JOURNAL ARTICLE

How AI Can Help Leaders Make Better Decisions Under Pressure.

  • Published In: Harvard Business Review Digital Articles, 2023. P. 1 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Purdy, Mark; Williams, A. Mark 3 of 3

Abstract

This article explores how AI can assist leaders in making better decisions under pressure. It acknowledges the increasing pressure faced by business leaders and managers to make the right decisions and the costs of poor decision-making. The article discusses the use of AI-powered technologies, such as virtual assistants and generative AI models, in improving decision-making capabilities. It addresses the contexts in which AI decision-making technologies are beneficial, the challenges and risks associated with using these technologies, and how business leaders can effectively benefit from them while mitigating risks. The article provides examples of how AI can improve decision-making through real-time tracking and prediction, virtual role-play, and acting as virtual advisors and sounding boards. It also mentions the various applications of generative AI, including business continuity, crisis response management, risk assessment in financial investments, and decision-making support. Companies like Risk Management and GitHub Copilot are developing AI-powered assistants that can sift through data, generate executive summaries, and provide recommendations. Generative AI is also used in reputation management and can create synthetic data for decision-making models. However, the article acknowledges the challenges and risks associated with AI, such as bias and ethics violations, and emphasizes the need for organizations to carefully consider when to trust machines over humans and how to maintain expertise. It mentions prompt engineering as a new discipline that focuses on structuring questions to AI systems effectively. While AI tools can improve decision-making, the article emphasizes that human decision makers must continue to develop their own skills and judgment. [Extracted from the article]

Additional Information

  • Source:Harvard Business Review Digital Articles. 2023/10, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • Accession Number:173300957
  • Copyright Statement:Copyright 2023 Harvard Business Publishing. All Rights Reserved. Additional restrictions may apply including the use of this content as assigned course material. Please consult your institution's librarian about any restrictions that might apply under the license with your institution. For more information and teaching resources from Harvard Business Publishing including Harvard Business School Cases, eLearning products, and business simulations please visit hbsp.harvard.edu. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.