A proposed AI of the AI ecosystem for the orchestration, evaluation, and governance of autonomous AI systems - Brisebois, Ronald; Nadembega, Apollinaire; Abran, Alain (Edelweiss Applied Science and Technology, 2026)
Coordinating autonomous and heterogeneous artificial intelligence (AI) systems is difficult because their capabilities, domain specializations, interfaces, and output structures vary widely and rapidly evolve. The purpose of this study is to address these issues through the design of an AI of the AI (AoA) ecosystem as a hierarchical system-of-systems framework that orchestrates and challenges multiple independent AI agents while preserving their operational autonomy. In this approach, the AoA integrates three interconnected layers: (i) a configuration and longitudinal performance-tracking layer that maintains operational parameters, version histories, and domain-specific performance profiles; (ii) a moderated collaboration and evaluation layer that enables indirect coordination through standardized response schemas, structured competition, and cross-agent benchmarking; and (iii) a context-dependent authority and data-source evaluation layer that weights AI outputs based on source credibility, reference quality, and domain relevance, supported by federated ontologies for semantic alignment and conflict reconciliation. In conclusion, this ecosystem also includes multi-stage alert mechanisms that detect drift, inconsistencies, conflicts, and emergent patterns, enabling continuous self-assessment, adaptive governance, and iterative ranking updates. In terms of practical implications, this AoA is designed to interoperate with existing information technology (IT) infrastructure and is additionally forward-compatible with emerging quantum computing platforms, providing a scalable foundation for orchestrating and governing heterogeneous AI ecosystems.