The indirect impacts of digitalisation on energy use and carbon emissions are large but uncertain. In this study, we provide quantitative estimates of digitalisation impacts focusing on both energy-saving and energy-increasing potentials. We draw on studies of specific digital use cases in transport and consumer goods sectors, and normalise impact estimates as percent changes relative to reference cases without digitalisation. For the industry sector, we draw on statistical models using panel data that estimate how energy demand changes with increased digitalisation. In each case we present the maximum uncertainty ranges of impact estimates, and explore the conditions explaining both lower and upper bounds. We find strong evidence of both large reductions in energy use through substitution or efficiency improvements (e.g., shared ridehailing: -55% to -18%) and large increases in energy use through rebound or induced demand effects (e.g., ridehailing: +41% to +90%). In some cases, we find evidence of both negative and positive impacts depending on deployment conditions or use context (e.g., e-retail: -94% to +140%; mobility-as-a-service: -50% to +20%). Study design also affects the uncertainty of digitalisation impacts. Common features of the lower and upper bounds of estimated impact ranges point to generic strategies for aligning digitalisa- tion with climate mitigation goals. These include limiting poten- tial rebound through pricing or other constraints on increased activity, and incentivising business models that integrate digitally- enabled activities into wider systems of provision for mobility or electricity.