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

Yıl 2025, Cilt: 23 Sayı: 58, 2159 - 2181, 24.10.2025
https://doi.org/10.35408/comuybd.1654806

Öz

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.

Kaynakça

  • Adlof, L., ve Kim, M. (2023). Adapting to the Future: ChatGPT as a Means for Supporting Constructivist Learning Environments. TechTrends,68(1), 37-46. DOI:10.1007/s11528-023-00899-x
  • Aslam, F. (2023). The Impact of Artificial Intelligence on Chatbot Technology: A Study on the Current Advancements and Leading Innovations. AJP, 7(2), 62-72. https://doi.org/10.47672/ajdikm.1543
  • Aşiroğlu, M. (2024). Power BI İstanbul, Erişim03.02.2025, https://www.youtube.com/watch?v=H8UyBgzOFdw
  • Azmia, M., Mansour, A., ve Azmi, C. (2023). A Context-Aware Empowering Business with AI: Case of Chatbots . Procedia, 224(1), 479-484. Doi:10.1016/j.procs.2023.09.068
  • Bansal, N., Sharma, A., ve Singh, R. K. (2019). Fuzzy AHP Approach For Legal Judgement Summarization. Journal of Management Analytics , 6(3),323-340. https://doi.org/10.1080/23270012.2019.1655672
  • Bharadiya, J. P. (2023). A Comparative Study of Business Intelligence and Artificial Intelligence with Big Data Analytics . American Journal of Artificial Intelligenc, 7(1),24-30, Doi: 10.11648/j.ajai.20230701.14
  • Bırd, C., Ford, D. ve Zımmermann, T. (2022). Taking Flight with Copilot. Early insights and opportunities of AI-powered pair-programming tools, ACM Library, 20(6),35-57 https://dl.acm.org/doi/pdf/10.1145/3582083
  • Cao, Y., Lı, S., Lıu, Y., ve Yan, Z. (2023, 4 1). A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. ACM, 37(4), 1-44. DOI:10.48550/arXiv.2303.04226
  • Castellucio, C. (2024, 2 7). Introduction to Generaitive AI and LLMs, Erişim:04.04.2025. https://github.com/microsoft/generative-ai-for-beginners/tree/main/01-introduction-to-genai
  • Chao, M.-H., Trappey, A. J., ve C.-T. W. (2021). Emerging Technologies of Natural Language-Enabled Chatbots: AReview and Trend Forecast Using Intelligent OntologyExtraction and Patent Analytics. 2021,Wiley, 1-26. DOI: 10.1155/2021/5511866
  • Chrıstıan Bırd, Ford, D., ve Zımmermann, T. (2022). Taking Flight with Copilot. Acmqueue, 20(6),34-57, https://doi.org/10.1145/3582083
  • Cusumano, M. A. (2023). Generative AI as a New Innovation Platform. Communıcatıons Of The Acm |, 65(10), 1-4. DOI: 10.1145/3615859
  • Çetin, S. (2024). Yapay Zekâ, Hukuk Ve Düzenlemeler, Erişim : 14.01.2024,. https://www.birgun.net/haber/yapay-zeka-hukuk-ve-duzenlemeler-498165
  • Darvishi, A., Khosravi, H., Sadiq, S., Gasevic, D., ve Siemens, G. (2024). Impact of AI assistance on student agency. Computers & Education, 2010, 1-18. Doi:doi.org/10.1016/j.compedu.2023.104967
  • Davenport, T. H., ve Ronankı, R. (2018, January-February 5). Artıfıcıal Intellıgence For The Real World. Harvard Busıness Revıew,,109-119.
  • Dwivedi, Y. K., Kshetri, N., ve Hughes, L. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management , 71, 1-63. DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642
  • Eboigbe, E. O., ve Farayola, O. A. (2023). Busıness Intellıgence Transformatıon Through Aı And Data Analytıcs. Engineering Science & Technology Journal , 4(5),285-296. DOI: 10.51594/estj.v4i5.616
  • Erden, C. (2021). Python İle Veri Madenciliği. İstanbul: KODLAB.
  • France, S. L. (2024). Navigating software development in the ChatGPT and GitHub Copilot Era. Kelley School of Business, 67(5), 1-13., https://doi.org/10.1016/j.bushor.2024.05.009
  • Gang, T., ve Bei, S. (2008). The Research & Application of Business Intelligence System in Retail Industry. International Conference on Automation and Logistics , IEEE, China, 86-91
