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YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA

Year 2023, Issue: 98, 21 - 42, 17.04.2023
https://doi.org/10.25095/mufad.1259939

Abstract

Bu çalışmada, yapay zekâ odaklı iç denetim kültürünün, iç denetçiler tarafından yapay zekânın dikkate alınıp alınmadığının ve yapay zekânın iç denetçilerin algısı üzerindeki etkisinin ortaya konması amaçlanmaktadır. Bu amaç doğrultusunda, Borsa İstanbul 100 Endeksi’nde yer alan şirketlere Microsoft Form aracılığıyla anket formu gönderilmiştir. Araştırmaya Borsa İstanbul 100 Endeksi’nde yer alan 67 tane şirketin iç denetçisi katılmıştır. SPSS 22.0 programı yardımıyla anketten elde edilen veriler; yüzde ve frekans gibi tanımlayıcı istatistiklerle birlikte Kruskal-Wallis ve Mann-Whitney U testleri kullanılarak analiz edilmiştir. Araştırma sonucunda, yapay zekâ araçlarının iç denetimde kullanılması gerektiği ve yapay zekânın iç denetçilerin algılarını sorumluluk, kariyer planlaması, motivasyon, kalite, performans ve verimlilik gibi çeşitli konularda etkilediği tespit edilmiştir. Ayrıca, iç denetçilerin aynı pozisyonda çalışma süresi ile yapay zekânın kullanılabilirliği arasında istatistiksel olarak anlamlı bir fark olduğu saptanmıştır.

