As the rollout of 5G accelerates, its soaring energy demand poses a growing climate challenge. According to a World Bank Group report, the Information and Communication Technology (ICT) sector is responsible at least 1.7 % of global greenhouse gas (GHG) emissions. This study examines an intelligent suite of energy-saving methods—particularly deep reinforcement learning sleep modes, adaptive RIS, and cluster-zooming cell-free MIMO at the network edge, alongside dynamic power adjustments on user devices—and quantifies their environmental impact using an ICT-focused environmentally extended input-output (EEIO) model. Anchored in the UK’s 2019 economic and emissions data, the model captures both production and consumption effects across 33 sectors. Results spotlight two standout strategies—AI-powered base station sleep control and refined user device signaling—as catalysts for deep, economy-wide CO₂ reductions. Notably, the financial, IT services, and programming sectors benefit most from these ripple effects. Our findings outline practical paths towards greener 5G deployments and underscore policy opportunities to amplify their socioeconomic value.