Contents
If your content ecosystem consists of unstructured, long-form content, chances are high that (a) people are spending hours trying to find information and (b) your organization is looking to AI solutions to help people find answers faster.
Most enterprise content is full of inaccuracies, inconsistencies, and redundancies that have interfered with findability for decades. Now, AI solutions are shining a spotlight on those issues by providing wrong or contradictory answers. When the AI can’t find an answer, it hallucinates in an attempt to provide you with something, anything at all. The problem is that even AI, despite its ability to process information at unprecedented speed, cannot make up for issues in the source content.
All those steps you should take to make content findable and usable for humans are the same steps you must take to prepare your content for retrieval-augmented generation (RAG) and generative AI (GenAI) solutions.
Takeaways
- Basic understanding of RAG, GenAI, large language models (LLM), and artificial neural networks (ANN)
- Four phases of implementing an AI solution
- Three things you must do to your content to enable AI to produce quality results
Prior knowledge
Familiarity with structured / component-based content is a plus
No prior AI knowledge is necessary