LLMs Outperform Data Scientists (2025) (presentofcoding.substack.com)

In a groundbreaking report released in 2025, large language models (LLMs) have demonstrated the ability to outperform human data scientists in various tasks, revolutionizing the landscape of AI and machine learning. This significant evolution in LLM capabilities suggests that these models can not only process and analyze vast amounts of data but also generate actionable insights with greater speed and accuracy than their human counterparts. This shift could redefine roles in data science, prompting a reevaluation of how businesses approach data-related challenges. The implications of this development extend far beyond mere performance metrics. With LLMs surpassing human proficiency in data analysis, organizations may increasingly rely on AI to drive decision-making processes, potentially improving efficiency and reducing operational costs. Moreover, the integration of LLMs into data science workflows could lead to innovations in automated machine learning (AutoML), allowing companies to deploy high-quality predictive models with minimal human intervention. As a result, we may see a significant upskilling of the human workforce, with a focus on strategic oversight and the cultivation of AI literacy to complement these advanced tools.