[Case Study] Hakuhodo DY ONE adopts ailead, redesigning new graduate recruitment with a Human-AI hybrid evaluation model

株式会社ailead, the developer and provider of the conversational AI data platform 'ailead,' has announced the release of a service deployment case study at Hakuhodo DY ONE.

Background of ailead Adoption: Addressing Inconsistencies and Workload in High-Volume Recruitment

Following the integration of Digital Advertising Consortium Inc. and Irep Co., Ltd., Hakuhodo DY ONE grew into an organization of 3,000 employees, necessitating a restructuring of its recruitment system. In new graduate hiring, in particular, inconsistencies in evaluation standards and the subjective nature of assessments had become significant challenges.

Furthermore, the selection workload across stages—including document screening, group discussions, and interviews—was overwhelming, placing a heavy burden on HR staff. To maintain hiring quality while ensuring transparency through hybrid evaluations by AI and interviewers, and to guarantee that final decisions remain human-led, the company decided to introduce 'ailead' to enhance its recruitment process.

Challenges Before ailead Adoption

1. Inconsistent Standards and Subjective Evaluation: Discrepancies in evaluation criteria across departments and interviewers made consistent candidate assessment difficult. 2. Heavy Recruitment Workload: Processing a large number of applicants with limited HR resources made efficiency a priority. 3. Balancing Speed with Quality: Maintaining speed while ensuring adequate evaluation time proved difficult as the volume of applicants grew.

Results of ailead Utilization

1. Sevenfold Increase in Group Discussion Capacity: AI agents analyze discussions and integrate with internal ATS, increasing concurrent processing from approximately 30 to 200 candidates. 2. Sixfold Efficiency Improvement in Evaluation Work: Reduced annual evaluation time from approximately 120 hours to 20 hours. 3. Establishment of Hybrid Evaluation: By using AI as a decision-making aid while leaving final decisions to humans, the company achieved both efficiency and transparency.