AI is transforming software development, enabling more contributors through code generation. However, this advancement outpaces improvements in code maintenance, posing a challenge. The Kubernetes community is proactively adapting to AI-assisted coding by establishing a comprehensive AI policy. This policy aims to balance innovation with accountability, ensuring code quality and human oversight. A core principle is transparency, requiring contributors to disclose AI usage in their pull requests.Crucially, human accountability remains paramount; AI cannot be listed as a co-author or co-signer. Contributors must also personally explain any AI-generated code, preventing knowledge gaps. The project enforces Contributor License Agreements for all co-authors, including AI-assisted ones, flagging incomplete PRs. Automated AI reviews are being explored to enhance code quality and provide initial feedback.Tools like GitHub Copilot and CodeRabbit are being evaluated and tested within specific Kubernetes projects. These tools can act as quality gates, offering quick spot checks before human review. The community is actively seeking help to tune review tools, evaluate emerging AI technologies, and explore AI's potential in reducing maintainer burnout and assisting with test triage.