Source: Quantable Analytics
After years of "GitHub Copilot will replace developers" rhetoric, adoption data shows code generation tools plateau at specific, narrow tasks—boilerplate scaffolding and test writing—rather than delivering the full-stack automation vendors promised. The constraint isn't model capability but organizational integration: enterprises still need humans to architect systems, debug failures, and maintain code that AI wrote but nobody fully understands. As technical debt accumulates, the economic case for these tools weakens.