Generative Artificial Intelligence is a class of AI systems that learn patterns from data and use them to create new content across text, images, audio, and video. At the core of most generative AI applications is a large language model (LLM)—a massive neural network, often with billions or trillions of parameters, trained on extensive datasets combined with human feedback. To solve real business problems, these models typically need to be adapted to a specific domain.

This customization can be done in two primary ways. Building generative AI into business workflows requires gathering relevant data, structuring it properly, and configuring the LLM—either through RAG pipelines or fine-tuning—to ensure it generates accurate, context-aware outputs.