, surveys as well as face-to-face interviews with the different stakeholders across the value chain including several industry experts.
| Type of Respondents | Number of Primaries |
|---|---|
| Tier 2/3 Suppliers | ~20 |
| Tier 1 Suppliers | ~25 |
| End-users | ~25 |
| Industry Expert/ Panel/ Consultant | ~30 |
| Total | ~100 |
MG Knowledgebase
• Repository of industry blog, newsletter and case studies
• Online platform covering detailed market reports, and company profiles
- Historical Trends – Past market patterns, cycles, and major events that shaped how markets behave over time. Understanding past trends helps predict future behavior.
- Industry Factors – Specific characteristics of the industry like structure, regulations, and innovation cycles that affect market dynamics.
- Macroeconomic Factors – Economic conditions like GDP growth, inflation, and employment rates that affect how much money people have to spend.
- Demographic Factors – Population characteristics like age, income, and location that determine who can buy your product.
- Technology Factors – How quickly people adopt new technology and how much technology infrastructure exists.
- Regulatory Factors – Government rules, laws, and policies that can help or restrict market growth.
- Competitive Factors – Analyzing competition structure such as degree of competition and bargaining power of buyers and suppliers.
Multiple Regression Analysis
- Identify and quantify factors that drive market changes
- Statistical modeling to establish relationships between market drivers and outcomes
Time Series Analysis – Seasonal Patterns
- Understand regular cyclical patterns in market demand
- Advanced statistical techniques to separate trend, seasonal, and irregular components
Time Series Analysis – Trend Analysis
- Identify underlying market growth patterns and momentum
- Statistical analysis of historical data to project future trends
Expert Opinion – Expert Interviews
- Gather deep industry insights and contextual understanding
- In-depth interviews with key industry stakeholders
Multi-Scenario Development
- Prepare for uncertainty by modeling different possible futures
- Creating optimistic, pessimistic, and most likely scenarios
Time Series Analysis – Moving Averages
- Sophisticated forecasting for complex time series data
- Auto-regressive integrated moving average models with seasonal components
Econometric Models
- Apply economic theory to market forecasting
- Sophisticated economic models that account for market interactions
Expert Opinion – Delphi Method
- Harness collective wisdom of industry experts
- Structured, multi-round expert consultation process
Monte Carlo Simulation
- Quantify uncertainty and probability distributions
- Thousands of simulations with varying input parameters
Our research framework is built upon the fundamental principle of validating market intelligence from both demand and supply perspectives. This dual-sided approach ensures comprehensive market understanding and reduces the risk of single-source bias.
Demand-Side Analysis: We understand end-user/application behavior, preferences, and market needs along with the penetration of the product for specific application.
Supply-Side Analysis: We estimate overall market revenue, analyze the segmental share along with industry capacity, competitive landscape, and market structure.
Data triangulation is a validation technique that uses multiple methods, sources, or perspectives to examine the same research question, thereby increasing the credibility and reliability of research findings. In market research, triangulation serves as a quality assurance mechanism that helps identify and minimize bias, validate assumptions, and ensure accuracy in market estimates.
- Data Source Triangulation – Using multiple data sources to examine the same phenomenon
- Methodological Triangulation – Using multiple research methods to study the same research question
- Investigator Triangulation – Using multiple researchers or analysts to examine the same data
- Theoretical Triangulation – Using multiple theoretical perspectives to interpret the same data
