Automation of the Recruitment Process
Generative AI plays a wide range of roles in automating the recruitment process, particularly in areas such as resume screening, job description creation, and communication with candidates.

• Resume Screening: Generative AI quickly analyzes large volumes of resumes and automatically extracts candidates with the required skills and experience. This enables HR personnel to efficiently find suitable candidates without spending excessive time. For example, by setting specific criteria such as keywords or years of experience, AI filters candidates accordingly.

• Job Description Creation: Generative AI automatically generates optimal job descriptions based on job requirements. This allows for the rapid creation of high-quality, consistent job descriptions, streamlining the initial stages of the recruitment process. Specifically, by inputting required skills and job duties, generative AI creates detailed job descriptions.

• Automation of Candidate Communication: Generative AI automates initial communication with candidates, such as scheduling interviews and sending follow-up emails, significantly reducing the burden on recruiters. Additionally, it can automatically respond to general questions from candidates, improving communication efficiency.

By implementing generative AI, the recruitment process becomes more efficient, and quicker, and ensures a fair selection. As a result, companies can acquire better talent in a shorter time, improving the quality of recruitment activities.

Enhancing Engagement and Learning Development
Generative AI is used as an important tool to enhance employee engagement and strengthen learning and development processes. Its benefits are particularly evident in developing engagement tools and providing customized learning and development plans.

• Development of Engagement Tools: Generative AI develops tools to measure and improve employee engagement. For example, it collects and analyzes employee feedback in real-time to identify areas for improving the work environment. Additionally, generative AI can provide personalized messages and support to boost employee motivation, contributing to improved engagement.

• Provision of Customized Learning and Development Plans: Generative AI creates individual learning and development plans based on employees’ skills and career goals. It suggests the best training programs and career paths based on employees’ past performance and skill evaluations. This allows employees to efficiently enhance their skills using the most appropriate learning resources. Specific examples include generative AI recommending online courses, workshops, and arranging mentorships.

These generative AI functions help improve employee engagement and streamline learning and development processes. As a result, overall company productivity improves, and employee satisfaction increases.

Improvement in Performance Management
Generative AI also plays a significant role in improving performance management, particularly in the areas of data analysis for performance evaluation and the automatic generation of individual feedback.

• Performance Evaluation Through Data Analysis: Generative AI thoroughly analyzes employees’ performance data and provides objective performance evaluations. This enables fairer and more accurate assessments compared to traditional subjective evaluation methods. Specifically, it integrates various data points, such as work progress, the quality of deliverables, and patterns in working hours, to evaluate employees’ performance. This process helps improve consistency and reliability in performance evaluations.

• Automatic Generation of Individual Feedback: Generative AI generates individual feedback for each employee based on their performance data. This allows for timely and practical suggestions for improvement or praise. For example, feedback on progress in performance or skill improvement for specific projects is automatically created and provided to the employees. This personalized feedback not only boosts employee motivation but also leads to specific improvements in behavior.

With these generative AI functions, performance management becomes more effective and efficient. Companies can clearly understand employees’ strengths and areas for improvement and provide the appropriate support and guidance.