AI Governance: 2030 as the Year of Convergence from Symptoms to Infrastructure?

This paper advances the emerging field of infrastructural theory by reframing AI governance as a problem of system‑level calibration rather than public‑facing symptoms. Instead of treating misinformation, polarization, and digital addiction as isolated cultural failures, the essay demonstrates how these phenomena are produced by deeper infrastructures that remain largely invisible in public discourse. By mapping how healthcare, finance, law, and electoral systems are transitioning into AI‑mediated decision infrastructures, the paper provides a unified framework for understanding 2030 as a convergence horizon—where multiple systemic stresses become simultaneously visible through infrastructural failure.