Framework reveals systemic ecosystem orchestration as key to AI success, not just tech race
Original framing: “New research offers managers a framework for understanding who wins in AI ecosystems and why” — Phys.org
Empirical network‑analysis of AI value chains confirms that firms with dense, multi‑type connections (data, talent, policy) outperform isolated innovators. Simulation studies of ecosystem dynamics show that resilience emerges from modular interdependence rather than centralization. The framework aligns with systems‑theory and complexity science, providing a robust methodological basis for policy design.
The AI ecosystem is less a battlefield of isolated firms than a complex relational network where power, data, and institutional design determine who captures value.
Historical precedents from railroads to telecoms show that inclusive governance and standards can prevent monopolistic lock‑ins, while cross‑cultural case studies demonstrate alternative, community‑centric models that already thrive. Embedding indigenous data sovereignty, multi‑stakeholder boards, and public research infrastructure reshapes the orchestration logic toward equity and resilience. Future scenario modelling confirms that such systemic interventions yield higher social welfare and lower systemic risk, offering a pragmatic roadmap for policymakers, corporations, and civil society to co‑create a just AI future.