AI Mediated Intellectual Provenance: How everyday AI use could reshape the evidence used to recognize human contributions

AI assistants can participate in the development of ideas before those ideas appear in conventional publications. This perspective examines whether their increasing use as information sources and thinking partners could also change how intellectual contributions are documented and recognized. I propose a conditional transition: when everyday AI interactions produce consented, independently verifiable records, and systems can connect those records to later work, institutions may begin treating AI-organized provenance as attribution evidence. The transition depends on record quality, access, semantic comparison, and institutional practice; it does not follow from model capability alone. The paper defines AI-mediated intellectual provenance, separates recorded precedence from actual first conception, and describes five roles spanning information assistance, documented interaction, provenance investigation, evidentiary use, and delegated attribution authority. It positions this framework alongside existing work on AI memory, idea documentation, provenance standards, and contributor taxonomies. A worked hypothetical case illustrates how the same record can support a limited claim about documented conceptual contribution without establishing copying, ownership, or sole inventorship. The paper proposes falsifiable predictions and an evaluation program, including comparisons with conventional archives and measurements of false attribution, abstention, and institutional reliance. Its central concern is whether evidence becomes easier to inspect, or whether fluent reconstruction and incomplete coverage produce unearned authority. No prototype, empirical findings, exhaustive novelty review, or legal priority claim is presented. Perspective preprint, Version 1.0. Not peer reviewed. Research, drafting, and editing were assisted by ChatGPT; this assistance is disclosed in the manuscript. Author: Ahmed AttallahCorrespondence: ahmedattallah19010@gmail.comORCID: https://orcid.org/0009-0008-2571-9464LinkedIn: https://www.linkedin.com/in/ahmed-attallah