The AI Implementation Gap: Policy–Audit Misalignment in the UAE and Egypt

Following the International Auditing and Assurance Standards Board’s (IAASB) findings, artificial intelligence (AI) developments over human governance in the February 2026 Technology Quality Management roundtables outcome statement, this study aims to disclose the disconnect between the policy and practice of external audit functions in AI adoption. The research employs a qualitative multi-method design that compares the narratives of Big Four organizations’ transparency reports and audit practitioners in the United Arab Emirates (UAE) and Egypt. The study’s context was determined by the identified gaps in prior empirical research on the differences between the attitudes of corporate management and auditors towards AI usage in external audits. The lead research question focuses on the distinctions in Big Four strategies and individual auditors’ practices in AI applications. The findings are based on content analysis of the narrative of Big Four organizations’ 2021–2025 transparency reports and thematic analysis (TA) of the semi-structured interviews with the auditors in the UAE and Egypt in 2026. The study discovers that auditor practices are currently disconnected from the strategic level propositions. While corporate reports depict a vision in which AI is regarded as a normal component of audit processes, auditors’ experiences suggest it is limited and token adoption in practice. The authors conclude that governance and transparency issues, regional disparities in implementation, and algorithmic complexity contribute to the difficulties in auditor practices in adopting AI tools. These challenges drive the need to establish policy-practice configurations for the effective implementation of audit technologies based on AI. Akpughe, W. O., & Raphael, A. (2026). The Implementation Gap in Emerging Economies: a Theoretical Analysis of Policy Disconnects. Journal of Economics and Trade, 11(1), 286–301. doi.org Albous, M. R., Al-Jayyousi, O. R., & Stephens, M. (2025). AI Governance in the GCC States: a Comparative Analysis of National AI Strategies. Journal of Artificial Intelligence Research, 82, 2389–2422. doi.org Alkhoudi, S., Shaer, S., & Salem, F. (2025). Bridging the AI Divide: Inclusive Governance, Innovation & Competitiveness in the MENA Region. SSRN Electronic Journal. doi.org Alyani, N. (2018). Diversification and Specialisation in the Gulf’s Digitised Creative Sectors. In A. Mishrif & Y. Al Balushi (Eds.), Economic Diversification in the Gulf Region, Volume II: Comparing Global Challenges (pp. 113–143). Palgrave Macmillan. Andersen Egypt. (2025). English Translation of Law No. 151 of 2020. Andersen.com. eg.andersen.com Badawy, W. (2025). The ethical use and development of artificial intelligence (AI) strategy in Egypt: identifying gaps and recommendations. AI and Ethics, 5(4), 3579–3591. doi.org Baldwin, A. A., Brown, C. E., & Trinkle, B. S. (2006). Opportunities for artificial intelligence development in the accounting domain: the case for auditing. Intelligent Systems in Accounting, Finance and Management, 14(3), 77–86. doi.org Bandi, A., Kongari, B., Naguru, R., Pasnoor, S., & Vilipala, S. V. (2025). The rise of agentic AI: A review of definitions, frameworks, architectures, applications, evaluation metrics, and challenges. Future Internet, 17, 9. doi.org Bekhet, A. K., & Zauszniewski, J. A. (2012). Methodological Triangulation: an Approach to Understanding Data. Nurse Researcher, 20(2), 40–43. doi.org Birhane, A., Steed, R., Ojewale, V., Vecchione, B., & Raji, I. D. (2024). AI auditing: The Broken Bus on the Road to AI Accountability. In arXiv. arxiv.org Bohni Nielsen, S., Mazzeo Rinaldi, F., & Petersson, G. J. (2024). Evaluation in the Era of Artificial Intelligence. Artificial Intelligence and Evaluation, 1–12. doi.org Bose, S., Dey, S. K., & Bhattacharjee, S. (2022). Big Data, Data Analytics and Artificial Intelligence in Accounting: an Overview. In S. Akter & S. F. Wamba (Eds.), Handbook of Big Data Methods (pp. 1–34). Edward Elgar Publishing. ssrn.com Bromley, P., & Powell, W. W. (2012). From Smoke and Mirrors to Walking the Talk: Decoupling in the Contemporary World. Academy of Management Annals, 6(1), 483–530. doi.org Bruno, M., & Skoglund, K. (2024). Analyzing the Themes of Artificial Intelligence as Framed by the Big Four Accounting firms: a Document Analysis [Master’s Thesis]. gupea.ub.gu.se Burrell, J. (2016). How the Machine “thinks”: Understanding Opacity in Machine Learning Algorithms. Big Data & Society, 3(1), 2053951715622512. doi.org Cave, S., & Dihal, K. (2023). Imagining AI: How the World Sees Intelligent Machines. Oxford University Press. books.google.ae Chowdhury, M.F. (2014). Interpretivism in Aiding Our Understanding of the Contemporary Social World. Open Journal of Philosophy, [online] 4(3), pp.432–438. doi:10.4236/ojpp.2014.43047. Creswell, J. W. (2013). Qualitative Inquiry & Research design: Choosing among Five Approaches (3rd ed.). Sage Publications. DeAngelo, L. E. (1981). Auditor Size and Audit Quality. Journal of Accounting and Economics, 3(3), 183–199. doi.org)900021 DeFond, M., & Zhang, J. (2014). A Review of Archival Auditing Research. 2013 Conference Issue, 58(2), 275–326. doi.org Deloitte. (2022). 