This paper presents the managerial and institutional capstone of the Cognitive Amplification Inequality Theory (CAIT) research program. Building on the structural production framework (Part 1), socio-cognitive dynamics (Part 2), SIAM-style stability and bifurcation analysis (Part 3), and network spectral propagation (Part 4), this work develops the organizational architectures, governance structures, and managerial control mechanisms required to operationalize cognitive amplification within modernenterprises. The central proposition is that organizations are evolving into amplification-allocation systems in which competitive advantage, decision quality, institutional resilience, and workforce stratification increasingly depend on how LLM-mediated cognitive ampli-fication is allocated, governed, and stabilized across Human–AI networks. Part 5 translates the structural, dynamical, and network-theoretic results of the full CAIT series into a formal managerial law set (L1–L6), a governance control architecture, andan implementation roadmap for cognitively amplified enterprises. A key institutional finding is that rule-based governance regimes constrain interpretive drift and corruption-compatible behavior more effectively than discretionary guidelineframeworks, and that this distinction maps directly onto spectral stability conditions within the CAIT dynamical system. The resulting framework provides a coherent, regulator-grade managerial doctrine for designing, governing, and sustaining amplified work systems while mitigating amplification asymmetry, organizational instability, and cognitive inequality. Keywords: cognitive amplification; AI governance; Human–AI integration; organizationaldesign; managerial control; amplification inequality; spectral stability
Usman Zafar (Sun,) studied this question.