OneHR Co., Ltd. (Headquarters: Shinagawa-ku, Tokyo; Representative Director and President: Yusaburo Karasawa; hereinafter: the Company) announced the results of its "Joint Research on HR Placement Planning Using Talent Data and AI" (Note), conducted in collaboration with the Osaka City Waterworks Bureau since January 2025. The research confirmed that candidate extraction through matching talent information with position requirements using generative AI (LLM) is possible to a certain extent, and identified challenges for practical implementation. The results indicate that a reduction in tasks related to candidate extraction and review can be expected in the future.
Note: For details on the "Joint Research on HR Placement Planning Using Talent Data and AI" conducted in collaboration with the Osaka City Waterworks Bureau, please refer to our press release "OneHR Concludes Agreement with Osaka City Waterworks Bureau on Joint Research for HR Placement Planning Using Talent Data and AI" (https://onehr.jp/news/20250129/).
### **Verification Points**
The joint research aimed to more effectively create HR placement plans, which the Osaka City Waterworks Bureau has traditionally carried out, by utilizing talent information. Specifically, the following two points were verified:
* Verification of whether AI can enable more effective and efficient HR placement planning. * Verification of what kind of data collection, accumulation, and organization is necessary for AI-driven HR placement planning.
### **Implementation Details**
The HR placement planning operations at the Osaka City Waterworks Bureau involve a combination of two types of placement considerations:
1. Succession planning for vacant managerial positions (section chief, deputy section chief, unit chief) due to transfers or other reasons. 2. Reassignment of staff members who have gained experience in the same department for a certain period to new departments to acquire diverse work experience.
For each of these, efficiency verification was conducted using generative AI (LLM) and combinatorial optimization algorithms.
FACT BOX
- Source: PR TIMES
- Category: Survey