2021 Transparency Report. In Deloitte. deloitte.com Deloitte. (2023). 2022 Transparency Report. In Deloitte. deloitte.com Deloitte. (2024). 2023 Transparency Report. In Deloitte. deloitte.com Deloitte. (2025a). 2024 Transparency Report. In Deloitte. deloitte.com Deloitte. (2025b). UAE Audit Transparency Report 2025. In Deloitte. deloitte.com Detzen, D., & Gold, A. (2021). The Different Shades of Audit quality: a Review of the Academic Literature. Maandblad Voor Accountancy En Bedrijfseconomie, 95(1/2), 5–15. doi.org DiMaggio, P. J., & Powell, W. W. (1983). The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields. American Sociological Review, 48(2), 147–160. JSTOR. doi.org Ernst & Young [EY]. (2021). Transparency Report 2021. In EY. ey.com Ernst & Young [EY]. (2022). Transparency Report 2022. In EY. ey.com Ernst & Young [EY]. (2023). Transparency Report 2023. In EY. ey.com Ernst & Young [EY]. (2024). Transparency Report 2024. In EY. ey.com Ernst & Young [EY]. (2025). Transparency Report 2025. In EY. ey.com Regulation (EU) 2016/679 (General Data Protection Regulation), (2016). data.europa.eu Finch, W. W., & Butt, M. (2025). Gaps in AI-Compliant Complementary Governance Frameworks’ Suitability (for Low-Capacity Actors), and Structural Asymmetries (in the Compliance Ecosystem)—A Systematic Review. Journal of Cybersecurity and Privacy, 5(4), 101. doi.org Han, H., Shiwakoti , R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. doi.org Hassan, L., ElZeftawy, M., & Mahmoud, A. (2025). Datacenters in the Desert: Feasibility and Sustainability of LLM Inference in the Middle East. ArXiv Preprint. doi.org Herman, L. (2019). Neither takers nor makers: The Big-4 auditing firms as regulatory intermediaries. Accounting History, 25, 3. doi.org Hosseini, S., & Seilani, H. (2025). The Role of Agentic AI in Shaping a Smart future: a Systematic Review. Array, 26, 100399. doi.org Huda, S. N. (2022). Institutional Isomorphism. In A. Farazmand (Ed.), Global Encyclopedia of Public Administration, Public Policy, and Governance (pp. 6759–6765). Springer International Publishing. doi.org International Auditing and Assurance Standards Board [IAASB]. (2026). Technology Quality Management Roundtables: Outcomes and Next Steps. International Federation of Accountants (IFAC). iaasb.org International Monetary Fund [IMF]. (2025, April 22). World Economic Outlook Database - Groups and Aggregates Information. IMF. imf.org Islam, M. A., Somu, S., & Aldaihani, F. M. F. (2025). The Rise of Agentic AI: Synthesis of Current Knowledge and Future Research Agenda. Global Business and Organizational Excellence. doi.org Issa, H., Sun, T., & Vasarhelyi, M. A. (2016). Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1–20. doi.org Klynveld Peat Marwick Goerdeler [KPMG]. (2021). Transparency Report 2021. In KPMG. assets.kpmg.com Klynveld Peat Marwick Goerdeler [KPMG]. (2022). Transparency Report 2022. In KPMG. assets.kpmg.com Klynveld Peat Marwick Goerdeler [KPMG]. (2023). Transparency Report 2023. In KPMG. assets.kpmg.com Klynveld Peat Marwick Goerdeler [KPMG]. (2024). Transparency Report 2024. In KPMG. assets.kpmg.com Klynveld Peat Marwick Goerdeler [KPMG]. (2025). Transparency Report 2025. In KPMG. assets.kpmg.com Kokina, J., Blanchette, S., Davenport, T. H., & Pachamanova, D. (2025). Challenges and Opportunities for Artificial Intelligence in auditing: Evidence from the Field. International Journal of Accounting Information Systems, 56, 100734. doi.org Kokina, J., & Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. doi.org Kosow, H., & Gaßner, R. (2008). Methods of Future and Scenario Analysis: Overview, Assessment, and Selection Criteria (Vol. 39, p. 133). Deutsches Institut für Entwicklungspolitik. nbn-resolving.org Kostova, T., & Roth, K. (2002). Adoption of an Organizational Practice by Subsidiaries of Multinational Corporations: Institutional and Relational Effects. The Academy of Management Journal, 45(1), 215–233. JSTOR. doi.org Kuckartz, U. (2014). Qualitative Text Analysis: A Guide to Methods, Practice & Using Software. SAGE Publications Ltd. doi.org Kvale, S., & Brinkmann, S. (2009). InterViews: Learning the Craft of Qualitative Research interviewing, 2nd ed. In InterViews: Learning the craft of qualitative research interviewing, 2nd ed. (pp. xviii, 354–xviii, 354). Sage Publications, Inc. Leonardi, P. (2011). When Flexible Routines Meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies. MIS Quarterly, 35, 147–167. doi.org Li, Y., & Goel, S. (2025). Bridging IT auditors and AI auditing: Understanding pathways to effective IT audits of AIdriven processes. Advances in Accounting, 69, 100842. doi.org Lim, W. M. (2025). What Is Qualitative Research? An Overview and Guidelines. Australasian Marketing Journal, 33(2), 199–229. doi.org Mayring, P. (2014). Qualitative Content Analysis. Theoretical Foundation, Basic Procedures and Software Solution. Mayring, P. (2019). Qualitative Content Analysis: Demarcation, Varieties, Developments. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 20(3). doi.org Meyer, J. W., & Rowan, B. (1977). Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology, 83(2), 340–363. journals.uchicago.edu Mishrif, A., & Al Balushi, Y. (2018). Economic diversification in the Gulf Region Volume 2 Comparing global challenges. