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DeepSeek: implications for data science and management in the AI era

  • Southern University of Science and Technology
  • New Jersey Institute of Technology
  • Xi'an Jiaotong University
  • Santa Clara University

Research output: Contribution to journalComment/debate

3 Scopus citations

Abstract

DeepSeek has emerged as a disruptive force in artificial intelligence. Unlike traditional large language models (LLMs), which demand extensive computational resources, DeepSeek delivers comparable performance to industry-leading models at a fraction of the cost. Its impact spans both data science and business. In data science, DeepSeek enhances data processing, feature engineering, and statistical modeling, enabling enterprises to deploy AI-driven analytics more cost-effectively. In business, DeepSeek supports various industry sectors, making advanced AI more accessible to small and medium-sized enterprises (SMEs). Additionally, its source-available licensing model promotes transparency and adaptability, challenging the dominance of proprietary AI ecosystems. This paper explores the implications of DeepSeek, reviews its technological advancements and challenges, and outlines future research directions.

Original languageEnglish
Pages (from-to)536-541
Number of pages6
JournalData Science and Management
Volume8
Issue number4
DOIs
StatePublished - Dec 2025

Keywords

  • AI for business
  • AI-driven analytics
  • Cost-efficient AI
  • DeepSeek
  • Large language models (LLMs)

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