Reducing Barriers to Test Automation Through AI-Assisted Development
Date:
Abstract
As software complexity increases, manual testing becomes impractical — particularly in regulated medical device environments where verification must satisfy rigorous compliance requirements. This presentation examines how AI-assisted development tools can accelerate test automation by supporting code generation, debugging, documentation, and project organization. Routine verification tasks suitable for automation — including launching applications, configuring system settings, and executing scripted workflows — were evaluated and implemented with AI assistance. Results indicate that AI tools reduced prototyping and documentation effort, enabled broader exploration of automation concepts, and improved team understanding of available tooling. However, all AI-generated outputs required technical review to verify correctness, robustness, and suitability for the target environment. The central finding is that AI tools do not replace engineering judgment: in regulated settings, developers must retain control over architecture, validation strategy, and code review processes. Disciplined human oversight remains a prerequisite for deploying AI-assisted automation in safety-critical software development.