AIJul 31, 2025

How Far Are AI Scientists from Changing the World?

arXiv:2507.23276v213 citationsh-index: 8
Originality Synthesis-oriented
AI Analysis

It addresses the potential for AI to reshape scientific research by assessing progress toward human-level AI Scientists, but it is incremental as a review paper.

This survey analyzes the current achievements of AI Scientist systems, particularly LLM-based ones, and identifies key bottlenecks and components needed for them to produce groundbreaking discoveries that solve grand challenges, with evidence including AI-generated papers accepted at ICLR 2025.

The emergence of large language models (LLMs) is propelling automated scientific discovery to the next level, with LLM-based Artificial Intelligence (AI) Scientist systems now taking the lead in scientific research. Several influential works have already appeared in the field of AI Scientist systems, with AI-generated research papers having been accepted at the ICLR 2025 workshop, suggesting that a human-level AI Scientist capable of uncovering phenomena previously unknown to humans, may soon become a reality. In this survey, we focus on the central question: How far are AI scientists from changing the world and reshaping the scientific research paradigm? To answer this question, we provide a prospect-driven review that comprehensively analyzes the current achievements of AI Scientist systems, identifying key bottlenecks and the critical components required for the emergence of a scientific agent capable of producing ground-breaking discoveries that solve grand challenges. We hope this survey will contribute to a clearer understanding of limitations of current AI Scientist systems, showing where we are, what is missing, and what the ultimate goals for scientific AI should be.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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