Most researchers use ChatGPT as a simple “chatbot” for writing support or summarizing literature. However, for crucial scientific work, this chat-based approach is frequently insufficient. Scientific research workflows are often fragmented, involving manual data handling, documentation, and data analysis across multiple datasets. This DataSnack introduces AI Agents as an advanced approach for applying generative AI to research. Unlike conventional chat-based tools, AI Agents are software systems that can plan, reason, and act to perform multiple tasks on behalf of researchers, enabling them to automate routine and time-consuming processes such as literature reviews, data analysis, and the documentation of lab work. The session will highlight how this shift from interaction to orchestration can reduce manual workload and improve research efficiency through practical use cases. It will also address data governance, focusing on how researchers can maintain control over sensitive data while responsibly integrating AI into their workflows. Participants will leave with a practical understanding of how to begin using AI Agents to support their daily research processes and streamline routine tasks.
Floriann Deepika Louis (Thu,) studied this question.