References

  • Albawwata, I. - Al Frijata, Y. (2021), “An Analysis of Auditors’ Perceptions Towards Artificial Intelligence and Its Contribution to Audit Quality”, Accounting, pp. 755-762.
  • Al-Sayyed, S. - Shaher, F. - Lena, M. (2021), “The Effect of Artificial Intelligence Technologies on Audit Evidence”, Accounting, pp. 281-288.
  • Alina, C. - Cerasela, S. (2018), “Internal Audit Role in Artificial Intelligence”, University Annals, Economic Sciences Series XVII (1).
  • Baldwin, A. - Brown, C. - Trinkle, B. (2006), “Opportunities for Artificial Intelligence Development in The Accounting Domain: The Case for Auditing”, Intelligent Systems in Accounting, Finance and Management, 14, pp. 77-86.
  • Bringsjord, S. - Govindarajulu, N. (2018), “Artificial Intelligence”, The Stanford Encyclopedia of Philosophy, https://plato.stanford.edu/entries/artificial-intelligence/#HistAI, (Erişim Tarihi: 12 Ocak 2023).
  • Chassignol, Maud - Aleksandr, Khoroshavin - Alexandra, Klimova - Anna, Bilyatdinova (2018), “Artificial Intelligence Trends in Education: A Narrative Overview”, Procedia Computer Science, 136, pp. 16-24.
  • Commerford, B. - Dennis, S. - Joe, J. - Ulla, W. (2021). “Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence”, Journal of Accounting Research, 60 (1), pp. 171-201.
  • Corea, F. (2018), “AI Knowledge Map: How to Classify AI Technologies”, Forbes, https://www.forbes.com/sites/cognitiveworld/2018/08/22/ai-knowledge-map-how-to-classify-ai-technologies/, (Erişim Tarihi: 2 Şubat 2023).
  • Efe, A. - Tunçbilek, M. (2023), “Yapay Zekâ Algoritmaları ile Dönüşen Denetim Araçları Üzerine Bir Değerlendirme”, Denetişim, 27, ss. 72-102.
  • Faggella, D. (2020), “AI in The Accounting Big Four-Comparing Deloitte, PwC, KPMG, and EY”, https://emerj.com/ai-sector-overviews/ai-in-the-accounting-bigfour-comparing-deloitte-pwc-kpmg-and-ey/, (Erişim Tarihi: 9 Ocak 2023).
  • Gentner, Daniel – Birgit, Stelzer – Bujar, Ramosaj – Leo, Brecht (2018), “Strategic Foresight of Future B2b Customer Opportunities Through Machine Learning”, Technology Innovation Management Review, 8, pp. 5-17.
  • Gopalan, Puthukulam – Anitha, Ravikumar – Ravi, S. – Krishna, M. (2021), “Auditors' Perception on the Impact of Artificial Intelligence on Professional Skepticism and Judgment in Oman”, Universal Journal of Accounting and Finance, 9 (5), pp. 1184-1190.
  • Gusai, O. P. (2019), “Robot Human Interaction: Role of Artificial Intelligence in Accounting and Auditing”, Indian Journal of Accounting, 51(1), pp. 59-62.
  • Hongdan, Han - Radha, K. - Robin, Jarvis - Chima, M. - David, Botchie (2022), “Accounting and Auditing with Blockchain Technology and Artificial Intelligence: A Literature Review”, International Journal of AccountingInformation Systems, 48, pp. 1-16.
  • Huang, F. - Vasarhelyi, M. (2019), “Applying Robotic Process Automation (RPA) in Auditing: A Framework”, International Journal of Accounting Information Systems, 35, pp. 1-11.
  • Khamis, Abdullah (2021), “The Impact of Artificial Intelligence in Auditing and Accounting Decision Making”, https://www.researchgate.net/publication/352166419_The_Impact_ of_Artificial_Intelligence_inAuditing_and_Accounting_Decision_Making, (Erişim Tarihi: 6 Ocak 2023).
  • Kokina, J. - Davenport, T. (2017), “The Emergence of Artificial Intelligence: How Automation is Changing Auditing”, Journal of Emerging Technologies in Accounting 14(1), pp. 115-122.
  • Köse, E. - Apalı, A. - Aldemir, M. (2022), “Denetçilerin Yapay Zekâya Yönelik Algılarının Denetim Kalitesine Etkisi Üzerine Bir Araştırma”, Denetişim, pp. 32-44.
  • Law, K. - Shen, M. (2020), “How Does Artificial Intelligence Shape the Audit Industry?”, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3718343, (Erişim Tarihi:20 Ocak 2023).
  • McKinsey Global Institute, (2017), “Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation”, https://www.mckinsey.com/∼/media/McKinsey/Featured%20Insights /Future%20of%20Organizations/What%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Repo rt-December-6-2017.ashx, (Erişim Tarihi:16 Şubat 2023).
  • Moffitt, Kevin - Andrea, Rozario - Vasarhelyi, M. (2018), “Robotic Process Automation for Auditing”, Journal of Emerging Technologies in Accounting, 15, pp. 1-10.
  • Noordin, Azima - Khaled, Hussainey – Ahmad, Faisal (2022), “The Use of Artificial Intelligence and Audit Quality: An Analysis from the Perspectives of External Auditors in the UAE”, Journal of Risk and Financial Management, 15(339), pp. 1-14.
  • Nwakaego, Duru – Okpe, Ikechukwu (2015), “The Effect of Accounts Payable Ratio on The Financial Performance of Food and Beverages Manufacturing Companies in Nigeria”, Journal of Research in Business and Management, 3, pp. 15-21.
  • Özçetin, N. (2022), “Muhasebe Denetiminde Yapay Zekâ”, Uşak Üniversitesi Uygulamalı Bilimler Fakültesi Dergisi, 2(1), ss. 29-41.
  • Raschke, R. - Saiewitz, A. - Kachroo, P. - Lennard, J. (2018), “AI Enhanced Audit Inquiry: A Research Note”, Journal of Emerging Technologies in Accounting, 15(2), pp. 111-116.
  • Russell, S. - Norvig, P. (2010), “Artificial Intelligence - A Modern Approach”, Prentice-Hall. Schulenberg, Jennifer (2007), “Analysing Police Decision-Making: Assessing The Application of A Mixed-Method/Mixed-Model Research Design”, International Journal of Social Research Methodology, 10, pp. 99-119.
  • Sun, T. (2019), “Applying Deep Learning to Audit Procedures: An Illustrative Framework”, Accounting Horizons, 33(3), pp. 89-109.
  • Schwab, K. - Davis, N. - Nadella, S. (2018), “Shaping The Fourth Industrial Revolution”, World Economic Forum, https://jmss.vic.edu.au/wp-content/uploads/2021/06/The_Fourth_In dustrial_Revolution.pdf, (Erişim Tarihi: 10 Ocak 2023).
  • Tiberius, V. - Hirth, S. (2019), “Impacts of Digitization on Auditing: A Delphi Study for Germany”, Journal of InternationalAccounting, Auditing and Taxation, 37, pp. 1-17.
  • WEF, (2018), “The Future of Jobs Report 2018”, World Economic Forum, http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf, (Erişim Tarihi: 3 Şubat 2023). https://www.ibm.com/docs/en/spss-statistics/25.0.0?topic=features-reliability-analysis (Erişim Tarihi: 4 Şubat 2023).

