Generative artificial intelligence (AI) has created new possibilities for producing scientific figures, graphical abstracts, and conceptual diagrams at substantially lower time and skill cost. At the same time, publishers and journals have introduced heterogeneous policies governing the disclosure and acceptability of AI-generated imagery, leaving researchers with limited operational guidance. In this paper, we conduct a structured review of editorial policies from 12 major publishers and journals current to January 2026, analyze the principal concerns motivating these policies, and compare representative figure-generation tools for academic use. As an illustrative case, we examine SciDraw, a domain-specific platform for scientific illustration available at https://sci-draw.com. Our analysis indicates that publisher guidance converges on three requirements: transparent disclosure, retained human accountability, and heightened scrutiny for figures that could be mistaken for primary data. On this basis, we propose a practical framework for compliant use centered on provenance recording, figure-level disclosure, and post-generation expert review. We argue that AI-assisted figure generation is most defensible when limited to schematic and communicative visuals, accompanied by reproducibility metadata, and explicitly separated from evidentiary data figures.