AUTHOR
M any 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 circumstance: 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 to be considered to ensure effective implementation without inadvertently setting a substandard for decision-making.
NO DECISION PATH IS ONE-SIZEFITS-ALL OR NATURALLY MONOLITHIC
The notion…
