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Journals / Denetim ve Güvence Hizmetleri Dergisi / 2026 / Cilt: 6 Sayı: 2

An AI-Assisted Evidence Evaluation Model for Independent Auditing: A Human-Centered Conceptual Framework

Bağımsız Denetimde Yapay Zekâ Destekli Kanıt Değerlendirme Modeli: İnsan Merkezli Kavramsal Bir Öneri

Zeynep Yaroğlu(ANKARA HACI BAYRAM VELİ ÜNİVERSİTESİ)0000-0003-3713-9092
Pages
243–265
Publication Date
2026-07-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

By positioning AI use within a staged and iterative evidence evaluation process, the study presents a framework in which AI supports rather than replaces professional judgment, while final professional judgment, professional responsibility, and accountability remain with the auditor.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study proposes a Human-Centered Hybrid Evidence Evaluation Model that specifies the conditions under which information processed or generated by artificial intelligence (AI) tools can be used in independent auditing.
📊
Key Findings & Data:The model, which integrates the Turkish Standards on Auditing with socio-technical systems theory, human-centered AI, and hybrid intelligence, consists of four stages: obtaining and preparing data, conducting preliminary analyses and generating risk signals, assessing whether AI-processed or AI-generated information can be used as audit evidence, and evaluating audit evidence as a whole to form the audit opinion.
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Conclusion & Impact:By positioning AI use within a staged and iterative evidence evaluation process, the study presents a framework in which AI supports rather than replaces professional judgment, while final professional judgment, professional responsibility, and accountability remain with the auditor.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zekâ · Denetim Kanıtı · Mesleki Yargı

Abstract

This study proposes a Human-Centered Hybrid Evidence Evaluation Model that specifies the conditions under which information processed or generated by artificial intelligence (AI) tools can be used in independent auditing. The model, which integrates the Turkish Standards on Auditing with socio-technical systems theory, human-centered AI, and hybrid intelligence, consists of four stages: obtaining and preparing data, conducting preliminary analyses and generating risk signals, assessing whether AI-processed or AI-generated information can be used as audit evidence, and evaluating audit evidence as a whole to form the audit opinion. Decision points and feedback mechanisms at the end of each stage allow the auditor to perform additional procedures, return to earlier stages, or discontinue the use of an output. The model requires AI-processed/generated information to be evaluated in terms of relevance, reliability, data integrity, methodological suitability, verifiability, consistency with other evidence, resolution of contradictory evidence, and sufficiency. By positioning AI use within a staged and iterative evidence evaluation process, the study presents a framework in which AI supports rather than replaces professional judgment, while final professional judgment, professional responsibility, and accountability remain with the auditor.

Özet

Bu çalışmada, yapay zekâ (YZ) tabanlı araçlar tarafından işlenen veya üretilen bilgilerin bağımsız denetim sürecinde hangi koşullar altında kullanılabileceğini açıklamak amacıyla; Bağımsız Denetim Standartlarını (BDS) sosyo-teknik sistemler teorisi, insan-merkezli YZ ve hibrit zekâ yaklaşımlarıyla bütünleştiren İnsan-Merkezli Hibrit Kanıt Değerlendirme Modeli önerilmektedir. Geliştirilen model; verinin elde edilmesi ve hazırlanması, ön analiz ve risk sinyallerinin üretilmesi, YZ tarafından işlenen veya üretilen bilgilerin denetim kanıtı niteliğinin değerlendirilmesi ile kanıtların bütüncül değerlendirilerek denetim görüşünün oluşturulması olmak üzere dört basamaktan oluşmaktadır. Her basamak sonunda yer alan karar noktaları ve geri besleme yapısı, denetçinin ilave prosedür uygulamasına, önceki basamaklara dönmesine veya çıktıyı kullanmamasına olanak sağlamaktadır. Model, YZ destekli bilgilerin ihtiyaca uygunluk, güvenilirlik, veri bütünlüğü, metodolojik uygunluk, doğrulanabilirlik, diğer kanıtlarla tutarlılık, çelişkili kanıtların çözümlenmesi ve yeterlilik bakımından değerlendirilmesini gerektirmektedir. Çalışma, YZ kullanımını kademeli ve geri beslemeli bir kanıt değerlendirme süreci içinde konumlandırmakta; nihai mesleki yargı, sorumluluk ve hesap verebilirliğin denetçide kalması gerektiğini ortaya koymaktadır.

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Cite This Article

Yaroğlu, Z. (2026). An AI-Assisted Evidence Evaluation Model for Independent Auditing: A Human-Centered Conceptual Framework. Denetim ve Güvence Hizmetleri Dergisi, Cilt: 6 Sayı: 2, 243–265. https://ajindex.com/articles/1611722

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