While the Sustainable Development Goals (SDGs) have emerged as the preeminent sustainability framework across various spatial scopes, the reporting and assessment of new urban developments and regeneration projects often remain tethered to sustainability frameworks that lack direct alignment with SDG targets. This paper proposes a framework to integrate SDG reporting within urban regeneration initiatives. This approach leverages existing resources, such as the Joint Research Center’s (JRC) European Handbook for SDG Voluntary Local Report (VLR) and UN-Habitat’s Global Urban Monitoring Framework (UMF), to report potential contributions towards SDG progress. The framework is validated through the case study of Madrid Nuevo Norte (MNN), one of the largest urban regeneration projects currently developed in Europe, located in the northern district of the Spanish capital and encompasses the regeneration of a 3.2 million square meter area. The methodology evaluates MNN potential contributions through a set of indicators based on input–output/outcome–impact framework to track the causal pathways arising from MNN activities. This paper presents an analysis of the methodological framework developed for the MNN SDG report during the project-planning phase, with a focus on evaluating the framework’s capacity to accurately estimate the project’s contributions to the SDGs.

Digital transformation is portrayed both as a lever of territorial convergence and as a driver of polarisation between urban cores and peripheries, yet its effect on regional economic resilience has rarely been measured systematically. This study transposes the Economic Resilience Index framework from the national to the regional scale, building a Regional Resilience Index (R-ERI) for 236 NUTS2 regions of the EU-27 from Eurostat indicators, anchored in the capacities of absorption, recovery, and adaptation and measuring resilience as a capacity rather than as a realised shock trajectory. Two complementary models are estimated: a spatial Durbin panel with two-way fixed effects (2018–2023), spanning the COVID-19 pandemic and 2022 energy shocks, and an exploratory cross-sectional difference model exploiting regional artificial intelligence (AI) adoption data disaggregated by NACE branch (2023–2025). The results show that resilience is strongly spatially autocorrelated (Moran’s I between 0.66 and 0.74; p = 0.001); that digital connectivity generates a positive indirect effect on neighbouring regions despite a negative own-region effect; and that the synergy hypothesis—that digitalisation yields more resilience when combined with traditional sectors—does not hold robustly, the interaction being null in the panel and only marginally positive in the AI layer (p = 0.10). We conclude that digital connectivity is not, on its own, an automatic convergence mechanism, and that cohesion policy should account for each region’s sectoral structure and peripheral position.