The Effect of Artificial Intelligence on Internal Audıtors' Perception: A Research on BIST 100 Companies

Year 2023, Issue: 98, 21 - 42, 17.04.2023
https://doi.org/10.25095/mufad.1259939

Abstract

In this study, it is aimed to reveal the artificial intelligence-oriented internal audit culture, whether artificial intelligence is taken into account by internal auditors and the effect of artificial intelligence on the perception of internal auditors. For this purpose, a questionnaire was sent to the companies included in the Borsa Istanbul 100 Index via Microsoft Form. Internal auditors of 67 companies included in the Borsa Istanbul 100 Index participated in the research. Data obtained from the survey with the help of SPSS 22.0 program; were analyzed using the Kruskal-Wallis and Mann-Whitney U tests, along with descriptive statistics such as percentage and frequency. As a result of the research, it has been determined that artificial intelligence tools should be used in internal audit and artificial intelligence affects the perceptions of internal auditors on various issues such as responsibility, career planning, motivation, quality, performance and efficiency. In addition, it was determined that there is a statistically significant difference between the working time of the internal auditors in the same position and the usability of artificial intelligence.

References

  • Albawwata, I. - Al Frijata, Y. (2021), “An Analysis of Auditors’ Perceptions Towards Artificial Intelligence and Its Contribution to Audit Quality”, Accounting, pp. 755-762.
  • Al-Sayyed, S. - Shaher, F. - Lena, M. (2021), “The Effect of Artificial Intelligence Technologies on Audit Evidence”, Accounting, pp. 281-288.
  • Alina, C. - Cerasela, S. (2018), “Internal Audit Role in Artificial Intelligence”, University Annals, Economic Sciences Series XVII (1).
  • Baldwin, A. - Brown, C. - Trinkle, B. (2006), “Opportunities for Artificial Intelligence Development in The Accounting Domain: The Case for Auditing”, Intelligent Systems in Accounting, Finance and Management, 14, pp. 77-86.
  • Bringsjord, S. - Govindarajulu, N. (2018), “Artificial Intelligence”, The Stanford Encyclopedia of Philosophy, https://plato.stanford.edu/entries/artificial-intelligence/#HistAI, (Erişim Tarihi: 12 Ocak 2023).
  • Chassignol, Maud - Aleksandr, Khoroshavin - Alexandra, Klimova - Anna, Bilyatdinova (2018), “Artificial Intelligence Trends in Education: A Narrative Overview”, Procedia Computer Science, 136, pp. 16-24.
  • Commerford, B. - Dennis, S. - Joe, J. - Ulla, W. (2021). “Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence”, Journal of Accounting Research, 60 (1), pp. 171-201.
  • Corea, F. (2018), “AI Knowledge Map: How to Classify AI Technologies”, Forbes, https://www.forbes.com/sites/cognitiveworld/2018/08/22/ai-knowledge-map-how-to-classify-ai-technologies/, (Erişim Tarihi: 2 Şubat 2023).
  • Efe, A. - Tunçbilek, M. (2023), “Yapay Zekâ Algoritmaları ile Dönüşen Denetim Araçları Üzerine Bir Değerlendirme”, Denetişim, 27, ss. 72-102.
  • Faggella, D. (2020), “AI in The Accounting Big Four-Comparing Deloitte, PwC, KPMG, and EY”, https://emerj.com/ai-sector-overviews/ai-in-the-accounting-bigfour-comparing-deloitte-pwc-kpmg-and-ey/, (Erişim Tarihi: 9 Ocak 2023).
  • Gentner, Daniel – Birgit, Stelzer – Bujar, Ramosaj – Leo, Brecht (2018), “Strategic Foresight of Future B2b Customer Opportunities Through Machine Learning”, Technology Innovation Management Review, 8, pp. 5-17.
  • Gopalan, Puthukulam – Anitha, Ravikumar – Ravi, S. – Krishna, M. (2021), “Auditors' Perception on the Impact of Artificial Intelligence on Professional Skepticism and Judgment in Oman”, Universal Journal of Accounting and Finance, 9 (5), pp. 1184-1190.
  • Gusai, O. P. (2019), “Robot Human Interaction: Role of Artificial Intelligence in Accounting and Auditing”, Indian Journal of Accounting, 51(1), pp. 59-62.
