How NSF Uses AI-Driven Surveys for R&D Investment Decisions

The National Science Foundation (NSF) manages over $8 billion in annual research funding across thousands of institutions. Making strategic investment decisions requires understanding research priorities and capabilities across the entire research ecosystem. However, traditional survey methods were slow, limited in scope, and difficult to analyze at scale.

The Challenge

NSF needed to understand emerging research priorities across universities, national laboratories, and industry partners. Their previous approach involved manual surveys, lengthy analysis periods, and limited ability to segment responses by institution type, geography, or research discipline.

The Solution

NSF implemented iS&T Dashboard to conduct AI-powered surveys across their research community. The platform enabled them to:

• Generate contextually appropriate survey questions using AI, tailored to different research communities
• Collect responses from 500+ research institutions in real-time
• Perform cohort analysis to identify priorities by institution type, geography, and research discipline
• Generate automated reports for stakeholder distribution
• Track trends over time with longitudinal analysis

Results

The implementation delivered significant improvements:

Key Insights

The data revealed important patterns in research priorities across different institution types. Universities prioritized interdisciplinary collaboration, while national laboratories emphasized infrastructure investment. This segmentation enabled NSF to tailor funding mechanisms to better serve each community.

Looking Forward

NSF plans to conduct quarterly surveys using iS&T Dashboard to maintain current understanding of research priorities. The platform's ability to quickly generate insights enables more responsive policy-making and better alignment with the research community's evolving needs.