Based on data, AI systems make optimized decisions, generate specific recommendations, and provide estimates and forecasts. The underlying, highly complex algorithms with up to billions of parameters appear as 'black boxes' to their developers and users.
Explainable AI (XAI) allows to make the decisions of even the most complex AI systems comprehensible for different target audiences — even without interfering with the AI system's inner workings.
This way, the strengths of modern AI technology can be harnessed even where business risks and regulatory requirements currently prevent their application.