The hidden crisis behind AI’s promise: Why data quality became an afterthought

Companies rushed to adopt AI without robust data foundations, resulting in unreliable outputs and amplified biases, prompting regulatory scrutiny and a need for improved data stewardship to ensure high-quality, contextually appropriate data for AI systems.