  • Gharaibeh, A.,ve Kassim, N. M. (2024). ChatGPT-Artificial Intelligence Studies of Business Analytics Adoption and Usage. Springer.
  • Grover, V., Jeong, S. R., Kettinger, W. J., ve Teng, J. T. (2000). The Implementation of Business Process Reengineering. Journal of Management Information Systems, 1-37. https://doi.org/10.1080/07421222.1995.11518072
  • Hai, H. N. (2023). ChatGPT: The Evolution of Natural Language Processing. Authorea, 1-68. DOI: 10.22541/au.167935454.46075854/v1
  • Hart, M. ve Leavitt, S. (2024). Create smart narrative summaries. Erişim :10.02.2024 https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-smart-narrative
  • Haywood, S. ve Wolfmsft, A. (2024). How do generative AI and LLMs work? ,Erişim.01.06.2023 https://learn.microsoft.com/tr-tr/dotnet/ai/conceptual/how-genai-and-llms-work
  • Jiang, E., Olson, K., Toh, E., ve Molina, A. (tarih yok). Prompt-based Prototyping with Large Language Models. In CHI Conference on Human Factors in Computing Systems, ACM, 35, 1-8, DOI:https://dl.acm.org/doi/10.1145/3491101.3503564
  • K.Gowthami, ve Kumar, M. P. (2017). Study on Business Intelligence Tools for Enterprise Dashboard Development. 2022 3rd International Conference on Intelligent Engineering and Management, London,2987-2993.
  • Kang, Y., Zhao Cai, Tan, C.-W., Huang, Q., ve Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172, https://doi.org/10.1080/23270012.2020.1756939
  • Khalil, N. Z., Kong, N., ve Fricke, H. (2024). The influence of GNP on the mechanical andthermomechanical properties of epoxy adhesive:Pearson correlation matrix and heatmapapplication in data interpretation. Wiley, 45(10), 1-26. DOI:10.1002/pc.28390
  • Koc, E., Hatipoğlu, S., Kıvrak, O., Çelik, C., ve Koç, K. (2024). Houston, we have a problem!: The use of ChatGPT in responding to customer complaints. Technology in Society, 74, 1-20, https://doi.org/10.1016/j.techsoc.2023.102333
  • Korzynski, P., Kozminski, A. K., ve Baczynska, A. (2023). Navigating leadership challenges with technology: Uncovering the potential of ChatGPT, virtual reality, human capital management systems, robotic process automation, and social media. IER, 9(2), 7-17.
  • Kshetri, N., Dwivedi, Y. K., Davenport, T. H., & Panteli, N. (2024, 4 5). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75,. 1-10. https://doi.org/10.1016/j.ijinfomgt.2023.102716
  • Kumar, T., Garg, V., & Kumar, S. L. (2023). Measuring Impact of Generative AI in Software Development and Innovation . Springer , 57-67. DOI:10.1007/978-981-97-1682-1_6
  • Kytö, M. (2024). Copilot for Microsoft 365: A Comprehensive End-user Training Plan for Organizations. Haaga-Helia, 1-34. DOI: https://www.theseus.fi/handle/10024/852578
  • Leavitt, S. (2025). Create smart narrative summaries.Erişim 30.11.2024, https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-smart-narrative
  • Liu, V., ve Chilton, L. B. (2022). Design Guidelines for Prompt Engineering Text-to-Image Generative Models. ACM, 384,1-23. DOI: https://doi.org/10.1145/3491102.350182
  • Mbizo, T., Oosterwyk, G., Tsibolane, P., ve Kautondokwa, P. (2024). Cautious Optimism: The Influence of Generative AI Tools in Software Development Projects. SAICSIT, 361-373. DOI:10.1007/978-3-031-64881-6_21
  • Michael, C. I., Ipede, O. J., ve Adejumo, A. D. (2024). Data-driven decision making in IT: Leveraging AI and data science for business intelligence . WJARR, 23(1), 472-481. DOI:10.30574/wjarr.2024.23.1.2010
  • Microsoft. (2025). Erişim : 03.04.2025, https://www.microsoft.com/tr-tr/power-platform/products/power-bi/pricing
