The objective of this project is to explore how Generative AI can automate research workflows, improve efficiency, and reduce manual effort. It focuses on integrating AI tools for data collection, analysis, summarization, and reporting to enhance decision-making and productivity in research-driven environments.
Study the concept of research workflows, including stages such as data collection, cleaning, analysis, and reporting.
Understand the fundamentals of Generative AI (GenAI) and its applications in research and business analytics.
Identify key challenges in traditional research processes such as time consumption, manual errors, and data overload.
Explore various GenAI tools (e.g., ChatGPT, AI-based summarizers, and data analysis tools) used for automating research tasks.
Map existing research workflows and identify areas where automation can be implemented.
Design an automated workflow integrating GenAI tools for literature review, data extraction, and report generation.
Conduct a comparative analysis between manual and AI-driven research processes in terms of time, accuracy, and cost.
Use tools like Excel, Power BI, or Python to support automated data analysis and visualization.
Develop prompts and workflows for effective use of GenAI in research tasks.
Evaluate the limitations and ethical considerations of using AI in research (bias, data privacy, reliability).
Create a prototype or demonstration of an automated research workflow using available AI tools.
Measure improvements in productivity and efficiency after implementing automation.
Prepare dashboards or reports showcasing findings and performance improvements.
Provide actionable recommendations for organizations to adopt GenAI in research workflows effectivel
