What: AI and hiring analytics tools can now identify hidden barriers for underrepresented candidates, with research showing that data-driven hiring approaches increase diversity by 30% within a year when companies actively track and analyse candidate disengagement patterns.

Why it is important: The Mobley v. Workday lawsuit highlights how AI hiring tools can perpetuate discrimination, making it crucial for organisations to implement data-driven oversight of their recruitment processes to ensure both efficiency and fairness.

Organisations must move beyond gut feelings to data-driven hiring practices, particularly when addressing diversity and inclusion. The key lies in understanding where historically underrepresented candidates drop out of the hiring process through detailed funnel analysis spanning multiple years. AI tools can now analyse these patterns in seconds, identifying bias hotspots automatically. However, the technology must be implemented thoughtfully, with structured interviews and predefined scoring criteria to reduce bias. Tools like BarRaiser and HireVue can monitor interview consistency, flagging issues such as disproportionate interruptions or dismissal of non-traditional communication styles. The approach must extend beyond recruitment to offer transparency, particularly around salary discussions, as many qualified candidates withdraw at the offer stage. Success requires a comprehensive strategy that combines AI efficiency with human oversight to ensure both diversity and fairness in hiring.

IADS Notes:Recent market evidence underscores the complexity of AI in hiring. In March 2025, research showed AI-enabled teams reduced work time by 16% while maintaining performance quality, yet only 10% of retailers successfully scaled their AI applications. The Mobley v. Workday case, certified as a nationwide collective action in June 2025, highlights the risks of unchecked AI hiring systems, particularly in discriminating against protected groups. However, success stories demonstrate the potential: companies implementing systematic inclusion strategies achieve 21% higher returns, while those combining organisational learning with AI implementation are 1.6 to 2.2 times more effective at managing uncertainties, suggesting that balanced human-AI approaches yield the best results

How AI can help find and fix hidden barriers for underrepresented candidates