  • Mikalef, P., ve Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 1-20. DOI : https://doi.org/10.1016/j.im.2021.103434
  • Mishra, A., Soni, U., Arunkumar, A., & Huang, J. (2023). PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models. arXiv, 1-13.
  • Morandini, S., Fraboni, F., ve Angelis, M. D. (2023). The Impact Of Artıfıcıal Intellıgence On Workers’ Skılls: Upskıllıng And Reskıllıng In Organısatıons. Informing Science, 26,39-69, DOI:10.28945/5078
  • Nadella, S. (2024). Everyday AI in Microsoft 365. Microsoft Press.
  • Nah, F. F.-H., Zheng, R., Cai, J., Siau, K., ve Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277-304, DOI: https://doi.org/10.1080/15228053.2023.2233814
  • Passosl, M. R., ve Júnio, J. E. (2023). Chatbot, Chatgpt: Artificial İntelligence And/Or Business Intelligence And/Or Robotic Untruths, For Now. Doenças, 35, 1-4. DOI:10.5327/DST-2177-8264-2023351330
  • Popescu, C.-A. (2020). Chatbots as Marketing Communication Tool. FAIMA , 8(3), 63-75, DOI:10.4018/978-1-6684-7735-9.ch003
  • Rawat, B., Bist, A. S., Rahardja, U., Aini, Q., ve Sanjaya, Y. P. (2022). Recent Deep Learning Based NLP Techniques for Chatbot Development: An Exhaustive Survey, Conference: 2022 10th International Conference, Batam 1-4.
  • Rospigliosi, P. A. (2024). What is the role of ChatGPT and other large language model AI in Higher Education? Interactive Learning Environments, 32(2), 393-394. DOI: https://doi.org/10.1080/10494820.2024.2330836
  • Seppänen, L. (2024). Implementation of generative artificial intelligence in a project-based company. Oulin Yliopisto. DOI: nbnfioulu-202411126709.pd
  • Sharabi, K., ve Iseminger, D. (2024). Find Insights in Your Reports. Erişim : 21.06.2024 , https://learn.microsoft.com/en-us/power-bi/create-reports/insights
  • Sheikh, H., Prins, C., ve Schrijvers, E. (2023). Mission AI The New System Technology. Netherlands: Springer.
  • Short, C. E., ve Short, J. C. (2023). The artificially intelligent entrepreneur: ChatGPT, prompt engineering, and entrepreneurial rhetoric creation . Journal of Business Venturing Insights , 25, 1-10, DOI: https://doi.org/10.1016/j.jbvi.2023.e00388
  • Smith, B., ve Shum, H. (2022). The Future Computed Artificial Intelligence and İts Role İn Society. Washington: Microsoft Corporation.
  • Sparkman, M., ve Piesco, J. (2024). Pin a tile to a dashboard from Q&A. Erişim Tarihi :10.05.2024, https://learn.microsoft.com/en-us/power-bi/create-reports/service-dashboard-pin-tile-from-q-and-a
  • Tepe, M., ve Emekli, E. (2024). Decoding medical jargon: The use of AI language models (ChatGPT-4, BARD, microsoft copilot) in radiology reports. Patient Education and Counseling, 126, 1-5. DOI: https://doi.org/10.1016/j.pec.2024.108307
  • Vinuesa, R., Azizpour, H., Leite, I., ve Balaam, M. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature, 1-15. DOI:10.48550/arXiv.1905.00501
  • Wang, C.-H. (2015). Using quality function deployment to conduct vendor assessment and supplier recommendation for business-intelligence systems. Computers & Industrial Engineering, 84, 24:31. DOI: https://doi.org/10.1016/j.cie.2014.10.00
  • White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Henry Gilbert, A. E.-S., ve Schmidt, D. C. (2023). A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT. ArXiv, 5, 1-19. DOI:10.48550/arXiv.2302.11382
  • Yue Kanga, Cai, Z., Tan, C.-W., Huang, Q., ve Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172. DOI: https://doi.org/10.1080/23270012.2020.1756939
  • Zohuri, B., ve Moghaddam, M. (2020). From Business Intelligence to Artificial Intelligence. Lupine, 231-243. DOI:10.32474/MAMS.2020.02.000137

