This research examines how accountability mechanisms in code review processes are affected by the introduction of large language models (LLMs).

• Developers balance intrinsic motivations (professionalism, reputation) with extrinsic pressures (team expectations, organizational policies) when reviewing code
• LLMs are fundamentally changing the social dynamics of code review processes
• The introduction of AI tools creates new accountability challenges that engineering teams must proactively address

For engineering teams, understanding these dynamics is crucial as they integrate AI tools into existing code review workflows while maintaining quality standards and clear lines of responsibility.

Accountability in Code Review: The Role of Intrinsic Drivers and the Impact of LLMs