ETL services simplify the process of preparing data for fine-tuning AI models. By automating data cleaning, normalization, and augmentation, organizations can reduce the time and resources required for model adaptation. For example, in retail, ETL pipelines can curate customer behavior datasets to fine-tune recommendation engines, while in government, they can prepare structured data for policy analysis models. This streamlining ensures consistent and reliable inputs for fine-tuning applications.