Generative AI models are now embedded in everyday life, fueling major enthusiasm across enterprises and startups. As demand accelerates, organizations continue to invest heavily in AI-led products and services. Yet one question remains unresolved: Why do 85% of AI projects still fail?
The causes are technical, but the pattern is consistent: systems struggle with fragmented, complex data and fail to extract reliable meaning from it. That leads to a foundational question: What is an ontology, and how does it help ... [continue reading]
