Large language models (LLMs) like GPT-4 have captivated business leaders with the promise of enhanced decision-making, streamlined operations, and new innovation. Companies such as Zendesk and Slack have started using LLMs to advance customer support, improving satisfaction and reducing costs. Meanwhile, Goldman Sachs and GitHub are employing a similar AI to assist developers with code writing. Likewise, the company Unilever is using LLMs to help it respond to messages from customers, generate product listings, and even minimize food waste. Yet, off the shelf, LLMs don’t offer the plug-and-play solution companies might be hoping for. When confronted with an organization’s unique context, they often underperform.