Neutral Algorithmic Governance is defined as an AI-assisted institutional decision-making model designed to maximize operational efficiency, service continuity, and systemic resilience in critical infrastructure.

Its guiding principle is neither normative nor ideological, but strictly engineering-based: to reduce error, decision latency, and human variability in contexts of high systemic complexity.

In this framework, neutrality does not mean absence of criteria, but rather the technical explicitization of those criteria. The system's objectives — energy continuity, reduction of Mean Time to Recovery (MTTR), minimization of systemic failure rates, and optimization of supply flows — are defined beforehand by the competent authority and translated into verifiable algorithmic parameters. The AI does not replace political or administrative responsibility; it optimizes execution within a clearly delimited decision space.

This approach shifts the center of gravity of governance from reactive discretion toward reproducible, auditable, and performance-oriented decision architectures, capable of operating consistently above electoral cycles, short-term pressures, or institutional fragmentation.