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Adoption of Cloud Services and Artificial Intelligence Applications in European Energy: Implications and Opportunities for Sustainable Digital Tourism

Author

Listed:
  • Robert Sylvester Radomir

    (Lucian Blaga University of Sibiu, Faculty of Economic Sciences)

  • Răzvan Șerbu

    (Lucian Blaga University of Sibiu, Faculty of Economic Sciences)

Abstract

The rapid growth of cloud services is sometimes presented as a catalyst for the green transition, based on the argument that artificial intelligence algorithms, run at scale, would optimize economic processes and reduce total energy demand. This study empirically tests this hypothesis for Europe, linking the evolution of enterprise-level cloud adoption to Final Energy Consumption (FEC). Two harmonized Eurostat series are used: isoc_cicce_use (percentage of firms purchasing cloud services) and ten00123 (FEC, thousand tonnes of oil equivalent). The panel includes 27 countries and six common years (2014, 2016, 2018, 2020, 2021, 2023), totaling 162 observations. The econometric model is one with country and year fixed effects and country-clustered robust errors, in order to control for both structural national characteristics and annual macro shocks. The central result shows that the elasticity coefficient between the share of cloud-using firms and log-FEC is +0.011, statistically insignificant (p = 0.93). The simple bivariate correlation is almost zero (r = 0.019). Sensitivity tests, performed by excluding the pandemic year and introducing a 1-year lag, do not change the sign or the (non)significance of the coefficient. The empirical conclusion is that, in the 2014–2023 period, cloud adoption is not associated with measurable energy savings at a national scale. The interpretation of the results suggests three explanations: (i) the time horizon is too short for digital investments to generate net gains, (ii) the consumption of the data centers themselves may offset user savings, and (iii) the sectoral aggregation of FEC may mask divergent effects between industry and households. The policy implication is clear: digitalization must be accompanied by the decarbonization of the electricity mix and by dedicated sectoral measures to become a genuine ally of European energy objectives.

Suggested Citation

  • Robert Sylvester Radomir & Răzvan Șerbu, 2026. "Adoption of Cloud Services and Artificial Intelligence Applications in European Energy: Implications and Opportunities for Sustainable Digital Tourism," Springer Proceedings in Business and Economics,, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-17545-8_20
    DOI: 10.1007/978-3-032-17545-8_20
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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

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