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The Impact of Artificial Intelligence on Enterprise Decision-Making Processes

Author

Listed:
  • Górka, Ernest
  • Baran, Dariusz
  • Wojak, Gabriela
  • Ćwiąkała, Michał
  • Zupok, Sebastian
  • Starkowski, Dariusz
  • Reśko, Dariusz
  • Okrasa, Oliwia

Abstract

Purpose: This paper examines how artificial intelligence (AI) enhances enterprise decision-making. It explores the influence of AI tools on decision speed, accuracy, and managerial effectiveness. The study also identifies key human and organizational factors affecting implementation success. Design/methodology/approach: A quantitative survey of 92 enterprises from multiple industries was conducted. Data were collected via a structured questionnaire and analyzed using descriptive and correlation methods. The approach enables identification of relationships between AI adoption, decision efficiency, and organizational barriers. Findings: Results show that 93% of companies use AI, mainly in customer service, data analysis, and decision support. AI improves efficiency and data-driven management but faces barriers such as employee resistance and high costs. Understanding AI mechanisms and managing change are critical competencies. Practical recommendations: Companies should strengthen change management, enhance AI literacy, and address employee adaptation issues. Effective leadership and transparent communication can improve acceptance and outcomes. Aligning AI tools with human decision-making will maximize business value. Originality/value: The paper offers one of the first quantitative assessments of AI’s role in enterprise decision-making. It highlights the synergy between algorithmic and human intelligence. The study contributes to understanding how AI reshapes management practices and organizational agility.

Suggested Citation

  • Górka, Ernest & Baran, Dariusz & Wojak, Gabriela & Ćwiąkała, Michał & Zupok, Sebastian & Starkowski, Dariusz & Reśko, Dariusz & Okrasa, Oliwia, 2025. "The Impact of Artificial Intelligence on Enterprise Decision-Making Processes," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(4), pages 756-777.
    • Handle: RePEc:zbw:espost:338635
    DOI: 10.35808/ersj/4143
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    References listed on IDEAS

    as
    1. Sebastian Zupok & Michal Kapala, 2025. "Next Generation Marketing Channels: Typology, Strategic Implications, and the 6V Framework," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 576-590.
    2. Sebastian Zupok, 2024. "Contemporary Tools for Creating Customer Value," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 545-559.
    3. Ernest G'orka & Dariusz Baran & Gabriela Wojak & Micha{l} 'Cwik{a}ka{l}a & Sebastian Zupok & Dariusz Starkowski & Dariusz Re'sko & Oliwia Okrasa, 2025. "The Impact of Artificial Intelligence on Enterprise Decision-Making Process," Papers 2512.02048, arXiv.org.
    4. Dariusz Baran & Ernest Gorka & Gabriela Wojak & Michal Ćwiakala & Sebastian Zupok & Marek Lazewski, 2025. "From Visibility to Value: Social Media Strategies in the Global Market Research Sector," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 1104-1125.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

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    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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