Forbes April 3, 2025
Many organizations implementing AI agents tend to focus too narrowly on a single decision-making model, falling into the trap of assuming a one-size-fits-all decision-making framework—one that follows a typical sequence in any circumstances: from input to research and analysis toward decision, then execution, eventual evaluation, and hopefully, lessons learned.
However, it oversimplifies reality.
Human decision-making is far from uniform, far more complex, dynamic, and context-dependent. It is fluid and shaped by constraints, biases, urgency, situation, interactions, rationality, and most importantly, irrationality, as suggested by a recent MIT study.
If AI agents are to integrate into organizations, a diverse range of decision-making processes needs...
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