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Dergiler / Yönetim Bilimleri Dergisi / 2025 / Cilt: 23 Sayı: 58

İŞ ZEKÂSI UYGULAMALARINDA YAPAY ZEKÂ TEKNOLOJİLERİNİN RAPORLAMA SÜREÇLERİNE ETKİSİ

THE EFFECT OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES ON REPORTING PROCESSES IN BUSINESS INTELLIGENCE APPLICATIONS

Cemal Çelik(BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ)0000-0002-4027-3789
Sayfa
2159–2181
Yayın Tarihi
2025-10-24
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Uygulama sonucunda YZ araçları üzerinden elde edilen işlevsel raporların işletme karar süreçlerine destek vermesi beklenmektedir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Doğal Dil İşleme (NLP) alanında yaşanan hızlı gelişmeler, Yapay Zekâ (YZ) destekli sohbet robotlarının yaygınlaşıp gelişmesine olanak sağlayarak, firma ve çalışanlarının ihtiyaç duyduğu bilgiye erişimi kolaylaştırmış olur.
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Temel Bulgular & Veri:YZ destekli sohbet botları kullanıcı ifadelerini bağlamsal ve anlamsal olarak analiz edebilmektedir.
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Sonuç & Katkı:Uygulama sonucunda YZ araçları üzerinden elde edilen işlevsel raporların işletme karar süreçlerine destek vermesi beklenmektedir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:İş zekası · İstem (Prompt) · Yapay Zeka

Özet

Doğal Dil İşleme (NLP) alanında yaşanan hızlı gelişmeler, Yapay Zekâ (YZ) destekli sohbet robotlarının yaygınlaşıp gelişmesine olanak sağlayarak, firma ve çalışanlarının ihtiyaç duyduğu bilgiye erişimi kolaylaştırmış olur. YZ destekli sohbet botları kullanıcı ifadelerini bağlamsal ve anlamsal olarak analiz edebilmektedir. Bu nedenle kullanıcı istemleri ve komutlarını anlayıp yorumlayarak istenilen talepler doğrultusunda bilgi üretebilirler. Büyük Dil Modelleri (LLM) kullanılarak geliştirilen YZ araçları Üretken Yapay Zekâ (ÜYZ) alanına evrilerek, iş dünyasına yönelik sektörel çözümlerin üretilmesine ve bu çözümlerin şirket süreçlerine entegre edilmesine olanak sağlamıştır. ÜYZ araçlarının iş uygulamalarında kullanımı ve deneyimlenmesi amacıyla hazırlanmış olan bu çalışmada, iş zekâsı uygulaması üzerinde yer alan; Q&A, Smart Narrative, Copilot ve ChatGPT gibi ÜYZ araçlarının performans becerileri ve fonksiyonları karşılaştırmalı olarak kullanıcı istem (Prompt) komutları ile gösterilmeye çalışılmıştır. Bununla birlikte iş zekâsı ve benzer uygulamalarda yararlanılan istem (Prompt) komutlarının tasarım ve yazımının kullanıcı deneyimlerine getireceği kolaylıklar örnek bir uygulama üzerinden anlatılmıştır. Uygulama sonucunda YZ araçları üzerinden elde edilen işlevsel raporların işletme karar süreçlerine destek vermesi beklenmektedir.

Abstract

Rapid advances in Natural Language Processing (NLP) have enabled the proliferation and development of Artificial Intelligence (AI)-powered chatbots, facilitating access to the information companies and their employees need. AI-powered chatbots can analyze user expressions contextually and semantically. Therefore, they can understand and interpret user prompts and commands to generate information tailored to the desired demands. AI tools developed using Large Language Models (LLMs) have evolved into Generative Artificial Intelligence (GENERATIVE AI), enabling the creation of sector-specific solutions for the business world and the integration of these solutions into company processes. This study, designed to demonstrate the use and experience of GENERATIVE AI tools in business applications, aims to demonstrate the performance capabilities and functions of GENERATIVE AI tools such as Q&A, Smart Narrative, Copilot, and ChatGPT, available on business intelligence applications, through comparative user prompt commands. In addition, the ease of use that the design and writing of prompt commands used in business intelligence and similar applications will bring to user experiences is explained through a sample application. As a result of the application, functional reports obtained through AI tools are expected to support business decision processes.

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Bu Makaleye Atıf Yap

Çelik, C. (2025). İŞ ZEKÂSI UYGULAMALARINDA YAPAY ZEKÂ TEKNOLOJİLERİNİN RAPORLAMA SÜREÇLERİNE ETKİSİ. Yönetim Bilimleri Dergisi, Cilt: 23 Sayı: 58, 2159–2181. https://doi.org/10.35408/comuybd.1654806

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