Shah, Anand and Levy, Joshua, Access to Justice in the Age of AI: Evidence from U.S. Federal Courts (March 20, 2026). Available at SSRN: https://ssrn.com/abstract=6766859 – This paper studies how generative AI has reshaped entry into the federal civil court system. Drawing on administrative records covering more than 4.5 million non-prisoner federal civil court cases from FY2005-FY2026 and 46 million PACER docket entries matched to those cases, we document three sets of findings. First, the number of pro se cases-or self-represented cases-is increasing dramatically, rising from a long-term steady-state average of 11% to 16.8% in FY2025. This increase is concentrated in case types characterized by formulaic document production and absent from more complex, attorney-intensive categories. Second, we argue these cases are placing a larger burden on federal district courts. Pro se cases are not terminating faster, and this combined with the increased case numbers suggests more cases for judges to process. Moreover, intra-case activity is up, with the total volume of docket entries per court generated by pro se cases in their first 180 days up 158% from pre-AI means to 2025. Third, we directly validate that AI use is increasing in federal courts. Using a random sample of 1,600 complaints drawn from an 8-year period (2019-2026), we find that a large and growing share of complaints are flagging positive for AI-generated text, from essentially zero in the pre-AI period to more than 18% in 2026.