Explainable AI Market worth $25.52 billion by 2030, growing at a CAGR of 20.17% - Exclusive Report by 360iResearch
The Global Explainable AI Market to grow from USD 5.86 billion in 2022 to USD 25.52 billion by 2030, at a CAGR of 20.17%.
PUNE, MAHARASHTRA, INDIA , December 8, 2023 /EINPresswire.com/ -- The "Explainable AI Market by Offering (Services, Software), Deployment (Cloud-based, On-premise), Application, End-Use - Global Forecast 2023-2030" report has been added to 360iResearch.com's offering.The Global Explainable AI Market to grow from USD 5.86 billion in 2022 to USD 25.52 billion by 2030, at a CAGR of 20.17%.
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Explainable artificial intelligence (XAI) includes technologies that enable the interpretability and transparency of AI systems, allowing users to understand and trust the decision-making processes of complex algorithms. XAI is crucial, especially in applications where AI-driven decisions impact individuals or businesses. The growing need for accountability and ethical AI practices, particularly in sectors such as finance, healthcare, and law, is elevating the demand for explainable AI. Regulatory requirements emphasizing transparency and interpretability further contribute to the adoption of XAI solutions. Additionally, the increasing complexity of AI models and their applications heightens the demand for explainability, ensuring that decisions can be comprehended and validated. Striking the right balance between explainability and performance hinders the development and deployment of XAI systems. The integration of XAI in sectors, including healthcare for enhanced diagnostics and personalized treatment plans, fuels the market growth of the explainable AI market. Continuous innovations in the development of novel explainable artificial intelligence solutions by market vendors are expected to create opportunities for market growth.
Application: Expanding application of explainable AI in drug discovery and diagnostics for personalized treatment
Explainable AI is revolutionizing the worlds of drug discovery and diagnostics by shortening the development phases of drugs and enhancing diagnostic accuracy. The need-based preference for AI in this field emanates from its integral role in deciphering biological complexities, rare disease identification, and the development of personalized treatment plans. Explainable AI in fraud and anomaly detection is pivotal in providing transparent explanations for detected anomalies, mitigating false positives, and enhancing trust in the system. It caters to the needs of forensic auditors, security analysts, and financial institutions seeking comprehensive reporting and auditing capabilities. Explainable AI's application in identity and access management focuses on securing digital identities and controlling access within a system. The need for AI is driven by the exigencies of reliable user-behavior profiling and the prevention of unauthorized access. The use of Explainable AI for predictive maintenance allows for proactive management of equipment, decreased downtime, and substantial cost savings. Its demand is driven by the necessity to understand and predict equipment failures in industries such as manufacturing and energy. Explainable AI has the potential to transform supply chain management in demand forecasting, inventory optimization, and identifying bottlenecks within the supply chain.
Offering: Advancements in integrated software solutions for high data processing allows clearer analytics and decision-making processes
AI/ML enabled services primarily utilize artificial intelligence (AI) and machine learning (ML) algorithms to provide predictive and prescriptive analytics for various business operations. They can automate data analysis, enabling organizations to make well-informed decisions by utilizing insights from large datasets. Consulting services in Explainable AI are designed to provide businesses with expert advice on how to leverage AI technologies effectively. These services guide organizations on AI governance, ethics, and risk management, help design data strategies, provide AI literacy training, and assist in the development of AI proof of concepts. Cutting-edge AI/ML research services are focused on developing innovative AI and ML algorithms and solutions. These services explore the latest trends in the AI space, such as deep learning, reinforcement learning, and natural language processing. Data engineering services cater to the design, building, and maintenance of data architectures and databases necessary for data-driven business decisions. These services provide businesses with robust data pipelines for efficient data extraction, transformation, and loading. Data science advisory services involve expert strategic advice on managing, organizing, and interpreting large datasets. These services assist organizations in embracing data-centric practices, defining data strategy, implementing data governance practices, identifying key metrics, and setting KPIs. Training and education services in the domain of Explainable AI offer comprehensive training programs, workshops, webinars, and e-learning modules for knowledge sharing, skill upgradation, and comprehension enhancement. Automated Reporting Tools in the realm of Explainable AI make use of comprehensive algorithms to generate reports that explicate the decision-making processes of an artificial intelligence model. The tools significantly reduce human effort and bring in higher precision while delineating complex AI algorithms, thus facilitating transparency and trustworthiness of AI systems. Integrated Software in Explainable AI refers to those software solutions that incorporate a compelling mix of AI and explainability features within a single suite. It enables seamless collaboration between AI and its explainability tools, thereby ensuring that AI decisions are understandable, controllable, and auditable. Interactive Visualization Platforms in Explainable AI act as a visual interface between the user and the AI algorithms. They help in demystifying the black-box nature of AI systems by presenting the complex decision-making processes in a visually understandable format. Standalone software in Explainable AI refers to those software applications dedicated to providing explainability features separately, without being integrated within the AI system. With a major focus on system interpretability and transparency, these dedicated tools probe into the decision mechanisms of the AI, providing insights into its inner workings.
Deployment: Growing preference for cloud-based explainable AI deployment due to its affordability and ease of access
Cloud-based AI services offer the advantage of providing advanced analytical power to companies that lack the resources to run and maintain in-house AI systems. This model can be procured on an as-needed basis, explaining its growing popularity, particularly among startups and smaller organizations. On-premise AI solutions provide robust and customized AI implementation with greater control over data and increased compliance to high-security standards. Larger corporations or those dealing with sensitive data often prefer this model.
End-Use: Emerging application of explainable AI in aerospace and defense sector enabling transparent decision making and risk analysis
Explainable AI is used to facilitate decision-making processes and simulate virtual environments in the aerospace and defense sector. It aids in complex data analysis, predictive maintenance, and risk assessment. In the automotive industry, Explainable AI offers value in autonomous driving, predictive maintenance, and streamlining manufacturing processes. Explainable AI in BFSI aids in predictive analysis, fraud detection, risk modeling, and customer service. Explainable AI is vital for smart grids, energy management, and predictive maintenance in the energy & utilities sector. Explainable AI is instrumental for predictive analysis in disease diagnosis, patient care, drug discovery, and health records management. Explainable AI empowers predictive maintenance, network optimization, and customer service in this sector. AI improves content creation, audience analysis, and recommendation systems in the media & entertainment sector. The public sector uses AI for public safety, social welfare, and smart city initiatives. Explainable AI aids in customer behavior prediction, sales forecasting, inventory management, and recommendation systems in retail.
Regional Insights:
In the Americas, the explainable artificial intelligence (XAI) market is experiencing substantial growth, driven by a heightened awareness of the importance of transparent and interpretable AI systems. North America, in particular, plays a pivotal role in advancing the market, benefitting from a strong emphasis on technology innovation and regulatory frameworks. As the demand for trustworthy AI decision-making processes continues to rise, the Americas remain at the forefront of embracing and integrating explainable AI solutions, creating a dynamic landscape for innovation and adoption in the region. In the Asia-Pacific region, the explainable artificial intelligence (XAI) market is driven by a growing recognition of the need for transparent AI decision-making. Countries such as China and India are actively adopting XAI solutions across diverse industries, including finance, healthcare, and manufacturing. The region benefits from rapid technological advancements and an increasing focus on ethical AI practices. European countries, in particular, are adopting XAI solutions due to the presence of a strong regulatory framework and a commitment to transparency in AI decision-making processes. As the demand for interpretable AI systems continues to rise, EMEA remains a significant region in the advancement and integration of explainable AI solutions.
FPNV Positioning Matrix:
The FPNV Positioning Matrix is essential for assessing the Explainable AI Market. It provides a comprehensive evaluation of vendors by examining key metrics within Business Strategy and Product Satisfaction, allowing users to make informed decisions based on their specific needs. This advanced analysis then organizes these vendors into four distinct quadrants, which represent varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital(V).
