The global explainable AI market size accounted for USD 9.54 billion in 2024, grew to USD 11.28 billion in 2025 and is projected to surpass around USD 50.87 billion by 2034, representing a healthy CAGR of 18.22% between 2024 and 2034. The North America explainable AI market size is calculated at USD 3.91 billion in 2024 and is expected to grow at a fastest CAGR of 18.36% during the forecast year.
The global explainable AI market size is estimated at USD 9.54 billion in 2024 and is anticipated to reach around USD 50.87 billion by 2034, expanding at a CAGR of 18.22% between 2024 and 2034.
The U.S. explainable AI market size accounted for USD 9.54 billion in 2024 and is predicted to be worth around USD 50.87 billion by 2034, growing at a CAGR of 18.22% from 2024 to 2034.
North America dominated the global explainable AI market in 2023, the region is predicted to maintain its dominance during the forecast period. The rapid adoption of technology along with the presence of massive information technology (IT) infrastructure supported the growth of the market in North America. The nations such as the United States and Canada are observed to be the largest contributors to the market. The willingness to adapt advanced technologies for operational solutions and services by multiple industries/end-users promotes the growth of the explainable AI market in the region.
On the other hand, Asia Pacific is expected to be the most attractive region for the explainable AI market during the forecast period. Favorable economies, emerging technological hubs, adoption of generative services, and the presence of key players to promote technological advancements are a few factors that are expected to accelerate the market’s growth in the Asia Pacific.
Multiple technology-based startups and companies in the region are actively involved in the development of explainable AI solutions, the market in Asia Pacific is witnessing fierce competition which is observed to lead the introduction of advanced AI-based services.
Explainable artificial intelligence is the technology in artificial intelligence that is developed to provide human interpretation explanations for the decision-making process. Explainable AI is used in several industries such as healthcare, automobile, internet and telecommunication, and others. The modern era is almost dependent on emerging technologies and technological innovations. Artificial intelligence is one of the most promising technologies emerging in recent times for organizational growth. The explainable AI is also known as interpretability. Interpretability allows industries/end-users to understand the model of learning and the explanation behind the judgments in light of the real-world issues that are attempting to address. Explainable AI enhances the operations like trustworthiness, transparency, fairness, and accountability of Artificial Intelligent systems.
Explainable AI is used for the organization's development and market growth of it. The continuous technological development in regions like North America and Asia-Pacific has resulted in a major expansion in the growth of the market. The explainable Ai is used for the detection of cybercrime. The accessibility and accuracy of solutions and services offered by explainable AI have highlighted its importance in multiple sectors.
Explainable AI is used for the detection of the problem and increases confidence and elimination of biases in the organization. Explainable AI detects the mistakes and flaws of the system and gives solutions with newer insights. The growth of the explainable AI market is driven by the rising requirements to improve inventory management for better recalling clients by proving the significant retention strategy by providing building trust, improving customer satisfaction, and providing transparency.
| Report Coverage | Details |
| Market Size in 2023 | USD 9.54 Billion |
| Market Size by 2034 | USD 50.87 Billion |
| Growth Rate from 2024 to 2034 | CAGR of 18.22% |
| Largest Market | North America |
| Fastest Growing Market | Asia Pacific |
| Base Year | 2023 |
| Forecast Period | 2024 to 2034 |
| Segments Covered | By Component, By Deployment, By Application, and By End-use |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Rising collaborative activities between human and artificial intelligence
Collaboration between humans and AI is essential to meet regulatory and compliance requirements. Explainable AI enables organizations to provide justifications and evidence for the decisions made by AI systems, ensuring transparency and compliance with regulations. Human collaboration in the interpretation and explanation of AI decisions helps meet legal obligations and regulatory standards. Collaboration between humans and AI facilitates continuous learning and adaptation. Human experts can share their knowledge and expertise with AI systems, enabling them to learn from human feedback and adapt to evolving circumstances. This collaborative learning process improves the AI system's performance over time. Overall, the collaboration between humans and AI drives the growth of the explainable AI market by leveraging the strengths of both parties.
Performance limitations
In highly competitive industries, organizations may prioritize the performance of AI models over interpretability. If black-box models consistently outperform explainable AI models, businesses may be hesitant to adopt explainable AI solutions due to concerns about losing a competitive edge. There is often a trade-off between model interpretability and performance. As models become more interpretable, they may simplify or omit certain complex relationships in the data, leading to a potential decrease in performance. Addressing these performance limitations requires ongoing research and development efforts in the field of explainable AI.
Rising education and awareness about AI
Education and awareness about AI create opportunities for the explainable AI market by fostering understanding, addressing concerns, promoting regulatory compliance, bridging the gap between technical and non-technical stakeholders, empowering users, and encouraging research and innovation in the field of explainable AI. Education and awareness initiatives can inspire researchers, developers, and innovators to explore and advance the field of explainable AI. By highlighting the importance and potential applications of explainability, these initiatives can attract talent, investment, and resources toward developing novel techniques and solutions. This creates a positive feedback loop, where increased research and innovation drive further growth in the explainable AI market.
The solution segment dominated the market in 2023, the segment is expected to continue to witness a noticeable growth during the forecast period. The growth of the segment is attributed to the increasing adoption of AI technologies in multiple industries. Fraud detection is the major part where the explainable AI works. Explainable AI detects fraud and creates insightful solutions to it. In the technological era, cybercrime is one of the major challenges for the government as well as private organizations.
The service segment is expected to grow at a significant rate during the forecast period. The growth of the segment is attributed due to the increase in the services regarding the AI platform. The AI consulting services work to help the organization adopt AI solutions that are interpretable, transparent, and accountable.
The on-premises segment holds the largest share of the market with the largest market share. To build explainable AI on-premises, businesses employ a variety of methods, including rule-based systems, decision trees, and model-based explanations. Due to its security advantages, major businesses choose XAI installed on-premises across a variety of industry verticals, particularly in the BFSI, retail, and government sectors. The system employs machine learning to evaluate massive amounts of data, spot possibly fraudulent activity, and offer concise and honest justifications for its judgments.
The fraud and anomaly detection segment dominated the market in 2023 The segment is expected to maintain growth during the forecast period. Fraud and anomaly detection often require a combination of machine-learning algorithms and human expertise. Explainable AI models facilitate collaboration between human analysts and AI systems. By providing interpretable outputs, these models enable analysts to identify patterns, generate insights, and contribute their domain knowledge to enhance the overall detection capabilities.
The IT and telecommunications segment dominated the market in 2023, the segment will continue to grow at a significant rate during the forecast period. The It and telecommunications sectors generate massive amounts of data from multiple sources, the data is valuable for training AI models. Explainable AI solutions enable these sectors to leverage their data effectively and derive actionable insights. The requirements for consumer interactions and network logs from the IT and telecommunications sectors support the growth of the segment.
On the other hand, the retail and e-commerce segment will grow at a robust pace during the forecast period. Along with a globally expanded consumer base, e-commerce businesses are susceptible to fraud. The risk in online transaction fraud and inventory management has raised the requirements for explainable AI solutions and services by retail and e-commerce businesses.
Segments Covered in the Report:
By Component
By Deployment
By Application
By End-use
By Geography
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