The Invisible Singularity: Artificial Intelligence as Convergent Infrastructure and the Reorganization of Global Work, 2027–2035

The contemporary artificial intelligence landscape is characterized by an extraordinary cadence of model releases — successive frontier systems appearing at intervals of weeks rather than years. This paper argues that this proliferation is not the terminal state of the technology but a transitional phase, and that the observable trajectory points toward a structural convergence: a small number of highly capable, general-purpose AI systems that recede into the infrastructural background of economic life, invoked as unremarkably as search engines or enterprise resource platforms are invoked today. Drawing on the economics of general purpose technologies (Bresnahan & Trajtenberg, 1995), the theory of ubiquitous computing (Weiser, 1991), and the historical dynamics of technological revolutions (Perez, 2002; David, 1990), I develop a three-phase model — Proliferation, Acceleration, and Invisibility — and advance two central hypotheses. First, the Acceleration Hypothesis: beginning approximately in 2027, the rate of capability diffusion will compress such that materially novel tools and applications emerge on a near-daily cadence, rendering pre-2024 workflows structurally obsolete across most knowledge-intensive sectors. Second, the Reinstatement Hypothesis: contrary to popular displacement narratives, the task-creation channel identified by Acemoglu and Restrepo (2019) will dominate, producing net employment growth concentrated in newly instantiated occupational categories, consistent with the World Economic Forum's (2025) projection of 170 million jobs created against 92 million displaced by 2030. The paper's contribution is a unified framework that explains why the most transformative outcome of the current AI race is not a visible superintelligence but an invisible one — a utility so deeply embedded that, like electricity, its presence is noticed only in its absence. Limitations, falsifiable predictions, and counterarguments are addressed.