- Report
- August 2024
- 200 Pages
Global
From €1657EUR$1,821USD£1,408GBP
€2367EUR$2,601USD£2,011GBP
- Report
- November 2023
- 274 Pages
Global
From €2275EUR$2,499USD£1,932GBP
€3249EUR$3,570USD£2,760GBP
- Report
- December 2021
- 332 Pages
Japan
From €2362EUR$2,595USD£2,006GBP
€3374EUR$3,707USD£2,866GBP
- Book
- May 2025
- 384 Pages
- Book
- March 2025
- 704 Pages
- Book
- June 2024
- 432 Pages

Explainable AI (XAI) is a subfield of Artificial Intelligence (AI) that focuses on making AI models more transparent and interpretable. XAI seeks to explain the decisions made by AI models, which are often opaque and difficult to understand. XAI techniques can be used to identify and explain the factors that influence a model’s decisions, as well as to detect and mitigate potential biases. XAI can also be used to improve the accuracy and reliability of AI models.
XAI is becoming increasingly important as AI models are used in more and more applications, such as healthcare, finance, and autonomous vehicles. XAI can help ensure that AI models are making decisions that are fair, accurate, and reliable.
Companies in the Explainable AI market include IBM, Microsoft, Google, Amazon, and Salesforce. Other companies, such as Dessa, H2O.ai, and DataRobot, are also developing XAI solutions. Show Less Read more