İŞ ZEKÂSI UYGULAMALARINDA YAPAY ZEKÂ TEKNOLOJİLERİNİN RAPORLAMA SÜREÇLERİNE ETKİSİ

Yıl 2025, Cilt: 23 Sayı: 58, 2159 - 2181, 24.10.2025
https://doi.org/10.35408/comuybd.1654806

Öz

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.

Etik Beyan

Bu çalışmada Etik Beyan teşkil edecek bir unsur yoktur

Kaynakça

  • Adlof, L., ve Kim, M. (2023). Adapting to the Future: ChatGPT as a Means for Supporting Constructivist Learning Environments. TechTrends,68(1), 37-46. DOI:10.1007/s11528-023-00899-x
  • Aslam, F. (2023). The Impact of Artificial Intelligence on Chatbot Technology: A Study on the Current Advancements and Leading Innovations. AJP, 7(2), 62-72. https://doi.org/10.47672/ajdikm.1543
  • Aşiroğlu, M. (2024). Power BI İstanbul, Erişim03.02.2025, https://www.youtube.com/watch?v=H8UyBgzOFdw
  • Azmia, M., Mansour, A., ve Azmi, C. (2023). A Context-Aware Empowering Business with AI: Case of Chatbots . Procedia, 224(1), 479-484. Doi:10.1016/j.procs.2023.09.068
  • Bansal, N., Sharma, A., ve Singh, R. K. (2019). Fuzzy AHP Approach For Legal Judgement Summarization. Journal of Management Analytics , 6(3),323-340. https://doi.org/10.1080/23270012.2019.1655672
  • Bharadiya, J. P. (2023). A Comparative Study of Business Intelligence and Artificial Intelligence with Big Data Analytics . American Journal of Artificial Intelligenc, 7(1),24-30, Doi: 10.11648/j.ajai.20230701.14
  • Bırd, C., Ford, D. ve Zımmermann, T. (2022). Taking Flight with Copilot. Early insights and opportunities of AI-powered pair-programming tools, ACM Library, 20(6),35-57 https://dl.acm.org/doi/pdf/10.1145/3582083
  • Cao, Y., Lı, S., Lıu, Y., ve Yan, Z. (2023, 4 1). A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. ACM, 37(4), 1-44. DOI:10.48550/arXiv.2303.04226
  • Castellucio, C. (2024, 2 7). Introduction to Generaitive AI and LLMs, Erişim:04.04.2025. https://github.com/microsoft/generative-ai-for-beginners/tree/main/01-introduction-to-genai
  • Chao, M.-H., Trappey, A. J., ve C.-T. W. (2021). Emerging Technologies of Natural Language-Enabled Chatbots: AReview and Trend Forecast Using Intelligent OntologyExtraction and Patent Analytics. 2021,Wiley, 1-26. DOI: 10.1155/2021/5511866
  • Chrıstıan Bırd, Ford, D., ve Zımmermann, T. (2022). Taking Flight with Copilot. Acmqueue, 20(6),34-57, https://doi.org/10.1145/3582083
  • Cusumano, M. A. (2023). Generative AI as a New Innovation Platform. Communıcatıons Of The Acm |, 65(10), 1-4. DOI: 10.1145/3615859
  • Çetin, S. (2024). Yapay Zekâ, Hukuk Ve Düzenlemeler, Erişim : 14.01.2024,. https://www.birgun.net/haber/yapay-zeka-hukuk-ve-duzenlemeler-498165
  • Darvishi, A., Khosravi, H., Sadiq, S., Gasevic, D., ve Siemens, G. (2024). Impact of AI assistance on student agency. Computers & Education, 2010, 1-18. Doi:doi.org/10.1016/j.compedu.2023.104967
  • Davenport, T. H., ve Ronankı, R. (2018, January-February 5). Artıfıcıal Intellıgence For The Real World. Harvard Busıness Revıew,,109-119.
  • Dwivedi, Y. K., Kshetri, N., ve Hughes, L. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management , 71, 1-63. DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642
  • Eboigbe, E. O., ve Farayola, O. A. (2023). Busıness Intellıgence Transformatıon Through Aı And Data Analytıcs. Engineering Science & Technology Journal , 4(5),285-296. DOI: 10.51594/estj.v4i5.616
  • Erden, C. (2021). Python İle Veri Madenciliği. İstanbul: KODLAB.
  • France, S. L. (2024). Navigating software development in the ChatGPT and GitHub Copilot Era. Kelley School of Business, 67(5), 1-13., https://doi.org/10.1016/j.bushor.2024.05.009
  • Gang, T., ve Bei, S. (2008). The Research & Application of Business Intelligence System in Retail Industry. International Conference on Automation and Logistics , IEEE, China, 86-91
  • Gharaibeh, A.,ve Kassim, N. M. (2024). ChatGPT-Artificial Intelligence Studies of Business Analytics Adoption and Usage. Springer.
