PUBLISHER: TechSci Research | PRODUCT CODE: 1901611
PUBLISHER: TechSci Research | PRODUCT CODE: 1901611
We offer 8 hour analyst time for an additional research. Please contact us for the details.
The Global Explainable AI Market will grow from USD 6.81 Billion in 2025 to USD 19.04 Billion by 2031 at a 18.69% CAGR. Explainable AI (XAI) defines a set of protocols and methods that enable human users to comprehend and validate the outputs generated by machine learning algorithms.
| Market Overview | |
|---|---|
| Forecast Period | 2027-2031 |
| Market Size 2025 | USD 6.81 Billion |
| Market Size 2031 | USD 19.04 Billion |
| CAGR 2026-2031 | 18.69% |
| Fastest Growing Segment | Cloud |
| Largest Market | North America |
Key Market Drivers
The implementation of stringent government regulations and compliance mandates acts as a primary catalyst for the Global Explainable AI Market. Governments worldwide are enforcing legal frameworks that require transparency in automated decision-making processes to prevent bias and ensure accountability. These legislative measures compel organizations to adopt explainable AI (XAI) solutions that can deconstruct complex model behaviors into interpretable audits for regulators.
Key Market Challenges
The primary challenge hampering the Global Explainable AI Market is the inherent trade-off between predictive accuracy and model interpretability, often described as the "black box" problem. As organizations strive for higher performance, they frequently deploy complex deep learning models that offer superior accuracy but lack transparent logic. This opacity creates substantial friction in regulated industries such as finance and healthcare, where stakeholders must validate decisions to meet strict compliance and liability standards.
Key Market Trends
Integration of Explainability into MLOps and LLMOps Workflows marks a pivotal shift in the market, moving interpretability from ad-hoc analysis to a continuous, embedded function within deployment pipelines. Enterprises are increasingly prioritizing real-time observability to manage the operational complexity of Large Language Models (LLMs), where tracing retrieval contexts and validating outputs are essential for maintaining reliability. This technical integration allows engineering teams to instantaneously diagnose hallucinations or drift, ensuring that model behavior aligns with intended logic during production scaling.
In this report, the Global Explainable AI Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Explainable AI Market.
Global Explainable AI Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: