Human AI Collaborative Knowledge Synthesis for Corporate Policy Analysis and Cross-Division Decision Alignment

Abstract

Corporate policy environments are often characterized by fragmented documents, inconsistent terminology, overlapping authority, and division-specific procedural interpretations that weaken organizational alignment. This study proposes an intelligent knowledge synthesis framework to analyze corporate policy corpora and assess cross-division decision alignment through an interpretable semantic pipeline. The framework integrates document acquisition, preprocessing, policy representation, knowledge synthesis, contradiction detection, alignment scoring, and evaluation within a unified architecture. Using a corpus of 540 source documents consisting of corporate policies, standard operating procedures, internal memoranda, strategic directives, and implementation notes, the method transformed the data into 1,980 normalized policy units and generated 246 synthesized policy clusters with a mean semantic coherence of 0.87. Domain-level results showed the highest coherence in compliance (0.90), approval governance (0.89), and reporting (0.88), while resource allocation and risk control produced lower but still stable coherence scores of 0.84 and 0.86. Contradiction analysis identified 173 significant conflict cases and 94 structured exception relationships, with conditional exceptions representing the largest pattern, followed by direct conflict, authority clash, and procedural override. Inter-divisional analysis showed the strongest friction between operations and compliance, IT and legal, and finance and operations, indicating that policy misalignment frequently emerges from localized procedural adaptation rather than explicit policy rejection. Across 320 evaluated decision cases, the alignment model achieved a mean score of 0.84, with 71.6% of cases classified in the high-alignment band, 19.1% in the moderate band, 6.9% in the low band, and 2.5% in the critical band. Category-level evaluation showed the highest alignment for compliance (0.91) and reporting (0.89), while resource-related decisions recorded the lowest score at 0.77. Division-level analysis further revealed that legal and compliance maintained the strongest stability profiles, with mean alignment scores of 0.90 and 0.88 and low variance values of 0.012 and 0.015, whereas IT and operations displayed greater volatility, with mean scores of 0.80 and 0.78 and variance values of 0.031 and 0.036. Comparative evaluation demonstrated that the full framework outperformed the baseline and synthesis-only configurations across synthesis quality, conflict detection, alignment stability, and interpretive usefulness, reaching scores of 0.90, 0.87, 0.89, and 0.92, respectively. These findings show that intelligent knowledge synthesis can function as a robust analytical foundation for enterprise policy interpretation, contradiction diagnosis, and coordination-aware decision support across organizational divisions.