Market Share Analysis:
The Market Share Analysis offers an insightful look at the current state of vendors in the Explainable AI Market. By comparing vendor contributions to overall revenue, customer base, and other key metrics, we can give companies a greater understanding of their performance and what they are up against when competing for market share. The analysis also sheds light on just how competitive any given sector is about accumulation, fragmentation dominance, and amalgamation traits over the base year period studied.
Key Company Profiles:
The report delves into recent significant developments in the Explainable AI Market, highlighting leading vendors and their innovative profiles. These include Abzu ApS, Alphabet Inc., Alteryx, Inc., ArthurAI, Inc., C3.ai, Inc., DarwinAI, DataRobot, Inc., Equifax Inc., Fair Isaac Corporation, Fiddler Labs, Inc., H2O.ai, Inc., Intel Corporation, Intellico.ai s.r.l, International Business Machines Corporation, ISSQUARED Inc., Kyndi, Inc., Microsoft Corporation, Mphasis Limited, NVIDIA Corporation, Salesforce, Inc., SAS Institute Inc., Squirro Group, Temenos Headquarters SA, Tensor AI Solutions GmbH, Tredence Analytics Solutions Pvt. Ltd., and ZestFinance Inc..
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Market Segmentation & Coverage:
This research report categorizes the Explainable AI Market in order to forecast the revenues and analyze trends in each of following sub-markets:
Based on Offering, market is studied across Services and Software. The Services is further studied across AI/ML Enabled Service, Consulting Services, Cutting Edge AI/ML Research, Data Engineering Services, Data Science Advisory Services, and Training & Education Services. The Software is further studied across Automated Reporting Tools, Integrated Software, Interactive Visualization Platform, and Standalone Software. The Software is projected to witness significant market share during forecast period.
Based on Deployment, market is studied across Cloud-based and On-premise. The Cloud-based is projected to witness significant market share during forecast period.
Based on Application, market is studied across Drug Discovery & Diagnostics, Fraud & Anomaly Detection, Identity & Access Management, Predictive Maintenance, and Supply Chain Management. The Supply Chain Management is projected to witness significant market share during forecast period.
Based on End-Use, market is studied across Aerospace & Defense, Automotive, Banking, Financial Services, & Insurance (BFSI), Energy & Utilities, Healthcare, IT & Telecommunications, Media & Entertainment, Public Sector & Government, and Retail & eCommerce. The Public Sector & Government is projected to witness significant market share during forecast period.
Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom. The Americas commanded largest market share of 42.91% in 2022, followed by Europe, Middle East & Africa.
Key Topics Covered:
1. Preface
2. Research Methodology
3. Executive Summary
4. Market Overview
5. Market Insights
6. Explainable AI Market, by Offering
7. Explainable AI Market, by Deployment
8. Explainable AI Market, by Application
9. Explainable AI Market, by End-Use
10. Americas Explainable AI Market
11. Asia-Pacific Explainable AI Market
12. Europe, Middle East & Africa Explainable AI Market
13. Competitive Landscape
14. Competitive Portfolio
15. Appendix
The report provides insights on the following pointers:
1. Market Penetration: Provides comprehensive information on the market offered by the key players
2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes penetration across mature segments of the markets
3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments
4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players
5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments
The report answers questions such as:
1. What is the market size and forecast of the Explainable AI Market?
2. Which are the products/segments/applications/areas to invest in over the forecast period in the Explainable AI Market?
3. What is the competitive strategic window for opportunities in the Explainable AI Market?
4. What are the technology trends and regulatory frameworks in the Explainable AI Market?
5. What is the market share of the leading vendors in the Explainable AI Market?
6. What modes and strategic moves are considered suitable for entering the Explainable AI Market?
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Mr. Ketan Rohom
360iResearch
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ketan@360iresearch.com
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