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Global Explainable AI Market to reach USD 20.64 billion by the end of 2030

Global Explainable AI Market Size Study & Forecast, by Component (Solution, Services), By Deployment (Cloud, On-Premises), By Application (Fraud and anomaly detection, Drug discovery & diagnostics, Predictive maintenance, Supply chain management, Identity and access management), By End-use (Healthcare, BFSI, Aerospace & Defense, Retail and e-commerce, IT & telecommunication, Others), and Regional Analysis, 2023-2030

Product Code: ICTNGT-33547292
Publish Date: 10-08-2023
Page: 200

Global Explainable AI Market is valued at approximately USD 5.49 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 18.0% over the forecast period 2023-2030. Explainable AI refers to the development of artificial intelligence (AI) systems that provide understandable and transparent explanations for their decision-making processes. Explainable AI (XAI) is a field of study that focuses on developing methods for explaining the decisions made by AI models. XAI is important because it helps users to understand how AI models work and why they make the decisions they do. This helps users to trust AI models and to use them more effectively. The rising trend of digitalization, growing customer expectations and user experience, coupled with the increasing number of favorable government initiatives are the most prominent factors that are propelling the market demand across the globe.

In addition, the increase in applications of explainable AI across the healthcare sector is acting as a catalyzing factor during the estimated period. Explainable AI is utilized for medical diagnosis and treatment recommendations and helps doctors and other healthcare professionals to comprehend and believe the judgments made by AI algorithms. Explainable models give explanations for diagnosis, offer viable therapies, and highlight pertinent medical issues, empowering healthcare professionals to make better-educated choices. According to the Statista analysis, in 2021, the global market for Artificial intelligence (AI) in healthcare was estimated to be worth around USD 11.06 billion. In addition, it is projected that the market grows and reached USD 38.66 billion by 2025 and USD 187.95 by 2030. Thereby, these aforementioned factors are likely to boost the market expansion globally. Moreover, the emerging technological advancements and the development of AI, as well as the rising number of strategic initiatives by the key market players present various lucrative opportunities over the forecasting years. However, the high cost of explainable AI solutions and the lack of skilled professionals are hindering the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Explainable AI Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the presence of a strong IT infrastructure, as well as surging demand for AI-powered solutions. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecasting years. The growing need for compliance with regulations, rising investment in XAI research and development, and increasing advancements in hardware and parallel processing are significantly propelling the market demand across the region.

Major market players included in this report are:
Amelia US LLC
BuildGroup
DataRobot, Inc.
Ditto.ai
DarwinAI
Factmata
Google LLC
IBM Corporation
Kyndi
Microsoft Corporation

Recent Developments in the Market:
Ø In March 2023, Monroe Capital and BuildGroup teamed with AI company Amelia to supply financial funding and managerial expertise. The strategic partnership accelerates the commercialization of Amelia’s AI solutions. The strategic partnership hastens the commercialization of Amelia’s AI solutions. BuildGroup and Monroe Capital are leading the USD 175 million transactions with this round of funding. Amelia has the required resources to maintain its market-leading position and increase its dedication to offering its customers cutting-edge, comprehensible AI technologies.

Global Explainable AI Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Deployment, Application, End-use, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
Solution
Services

By Deployment:
Cloud
On-Premises

By Application:
Fraud and anomaly detection
Drug discovery & diagnostics
Predictive maintenance
Supply chain management
Identity and access management

By End-use:
Healthcare
BFSI
Aerospace & defense
Retail and e-commerce
IT & telecommunication
Others

