Yapay Zekâ Tabanlı Karar Destek Sistemleri İle Personel Seçimi

Öz

Dijitalleşmenin hız kazandığı günümüzde, insan kaynakları yönetiminde yapay zekâ (YZ) tabanlı karar destek sistemlerinin kullanımı giderek artmaktadır. Bu çalışma, bankacılık sektöründe personel seçim sürecini daha nesnel ve etkin hale getirmek amacıyla YZ destekli çok kriterli bir değerlendirme modeli önermektedir. Araştırmada, personel seçiminde dikkate alınması gereken dokuz temel kriter belirlenmiş ve bu kriterler TOPSIS yöntemiyle sıralanarak ideal aday profili oluşturulmuştur. Bulgular, problem çözme yeteneği, motivasyon ve iletişim becerisi gibi bireysel yeterliliklerin öncelikli olduğunu ortaya koymuştur. Ayrıca etik değerler ve teknolojik adaptasyon gibi kriterlerin göreli önem düzeyleri değerlendirilmiştir. Araştırma, karar verme süreçlerinde veri temelli ve şeffaf yaklaşımların benimsenmesini teşvik ederken, insan kaynakları uygulamalarında dijital dönüşümün yönünü belirlemeye katkı sunmaktadır. Çalışmanın sonuçları, literatürdeki benzer araştırmalarla karşılaştırılmış, teorik katkılar ve uygulamaya yönelik öneriler tartışılmıştır. Bu bağlamda araştırma, hem akademik literatüre katkı sağlamakta hem de sektörel uygulamalara rehberlik etmektedir.

Anahtar Kelimeler

• Yapay Zekâ
• Karar Destek Sistemleri
• Personel Seçimi
• TOPSIS Yöntemi.

PERSONNEL SELECTİON USİNG ARTİFİCİAL INTELLİGENCE-BASED DECİSİON SUPPORT SYSTEMS

Abstract

With the accelerating pace of digitalization, the use of artificial intelligence (AI)-based decision support systems in human resource management has become increasingly prevalent. This study proposes an AI-assisted multi-criteria evaluation model to enhance the objectivity and efficiency of personnel selection processes in the banking sector. Nine essential evaluation criteria were identified and prioritized using the TOPSIS method, resulting in the development of an ideal candidate profile. The findings indicate that individual competencies such as problem-solving ability, motivation, and communication skills are of primary importance. Additionally, the relative significance of criteria such as ethical values and technological adaptability was assessed. The study encourages the adoption of data-driven and transparent approaches in decision-making and contributes to shaping the digital transformation of human resources practices. The results are compared with similar studies in the existing literature, and both theoretical contributions and practical implications are discussed. Accordingly, this research offers valuable insights for both academia and industry by providing a structured framework for AI-integrated personnel selection.

Keywords

• Artificial Intelligence
• Decision Support Systems
• Personnel Selection
• TOPSIS Method.

Kaynakça

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