Gross Domestic Product (GDP) remains the dominant yardstick for economic performance, yet its aggregated, nation-bound and market-exclusive nature obscures crucial dimensions of prosperity, equity and environmental sustainability. Building on recent advances in data science and the expanding “Beyond-GDP” literature, this article argues for a generational shift in economic measurement designated “GDP 5.0.” This new approach of GDP integrates high-frequency, geolocated micro-data with artificial-intelligence methods to generate real-time dashboards of economic activity, social welfare and planetary boundaries. The framework adopts an inductive, bottom-up approach, combining firm-level transactions, satellite imagery, sensor inputs, and social indicators. These diverse data streams are fused using explainable machine learning techniques to construct composite indices that capture regional heterogeneity and internalize negative externalities. The article examines the methodological foundations, governance challenges, and safeguards against algorithmic bias associated with GDP 5.0. It highlights the policy relevance of the framework through stylized applications in monetary, fiscal, and environmental domains. Aligning measurement practices with the complexities of the twenty-first century, GDP 5.0 proposes a pathway toward more responsive, inclusive, and sustainable economic governance.