Social License to Operate in High Technology: Applicability of the SLO Model to AI Data Centers in the Developed World, with a Focus on the United States

This paper applies the Social License to Operate (SLO) model to one of the most strategically sensitive investment frontiers of the contemporary economy: large-scale digital infrastructure for artificial intelligence. Built on the author’s conceptual framework and supported by recent U.S. evidence, it argues that AI data-center viability depends not only on capital, land, permits, power, and compute, but also on social legitimacy, distributive balance, public trust, and preventive governance. Artificial intelligence has turned data centers into critical infrastructure intensive in energy, water, land, and regulatory capacity. This article demonstrates the applicability of the Social License to Operate model to next-generation digital infrastructure in developed economies, with a focus on the United States. It presents the origin of the model, its general formula, its four components—Social Value, Social Capital, Social Risk, and Negative Social Impact—and its equilibrium logic. It also shows the model’s usefulness for qualitative and quantitative measurement, social and regulatory risk estimation, and project and investment viability assessment. The demonstration relies on a recent empirical sequence: academic criticism, community resistance, municipal moratoria, statewide moratoria, and the industry’s own defensive response. The article concludes that SLO has become a condition of possibility for AI infrastructure and a strategic variable for sponsors, banks, utilities, technology firms, and the public sector.