  • Hongdan, Han - Radha, K. - Robin, Jarvis - Chima, M. - David, Botchie (2022), “Accounting and Auditing with Blockchain Technology and Artificial Intelligence: A Literature Review”, International Journal of AccountingInformation Systems, 48, pp. 1-16.
  • Huang, F. - Vasarhelyi, M. (2019), “Applying Robotic Process Automation (RPA) in Auditing: A Framework”, International Journal of Accounting Information Systems, 35, pp. 1-11.
  • Khamis, Abdullah (2021), “The Impact of Artificial Intelligence in Auditing and Accounting Decision Making”, https://www.researchgate.net/publication/352166419_The_Impact_ of_Artificial_Intelligence_inAuditing_and_Accounting_Decision_Making, (Erişim Tarihi: 6 Ocak 2023).
  • Kokina, J. - Davenport, T. (2017), “The Emergence of Artificial Intelligence: How Automation is Changing Auditing”, Journal of Emerging Technologies in Accounting 14(1), pp. 115-122.
  • Köse, E. - Apalı, A. - Aldemir, M. (2022), “Denetçilerin Yapay Zekâya Yönelik Algılarının Denetim Kalitesine Etkisi Üzerine Bir Araştırma”, Denetişim, pp. 32-44.
  • Law, K. - Shen, M. (2020), “How Does Artificial Intelligence Shape the Audit Industry?”, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3718343, (Erişim Tarihi:20 Ocak 2023).
  • McKinsey Global Institute, (2017), “Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation”, https://www.mckinsey.com/∼/media/McKinsey/Featured%20Insights /Future%20of%20Organizations/What%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Repo rt-December-6-2017.ashx, (Erişim Tarihi:16 Şubat 2023).
  • Moffitt, Kevin - Andrea, Rozario - Vasarhelyi, M. (2018), “Robotic Process Automation for Auditing”, Journal of Emerging Technologies in Accounting, 15, pp. 1-10.
  • Noordin, Azima - Khaled, Hussainey – Ahmad, Faisal (2022), “The Use of Artificial Intelligence and Audit Quality: An Analysis from the Perspectives of External Auditors in the UAE”, Journal of Risk and Financial Management, 15(339), pp. 1-14.
  • Nwakaego, Duru – Okpe, Ikechukwu (2015), “The Effect of Accounts Payable Ratio on The Financial Performance of Food and Beverages Manufacturing Companies in Nigeria”, Journal of Research in Business and Management, 3, pp. 15-21.
  • Özçetin, N. (2022), “Muhasebe Denetiminde Yapay Zekâ”, Uşak Üniversitesi Uygulamalı Bilimler Fakültesi Dergisi, 2(1), ss. 29-41.
  • Raschke, R. - Saiewitz, A. - Kachroo, P. - Lennard, J. (2018), “AI Enhanced Audit Inquiry: A Research Note”, Journal of Emerging Technologies in Accounting, 15(2), pp. 111-116.
  • Russell, S. - Norvig, P. (2010), “Artificial Intelligence - A Modern Approach”, Prentice-Hall. Schulenberg, Jennifer (2007), “Analysing Police Decision-Making: Assessing The Application of A Mixed-Method/Mixed-Model Research Design”, International Journal of Social Research Methodology, 10, pp. 99-119.
  • Sun, T. (2019), “Applying Deep Learning to Audit Procedures: An Illustrative Framework”, Accounting Horizons, 33(3), pp. 89-109.
  • Schwab, K. - Davis, N. - Nadella, S. (2018), “Shaping The Fourth Industrial Revolution”, World Economic Forum, https://jmss.vic.edu.au/wp-content/uploads/2021/06/The_Fourth_In dustrial_Revolution.pdf, (Erişim Tarihi: 10 Ocak 2023).
  • Tiberius, V. - Hirth, S. (2019), “Impacts of Digitization on Auditing: A Delphi Study for Germany”, Journal of InternationalAccounting, Auditing and Taxation, 37, pp. 1-17.
  • WEF, (2018), “The Future of Jobs Report 2018”, World Economic Forum, http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf, (Erişim Tarihi: 3 Şubat 2023). https://www.ibm.com/docs/en/spss-statistics/25.0.0?topic=features-reliability-analysis (Erişim Tarihi: 4 Şubat 2023).
There are 30 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Hüseyin Özyiğit 0000-0002-0632-7931

