Person-AI Bidirectional Fit - A Proof-Of-Concept Case Study Of Augmented Human-Ai Symbiosis In Management Decision-Making Process
This is an incremental proof-of-concept for improving management decision-making through augmented human-AI symbiosis, with potential benefits for executives and organizations.
The study tackled the problem of aligning human decision-makers with AI systems in management by introducing the Person-AI bidirectional fit concept, and found that higher fit, as in the CEO-H3LIX-LAIZA relationship, led to more accurate and trustworthy decisions, including ethical disqualifications and identifying false positives from an LLM.
This article develops the concept of Person-AI bidirectional fit, defined as the continuously evolving, context-sensitive alignment-primarily cognitive, but also emotional and behavioral-between a human decision-maker and an artificial intelligence system. Grounded in contingency theory and quality theory, the study examines the role of P-AI fit in managerial decision-making through a proof-of-concept case study involving a real hiring process for a Senior AI Lead. Three decision pathways are compared: (1) independent evaluations by a CEO, CTO, and CSO; (2) an evaluation produced by an augmented human-AI symbiotic intelligence system (H3LIX-LAIZA); and (3) an assessment generated by a general-purpose large language model. The results reveal substantial role-based divergence in human judgments, high alignment between H3LIX-LAIZA and the CEOs implicit decision model-including ethical disqualification of a high-risk candidate and a critical false-positive recommendation from the LLMr. The findings demonstrate that higher P-AI fit, exemplified by the CEO H3LIX-LAIZA relationship, functions as a mechanism linking augmented symbiotic intelligence to accurate, trustworthy, and context-sensitive decisions. The study provides an initial verification of the P-AI fit construct and a proof-of-concept for H3LIX-LAIZA as an augmented human-AI symbiotic intelligence system.