Survey on Generative AI Adoption at the Italian National Institute for Astrophysics, 2025

Spring 2025 survey of 371 staff members (~20% of the workforce) at the Italian National Institute for Astrophysics (INAF) on generative AI usage. The data were collected and analyzed by Alessandro Cabras, revealing weekly usage patterns, ethical concerns, and user segmentation. Results were published in a PDF document in June 2026.

Use Cases

• Analyzing correlations between AI literacy and user satisfaction based on survey responses.
• Segmenting research staff into user personas (Enthusiasts, Pragmatists, Skeptics) using K-Means clustering results.
• Investigating the prevalence and equity concerns of 'Shadow IT' where researchers use personal funds for premium tools.
• Studying primary use cases for generative AI, such as coding and linguistic refinement, within an astrophysics research context.

Strengths

• Based on 371 survey responses, representing approximately 20% of the target institution's workforce.
• Includes quantitative analysis and qualitative feedback, providing both statistical and attitudinal insights.
• User segmentation identifies three distinct personas (Enthusiasts, Pragmatists, Skeptics) from the data.
• Reports specific findings like 50% weekly adoption rate and 18% engagement in 'Shadow IT'.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small (101.7 KB), indicating limited raw data or a summary report rather than a full dataset.
• Data may reflect temporal and institutional bias specific to INAF in spring 2025.

Provenance

Source

Survey conducted at the Italian National Institute for Astrophysics (INAF).

Collection Method

Comprehensive survey analyzed quantitatively (including K-Means clustering) and qualitatively.

Time Range

Spring 2025.

Freshness

Last updated 2026-06-02 05:26:52; freshness should be verified.

Geography

Italy (specifically the Italian National Institute for Astrophysics).