As AI continues to shape industries, explainability is becoming essential for building trust. For AI to be trusted, users must understand how and why it generates its outputs. 🤔
This goes beyond simply explaining algorithms—it’s about providing clear, verifiable explanations of data lineage and the sources that inform decisions, especially in high-risk use cases.
In fact, most executives in our research recognize the importance of explainability, with 78% maintaining documentation, 74% conducting ethical assessments, and 70% testing for risks. It's clear: trustworthy, explainable AI is the future of innovation.
📥 Read the full report to learn about the three critical trust factors, including explainability, that can't be ignored in AI governance: https://ibm.co/3VAV0EN