The GenAI Spike: Proposal Submission Trends and Competition in Horizon Europe (2021-2026)
Year: 2026
Type: conference-paper
Abstract: The rapid adoption of Large Language Models (LLMs) in professional knowledge work since late 2022 raises questions about how AI-assisted writing affects competitive research funding. This paper presents the first programme-level, topic-granularity analysis of proposal submission dynamics in Horizon Europe (HE) using the public CORDIS dataset, covering 2,136 Research and Innovation Action (RIA), Innovation Action (IA), and Coordination and Support Action (CSA) topics from 2021 to 2026. We document a structural shift coinciding with the GenAI adoption wave: mean proposals per topic grew 136%, the 90 th percentile nearly tripled (+189%), and oversubscription more than doubled from 4.3× in 2021 to 10.3× in 2025, while topic-level success rates declined from 40% to 22%. This trend is consistent across action types and is corroborated by recent micro-level evidence showing approximately 40% of firm-submitted HE proposals contain detectable LLM-assisted content by end of 2024. We term this the "GenAI Spike," and establish an empirical baseline for longitudinal follow-up work on LLM impacts in Horizon Europe.
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7204440824