As generic AI models plateau, organizations must customize LLMs for their specific domains to achieve meaningful performance breakthroughs.

Large language models have shifted from delivering 10x capability jumps per iteration to providing only incremental improvements in general-purpose applications

Domain-specialized AI models remain the exception, continuing to show step-function improvements and significant competitive advantages

Organizations are moving toward customizing AI models by integrating them with proprietary data and workflows rather than relying on generic foundational models