As artificial intelligence becomes deeply embedded in digital training environments, organizations are increasingly faced with a strategic decision: should they rely on prompt engineering to guide large language models, or invest in fine-tuning a model for specialized performance? Both approaches offer powerful ways to customize AI behavior, but they differ significantly in complexity, cost, flexibility,…