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Explainable AI Market, by Region, 2020-2030 (USD Billion)
1.2.2. Explainable AI Market, by Component, 2020-2030 (USD Billion)
1.2.3. Explainable AI Market, by Deployment, 2020-2030 (USD Billion)
1.2.4. Explainable AI Market, by Application, 2020-2030 (USD Billion)
1.2.5. Explainable AI Market, by End-use, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Explainable AI Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Explainable AI Market Dynamics
3.1. Explainable AI Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing number of favorable government initiatives
3.1.1.2. Increase in applications of explainable AI across the healthcare sector
3.1.2. Market Challenges
3.1.2.1. High cost of Explainable AI Solutions
3.1.2.2. Lack of skilled professionals
3.1.3. Market Opportunities
3.1.3.1. Emerging technological advancements and the development of AI
3.1.3.2. Rising number of strategic initiatives by the key market players
Chapter 4. Global Explainable AI Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Explainable AI Market, by Component
5.1. Market Snapshot
5.2. Global Explainable AI Market by Component, Performance – Potential Analysis
5.3. Global Explainable AI Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Explainable AI Market, Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global Explainable AI Market, by Deployment
6.1. Market Snapshot
6.2. Global Explainable AI Market by Deployment, Performance – Potential Analysis
6.3. Global Explainable AI Market Estimates & Forecasts by Deployment 2020-2030 (USD Billion)
6.4. Explainable AI Market, Sub Segment Analysis
6.4.1. Cloud
6.4.2. On-Premises
Chapter 7. Global Explainable AI Market, by Application
7.1. Market Snapshot
7.2. Global Explainable AI Market by Application, Performance – Potential Analysis
7.3. Global Explainable AI Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
7.4. Explainable AI Market, Sub Segment Analysis
7.4.1. Fraud and anomaly detection
7.4.2. Drug discovery & diagnostics
7.4.3. Predictive maintenance
7.4.4. Supply chain management
7.4.5. Identity and access management
Chapter 8. Global Explainable AI Market, by End-use
8.1. Market Snapshot
8.2. Global Explainable AI Market by End-use, Performance – Potential Analysis
8.3. Global Explainable AI Market Estimates & Forecasts by End-use 2020-2030 (USD Billion)
8.4. Explainable AI Market, Sub Segment Analysis
8.4.1. Healthcare
8.4.2. BFSI
8.4.3. Aerospace & defense
8.4.4. Retail and e-commerce
8.4.5. IT & telecommunication
8.4.6. Others
Chapter 9. Global Explainable AI Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Explainable AI Market, Regional Market Snapshot
9.4. North America Explainable AI Market
9.4.1. U.S. Explainable AI Market
9.4.1.1. Component breakdown estimates & forecasts, 2020-2030
9.4.1.2. Deployment breakdown estimates & forecasts, 2020-2030
9.4.1.3. Application breakdown estimates & forecasts, 2020-2030
9.4.1.4. End-use breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Explainable AI Market
9.5. Europe Explainable AI Market Snapshot
9.5.1. U.K. Explainable AI Market
9.5.2. Germany Explainable AI Market
9.5.3. France Explainable AI Market
9.5.4. Spain Explainable AI Market
9.5.5. Italy Explainable AI Market
9.5.6. Rest of Europe Explainable AI Market
9.6. Asia-Pacific Explainable AI Market Snapshot
9.6.1. China Explainable AI Market
9.6.2. India Explainable AI Market
9.6.3. Japan Explainable AI Market
9.6.4. Australia Explainable AI Market
9.6.5. South Korea Explainable AI Market
9.6.6. Rest of Asia Pacific Explainable AI Market
9.7. Latin America Explainable AI Market Snapshot
9.7.1. Brazil Explainable AI Market
9.7.2. Mexico Explainable AI Market
9.8. Middle East & Africa Explainable AI Market
9.8.1. Saudi Arabia Explainable AI Market
9.8.2. South Africa Explainable AI Market
9.8.3. Rest of Middle East & Africa Explainable AI Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Amelia US LLC
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. BuildGroup
10.3.3. DataRobot, Inc.
10.3.4. Ditto.ai
10.3.5. DarwinAI
10.3.6. Factmata
10.3.7. Google LLC
10.3.8. IBM Corporation
10.3.9. Kyndi
10.3.10. Microsoft Corporation
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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