This study aims to examine the impacts of AI investment on economic growth, while controlling for labor force participation and gross fixed capital formation in Germany. The analysis is based on data collected on the state of economic development in Germany from the first quarter of 2012 to the fourth quarter of 2022. The study used a nonlinear ARDL bounds approach for these investigations. The outcomes clearly reveal that positive shocks to labor force participation and investment in AI significantly enhance economic growth (GDP) in Germany, whereas a positive shock to gross fixed capital formation (GFCF) has no considerable effect on economic growth. Likewise, negative shocks to gross fixed capital formation and AI investment increase GDP growth. Negative shock to the labor force reduces GDP growth. Recommendations are made that Germany must maintain its measured approach while offering long-term commitment. More spectacular AI expenditure increases are not required; prioritize steadiness and integration. Establish long-time-horizon AI development partnerships between government, universities, and industry with stable funding streams on long-term horizons. The fragile link between traditional capital formation and growth means that Germany needs to redefine productive investment.

Climate policy in Italy has come to treat energy and resource productivity as central levers, reflecting a broader recognition that how efficiently an economy uses energy and materials shapes its environmental outcomes. This study aims to investigate the dynamic nexus between energy productivity, resource productivity, and carbon dioxide (CO₂) emissions in Italy. To do this, this study uses quarterly time series data from 2000 to 2022 and employs wavelet quantile methods, specifically wavelet quantile regression and wavelet quantile correlation. The wavelet quantile correlation reveals that a euro per kilogram unit change in resource productivity negatively correlates with CO₂ emissions by approximately −0.9 metric tonnes, and a euro per kilogram of oil equivalent unit change in energy productivity negatively correlates with CO₂ emissions by approximately −0.9 metric tonnes across all periods and quantiles, particularly in the long term. Moreover, the findings of wavelet quantile regression reveal that, in the long run, a euro per kilogram unit change in resource productivity and a euro per kilogram of oil equivalent unit change in energy productivity reduce CO₂ emissions across all periods and quantiles by approximately −0.40 and −1.0 metric tonne, respectively. The study recommends that stakeholders in Italy should invest in both short- and long-term energy productivity programs, such as investing in smart appliances that adjust energy consumption and a Combined Heat and Power (CHP) System, as all will be effective. Beyond its methodological novelty, Italy’s dualistic industrial base and EU-driven decarbonisation commitments make it a substantively useful case for a distributional, multi-horizon analysis of this kind.