  • Grover, V., Jeong, S. R., Kettinger, W. J., ve Teng, J. T. (2000). The Implementation of Business Process Reengineering. Journal of Management Information Systems, 1-37. https://doi.org/10.1080/07421222.1995.11518072
  • Hai, H. N. (2023). ChatGPT: The Evolution of Natural Language Processing. Authorea, 1-68. DOI: 10.22541/au.167935454.46075854/v1
  • Hart, M. ve Leavitt, S. (2024). Create smart narrative summaries. Erişim :10.02.2024 https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-smart-narrative
  • Haywood, S. ve Wolfmsft, A. (2024). How do generative AI and LLMs work? ,Erişim.01.06.2023 https://learn.microsoft.com/tr-tr/dotnet/ai/conceptual/how-genai-and-llms-work
  • Jiang, E., Olson, K., Toh, E., ve Molina, A. (tarih yok). Prompt-based Prototyping with Large Language Models. In CHI Conference on Human Factors in Computing Systems, ACM, 35, 1-8, DOI:https://dl.acm.org/doi/10.1145/3491101.3503564
  • K.Gowthami, ve Kumar, M. P. (2017). Study on Business Intelligence Tools for Enterprise Dashboard Development. 2022 3rd International Conference on Intelligent Engineering and Management, London,2987-2993.
  • Kang, Y., Zhao Cai, Tan, C.-W., Huang, Q., ve Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172, https://doi.org/10.1080/23270012.2020.1756939
  • Khalil, N. Z., Kong, N., ve Fricke, H. (2024). The influence of GNP on the mechanical andthermomechanical properties of epoxy adhesive:Pearson correlation matrix and heatmapapplication in data interpretation. Wiley, 45(10), 1-26. DOI:10.1002/pc.28390
  • Koc, E., Hatipoğlu, S., Kıvrak, O., Çelik, C., ve Koç, K. (2024). Houston, we have a problem!: The use of ChatGPT in responding to customer complaints. Technology in Society, 74, 1-20, https://doi.org/10.1016/j.techsoc.2023.102333
  • Korzynski, P., Kozminski, A. K., ve Baczynska, A. (2023). Navigating leadership challenges with technology: Uncovering the potential of ChatGPT, virtual reality, human capital management systems, robotic process automation, and social media. IER, 9(2), 7-17.
  • Kshetri, N., Dwivedi, Y. K., Davenport, T. H., & Panteli, N. (2024, 4 5). Generative artificial intelligence in marketing: Applications, opportunities, challenges, and research agenda. International Journal of Information Management, 75,. 1-10. https://doi.org/10.1016/j.ijinfomgt.2023.102716
  • Kumar, T., Garg, V., & Kumar, S. L. (2023). Measuring Impact of Generative AI in Software Development and Innovation . Springer , 57-67. DOI:10.1007/978-981-97-1682-1_6
  • Kytö, M. (2024). Copilot for Microsoft 365: A Comprehensive End-user Training Plan for Organizations. Haaga-Helia, 1-34. DOI: https://www.theseus.fi/handle/10024/852578
  • Leavitt, S. (2025). Create smart narrative summaries.Erişim 30.11.2024, https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-smart-narrative
  • Liu, V., ve Chilton, L. B. (2022). Design Guidelines for Prompt Engineering Text-to-Image Generative Models. ACM, 384,1-23. DOI: https://doi.org/10.1145/3491102.350182
  • Mbizo, T., Oosterwyk, G., Tsibolane, P., ve Kautondokwa, P. (2024). Cautious Optimism: The Influence of Generative AI Tools in Software Development Projects. SAICSIT, 361-373. DOI:10.1007/978-3-031-64881-6_21
  • Michael, C. I., Ipede, O. J., ve Adejumo, A. D. (2024). Data-driven decision making in IT: Leveraging AI and data science for business intelligence . WJARR, 23(1), 472-481. DOI:10.30574/wjarr.2024.23.1.2010
  • Microsoft. (2025). Erişim : 03.04.2025, https://www.microsoft.com/tr-tr/power-platform/products/power-bi/pricing
  • Mikalef, P., ve Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 1-20. DOI : https://doi.org/10.1016/j.im.2021.103434
  • Mishra, A., Soni, U., Arunkumar, A., & Huang, J. (2023). PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models. arXiv, 1-13.
