AI-powered interviews are becoming increasingly common across various industries, helping organizations streamline candidate assessments and improve hiring efficiency.

However, building an effective interview system involves more than just generating questions and evaluating responses. Challenges such as fairness, consistency, candidate experience, speech recognition accuracy, and evaluation reliability can significantly impact the overall effectiveness of the platform.

For teams that have worked on or used AI-driven interview solutions, what have been the most difficult challenges to solve? What approaches or best practices have proven successful in improving interview quality and candidate outcomes?

I'd be interested in hearing about both technical and operational perspectives.