The transition from traditional search engines to Generative Information Engines (GIEs) has fundamentally altered how information is retrieved, synthesized, and acted upon. While prior work has introduced frameworks such as the AI Visibility Index (AIVI) and AI Reputation Score (AIRS) to measure inclusion and perception within generative systems, there remains a gap in understanding how these outcomes can be systematically influenced. In this paper, we introduce Distributed Authority Domain Placement (DADP), a proprietary framework for optimizing entity visibility and representation across generative environments. DADP operates on the principle that generative systems prioritize distributed authority signals rather than single-domain optimization. We demonstrate that traditional GEO approaches limited to CMS and site-level optimization are insufficient in this new paradigm. Through comparative analysis and formal modeling, we establish DADP as a superior system-level strategy for influencing AI-mediated decision-making across commerce, capital allocation, and information ecosystems.