Publication Date April 17, 2023
Submission Date March 3, 2023
Published in Issue Year 2023 Issue: 98

Cite

APA Özyiğit, H. (2023). YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA. Muhasebe Ve Finansman Dergisi(98), 21-42. https://doi.org/10.25095/mufad.1259939
AMA Özyiğit H. YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA. Muhasebe ve Finansman Dergisi. April 2023;(98):21-42. doi:10.25095/mufad.1259939
Chicago Özyiğit, Hüseyin. “YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA”. Muhasebe Ve Finansman Dergisi, no. 98 (April 2023): 21-42. https://doi.org/10.25095/mufad.1259939.
EndNote Özyiğit H (April 1, 2023) YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA. Muhasebe ve Finansman Dergisi 98 21–42.
IEEE H. Özyiğit, “YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA”, Muhasebe ve Finansman Dergisi, no. 98, pp. 21–42, April 2023, doi: 10.25095/mufad.1259939.
ISNAD Özyiğit, Hüseyin. “YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA”. Muhasebe ve Finansman Dergisi 98 (April 2023), 21-42. https://doi.org/10.25095/mufad.1259939.
JAMA Özyiğit H. YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA. Muhasebe ve Finansman Dergisi. 2023;:21–42.
MLA Özyiğit, Hüseyin. “YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA”. Muhasebe Ve Finansman Dergisi, no. 98, 2023, pp. 21-42, doi:10.25095/mufad.1259939.
Vancouver Özyiğit H. YAPAY ZEKÂNIN İÇ DENETÇİLERİN ALGISINA ETKİSİ: BIST 100 ŞİRKETLERİNE YÖNELİK BİR ARAŞTIRMA. Muhasebe ve Finansman Dergisi. 2023(98):21-42.