  • Morandini, S., Fraboni, F., ve Angelis, M. D. (2023). The Impact Of Artıfıcıal Intellıgence On Workers’ Skılls: Upskıllıng And Reskıllıng In Organısatıons. Informing Science, 26,39-69, DOI:10.28945/5078
  • Nadella, S. (2024). Everyday AI in Microsoft 365. Microsoft Press.
  • Nah, F. F.-H., Zheng, R., Cai, J., Siau, K., ve Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277-304, DOI: https://doi.org/10.1080/15228053.2023.2233814
  • Passosl, M. R., ve Júnio, J. E. (2023). Chatbot, Chatgpt: Artificial İntelligence And/Or Business Intelligence And/Or Robotic Untruths, For Now. Doenças, 35, 1-4. DOI:10.5327/DST-2177-8264-2023351330
  • Popescu, C.-A. (2020). Chatbots as Marketing Communication Tool. FAIMA , 8(3), 63-75, DOI:10.4018/978-1-6684-7735-9.ch003
  • Rawat, B., Bist, A. S., Rahardja, U., Aini, Q., ve Sanjaya, Y. P. (2022). Recent Deep Learning Based NLP Techniques for Chatbot Development: An Exhaustive Survey, Conference: 2022 10th International Conference, Batam 1-4.
  • Rospigliosi, P. A. (2024). What is the role of ChatGPT and other large language model AI in Higher Education? Interactive Learning Environments, 32(2), 393-394. DOI: https://doi.org/10.1080/10494820.2024.2330836
  • Seppänen, L. (2024). Implementation of generative artificial intelligence in a project-based company. Oulin Yliopisto. DOI: nbnfioulu-202411126709.pd
  • Sharabi, K., ve Iseminger, D. (2024). Find Insights in Your Reports. Erişim : 21.06.2024 , https://learn.microsoft.com/en-us/power-bi/create-reports/insights
  • Sheikh, H., Prins, C., ve Schrijvers, E. (2023). Mission AI The New System Technology. Netherlands: Springer.
  • Short, C. E., ve Short, J. C. (2023). The artificially intelligent entrepreneur: ChatGPT, prompt engineering, and entrepreneurial rhetoric creation . Journal of Business Venturing Insights , 25, 1-10, DOI: https://doi.org/10.1016/j.jbvi.2023.e00388
  • Smith, B., ve Shum, H. (2022). The Future Computed Artificial Intelligence and İts Role İn Society. Washington: Microsoft Corporation.
  • Sparkman, M., ve Piesco, J. (2024). Pin a tile to a dashboard from Q&A. Erişim Tarihi :10.05.2024, https://learn.microsoft.com/en-us/power-bi/create-reports/service-dashboard-pin-tile-from-q-and-a
  • Tepe, M., ve Emekli, E. (2024). Decoding medical jargon: The use of AI language models (ChatGPT-4, BARD, microsoft copilot) in radiology reports. Patient Education and Counseling, 126, 1-5. DOI: https://doi.org/10.1016/j.pec.2024.108307
  • Vinuesa, R., Azizpour, H., Leite, I., ve Balaam, M. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature, 1-15. DOI:10.48550/arXiv.1905.00501
  • Wang, C.-H. (2015). Using quality function deployment to conduct vendor assessment and supplier recommendation for business-intelligence systems. Computers & Industrial Engineering, 84, 24:31. DOI: https://doi.org/10.1016/j.cie.2014.10.00
  • White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Henry Gilbert, A. E.-S., ve Schmidt, D. C. (2023). A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT. ArXiv, 5, 1-19. DOI:10.48550/arXiv.2302.11382
  • Yue Kanga, Cai, Z., Tan, C.-W., Huang, Q., ve Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172. DOI: https://doi.org/10.1080/23270012.2020.1756939
  • Zohuri, B., ve Moghaddam, M. (2020). From Business Intelligence to Artificial Intelligence. Lupine, 231-243. DOI:10.32474/MAMS.2020.02.000137
Toplam 60 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Operasyon Stratejisi
Bölüm Araştırma Makalesi
Yazarlar

Cemal Çelik 0000-0002-4027-3789

Gönderilme Tarihi 10 Mart 2025
Kabul Tarihi 11 Eylül 2025
Yayımlanma Tarihi 24 Ekim 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 23 Sayı: 58

Kaynak Göster

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

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