While generative AI has significantly enhanced code-writing efficiency, it has also imposed additional burdens on the open-source community. Studies indicate that the utilization of generative AI has led to an average reduction of 52% in the time required for code writing. Nevertheless, among the pull requests (PRs) received by maintainers of open-source projects, roughly 25% are comprised of low-quality content generated by AI. This proportion climbs as high as 31% in large-scale projects, substantially escalating the pressure on maintainers. AI has indeed lowered the barrier to entry for participation in open-source projects; however, community trust has not witnessed a concurrent improvement. A majority of maintainers are skeptical that AI has bolstered community trust, and the demand for guidance for new contributors has also surged. Presently, only 35% of projects have instituted policies governing AI contributions, while 32% of projects lack both policies and plans to implement them. The criteria for disclosing AI usage vary, thereby increasing the costs associated with review. The enhanced efficiency in code production brought about by AI is shifting the bottleneck in software engineering towards review, verification, and maintenance processes. Consequently, the open-source community must establish suitable verification and governance mechanisms to equitably distribute the subsequent costs associated with AI-generated code.