Companies are rapidly building internal GPTs and uploading leadership guides, onboarding decks, policies, and training materials to create a centralized source of answers. Initial outputs appear polished, fast, and aligned with leadership tone, giving the impression of captured company DNA. Centralization flattens nuance by prioritizing what was convenient to store over how decisions are actually made and how culture is lived. Reused frameworks, outdated templates, and polished statements can become unquestioned guidance while messy, real processes disappear. Broad adoption and scale increase the risk of entrenching ineffective norms and outdated practices.
Companies are racing to build internal GPTs instead of relying solely on general-purpose models like public ChatGPT. They upload leadership guides, onboarding decks, policy manuals, and training slides, expecting the tool to become a one-stop shop for answers. It's starting to look like throwing everything into a blender. The mix comes out smooth, consistent, and ready to serve. But smooth doesn't always mean good - sometimes it just means everything distinct got flattened. What looks aligned might actually taste worse.
But uploading everything into AI doesn't mean the tool reflects how the company actually works or decides. It reflects what was convenient to store. Old frameworks, outdated templates, and polished statements become the source of truth - while the lived parts of culture and the messy work of strategy disappear. When content is reused often enough, it stops being questioned.
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