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Managerial decision-making and AI: A decision canvas approach

Author

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  • Bagchi, Soumendra Narain
  • Sharma, Rajeev

Abstract

Given the undeniable fact that the quality of decisions significantly impacts organizational success and the careers of the decision-makers, in this article, we explore various categories of decisions that managers encounter and examine the existing literature for tools and frameworks that can enhance the decision-making process. Our search revealed a significant gap between the complexity of real-world problems and the capabilities of available decision-making tools. Current frameworks that rely on large language models (LLMs) like ChatGPT are still nascent and offer limited guidance. We propose using a decision canvas to harness the extensive capabilities of large language models. The decision canvas is structured using the organizational hierarchy and applicable operating principles. This canvas is designed to help decision-makers better comprehend their available options, tools, and frameworks. This canvas facilitates two broad approaches to decision-making: (1) developing a comprehensive understanding, starting from leaders’ personal philosophies toward the problem; and (2) a limited problem-solving approach to identify the possible solution.

Suggested Citation

  • Bagchi, Soumendra Narain & Sharma, Rajeev, 2026. "Managerial decision-making and AI: A decision canvas approach," Business Horizons, Elsevier, vol. 69(1), pages 55-66.
  • Handle: RePEc:eee:bushor:v:69:y:2026:i:1:p:55-66
    DOI: 10.1016/j.bushor.2024.12.001
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