This study explores the transformative potential of artificial intelligence (AI) as a force multiplier in modern organizations. Using the Delphi research method, a panel of experts across multiple industries assessed how AI can augment human capabilities, drive innovation, and unlock measurable business outcomes. The findings highlight a gap between AI’s promise and the actual benefits realized, often due to organizational constraints such as rigid budgeting, poor data quality, and low workforce readiness. To fully leverage AI, organizations must shift their focus to human-centric business capabilities, including dynamic funding, agile workflows, and continuous learning. This paper presents practical guidance for overcoming constraints and enabling a more adaptive, capability-driven approach to AI adoption.

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From Constraints to Capabilities: AI as a Force Multiplier

  • Evan Leybourn,
  • Christopher Morales

摘要

This study explores the transformative potential of artificial intelligence (AI) as a force multiplier in modern organizations. Using the Delphi research method, a panel of experts across multiple industries assessed how AI can augment human capabilities, drive innovation, and unlock measurable business outcomes. The findings highlight a gap between AI’s promise and the actual benefits realized, often due to organizational constraints such as rigid budgeting, poor data quality, and low workforce readiness. To fully leverage AI, organizations must shift their focus to human-centric business capabilities, including dynamic funding, agile workflows, and continuous learning. This paper presents practical guidance for overcoming constraints and enabling a more adaptive, capability-driven approach to AI adoption.