[ROXX] Development and Full-Scale Implementation of 'AI Feedback System' to Improve Interview Quality Begins

Q: What are the key facts in this article?

ROXX Inc. has independently developed an 'AI Feedback System' for its job change platform 'Z Career' and has begun full-scale implementation for in-house career advisors. This aims to improve interview quality and streamline the sharing of high-performer expertise.

Q: What is the direct answer?

ROXX Inc. has independently developed an 'AI Feedback System' for its job change platform 'Z Career' and has begun full-scale implementation for in-house career advisors. This aims to improve interview quality and streamline the sharing of high-performer expertise.

Q: What is the source and date?

Source: https://prtimes.jp/main/html/rd/p/000000204.000018129.html | Date: Date unavailable

ROXX Inc. (Headquarters: Shinjuku-ku, Tokyo; Representative Director and President: Taro Nakajima; TSE Growth: 241A; hereinafter ROXX) has independently developed an 'AI Feedback System' that uses AI to improve the quality of business negotiations and interviews, and has begun full-scale implementation for its in-house career advisors (hereinafter CA) on the job change platform 'Z Career'. Concurrently, ROXX has also initiated full-scale development with a view to external provision, including for sales professionals. This system enables immediate comparison and analysis of interview content with high-performer data, and seamlessly executes comprehensive analysis, evaluation, and feedback. This transforms the 'tacit knowledge' of high-performers, which was traditionally implicit, into 'explicit knowledge' and standardizes the coaching process that previously relied on managers' experience. This establishes a system where all CAs can autonomously and continuously improve their interview quality. ■ Background Since its establishment, ROXX has emphasized the 'unique value of human intervention' by CAs, providing support tailored to each job seeker. We believe that the value of an excellent CA in recruitment is not in mechanically matching conditions, but in drawing out what job seekers 'truly value' through dialogue, which they may not yet be able to articulate themselves, and supporting their decision to take a step forward in choosing a career that will occupy one-third of their lives. However, in reviewing interviews and training CAs, organizational challenges arose: reviewing interview logs and providing guidance was time-consuming, detailed individual feedback was difficult, and the accumulated expertise of high-performers could not be fully reflected in training. In addition to the resource shortage on the part of trainers, there was a question of how to formalize the 'tacit knowledge,' which depended on individual experience and intuition, into 'explicit knowled

[ROXX] Development and Full-Scale Implementation of 'AI Feedback System' to Improve Interview Quality Begins

AI Summary (NQ-processed)

AI Analysis