The Semiotic Architecture of the AI Investment Loop: A Peircean Semiotic Trajectory Architecture Analysis

Abstract The current AI investment boom exhibits a distinctive financial structure in which large technology firms simultaneously act as investors, cloud providers, and counterparties to substantial future compute commitments. These overlapping roles create the possibility of circular financial relationships in which investment, contractual obligations, reported revenue, valuation changes, and further investment become mutually reinforcing. This paper analyzes that phenomenon through two complementary frameworks: Carlota Perez’s theory of technological revolutions and the Peircean Semiotic Trajectory Architecture (PSTA). The central argument is not that AI infrastructure is unreal, but that financial signals can acquire greater interpretive authority than independent evidence of productive value. A financial signal becomes semiotically problematic when it is repeatedly used as evidence for the economic proposition that generated it. The empirical analysis distinguishes filed corporate disclosures, management commentary, and external analytical estimates. Microsoft’s commercial remaining performance obligations (~$625B in Q2 FY2026; ~$678B at FY2026 year‑end), its ~45% OpenAI attribution (management commentary), and Oracle’s ~$638B RPO illustrate the scale of future commitments. Other figures, including ~$460B in Big Tech AI‑startup investment and ~$879B in multi‑year cloud commitments, are treated as external analytical estimates. The paper develops conceptual, empirical, and institutional tools for diagnosing reflexive financial structures and illustrates how PSTA can clarify evidentiary status, model reflexive loops, bridge technological‑revolution theory with semiotic analysis, derive governance principles, and propose a structured recovery trajectory (D → F → I → O⁺). The analysis concludes that the relevant question is not whether AI investment is “real,” but whether its financial representations remain open to independent correction by Secondness.