Motivation

Digital transformation plays a major role in reshaping societal and economic activity. Despite its widespread presence today, and its expected influence as a transformative force, digitalisation is not explicitly reflected in the SSP narratives. Given its rapid evolution and wide-ranging socioeconomic implications, developing explicit projections for digitalisation is challenging. However, its absence means that climate scenarios may overlook an important driver of future climate and development pathways. Incorporating digital transformation into these scenarios can also support more policy-relevant analysis by enabling quantitative assessments of digitalisation’s impacts on energy use, emissions, climate policy, and sustainable development.

Identified trends

The analysis identifies divergent trajectories, with some regions advancing rapidly while others remain significantly behind. Historically, GDP per capita, R&D expenditure, and population size correlate with digital transformation. Projections to 2050 under the Shared Socioeconomic Pathways (SSPs) show marked variation: for example, under the fragmented future (SSP3) many countries lag substantially, whereas under SSP5 digitalisation reaches much higher levels. The study also highlights a persistent digital divide, with up to ~45% of the assessed population under the regional rivalry pathway (SSP3) remaining in countries with low digital transformation by mid-century. Digital transformation is both an enabler and a challenge for climate and sustainable development goals. The trajectories identified in this work can support further analysis in this area, with specific use cases detailed in the full article.

Limitations/Future research

There are two main limitations. First, projections rely on extrapolating historical relationships into the future, so that disruptive technologies and other unforeseen shifts will not be adequately captured. Second, digital transformation is treated as an outcome of socioeconomic drivers (e.g., GDP, population, R&D), whereas in reality it also drives change by shaping economic growth, governance, and inequality. This bidirectional relationship is not reflected in the current modelling framework. We recommend future work that examines these feedbacks, develops deeper sector-specific modelling (e.g., for energy use, materials, and emissions), and improves data and tools to better account for rapid technological change and regional differences in digital transformation.

Data

Although 62 country-level projections up to 2100 are provided (with 112 countries available in the supplementary material in the full article), the use of the 12 region (R12) spatial resolution up to 2050 is recommended. The broader regional aggregation helps reduce uncertainty. Caution is needed when interpreting the numerical values. The relative differences and relationships are more reliable than the absolute levels of digital transformation. Further details are available in the full article.

References