AI agents can significantly enhance research data gathering and information dissemination in the context of educational performance and federal oversight. By streamlining data collection from various sources, such as academic institutions and governmental databases, AI can automate the extraction of relevant information, reducing the manual effort typically involved. Utilizing web scraping techniques, AI can compile data into a centralized database, allowing researchers to access a wealth of information efficiently. Additionally, natural language processing (NLP) algorithms can analyze qualitative data from surveys and interviews, categorizing sentiments and themes to provide insights into stakeholders' opinions and experiences regarding educational policies. This qualitative analysis complements quantitative data, offering a more holistic view of educational performance.