"The Algorithm Made the Call": Why Your Revenue-Generating App Built with AI Code Could Suddenly Be Suspended

Just like YouTube's automated review structure, app stores and cloud platforms are also likely to use AI to automatically assess the risk level of software. In this process, if AI-generated code violates security policies or defects are discovered, developers could face monetization suspension or service restrictions without specific grounds.

The Liability Structure of AI Coding Tools Tools like GitHub Copilot mostly provide services "as-is" and limit liability for their output. In other words, even if AI generated the code, ultimate responsibility for accepting and deploying it belongs to the developer or operator.

The Hidden Costs and Risks of 'Vibe Coding' The issue isn't simply generating code quickly—the core problem lies in the costs and risks that arise during the review process.

• METR: When using AI tools, experienced developers' task completion can actually be delayed by 19%.
• Veracode: Known security vulnerabilities were found in 45% of AI-generated code.
• CodeRabbit: AI-co-authored code has 1.7x more major defects and 2.74x more security vulnerabilities.
• Vangala et al.: AI agents may require 13.5x more dependencies than expected in actual runtime.

Response Strategy: Verifiable Accountability Records Not using AI is not the answer—what matters is leaving a 'verifiable accountability record' that can prove how AI-generated code was validated.

• Define requirements and specify the scope of AI generation/modification
• Record security reviews and passed tests
• Record reasons for adding new dependencies and deployment approvals