<p>Energy poverty is not only a pressing global challenge today but is also expected to remain a persistent issue for human development in the foreseeable future. In the era of digitalization, it is crucial to evaluate the contribution of data factors in alleviating this problem. By constructing a multidimensional energy poverty index, this paper uses panel data from 30 provinces in China between 2003 and 2023 and employs the difference-in-differences (DID) method to assess the impact of the national big data pilot zone policy on energy poverty. The study finds that, compared to provinces without the establishment of a big data pilot zone, for every 1 percentage point increase in the implementation of the pilot zone, energy poverty levels decrease by 6.9 percentage points. That is, the implementation of the big data pilot zone policy has significantly improved the energy poverty situation in the pilot areas. This conclusion remains valid after a series of placebo and robustness tests. Further analysis shows that the BDPZ policy alleviates energy poverty indirectly by promoting industrial agglomeration and enhancing financial service capacity. Moreover, the policy exhibits spatial spillover effects in its impact on energy poverty. This paper highlights the deeper value of data factors, offering theoretical support for the strategic planning of data policies aimed at reducing energy poverty, and provides useful insights for other countries tackling similar issues.</p>