Overview
AI tools bring efficiency to software engineering, but they also introduce risks that can affect code quality, security, ethics, and long-term maintainability.
Key Risks
- Incorrect or insecure code: AI may suggest patterns with hidden bugs or vulnerabilities
- Loss of architectural coherence: Suggestions might conflict with design standards
- Bias in logic or outputs: Trained on public data, models may reflect harmful assumptions
- Over-reliance on AI: Developers may lose critical thinking or domain knowledge
- Lack of accountability: Hard to trace AI errors back to a responsible actor
How to Mitigate
- Combine AI with strong review processes
- Train teams on prompt engineering and AI limitations
- Enforce secure coding and ethical use policies
- Use AI selectively where it adds real value
Related Context
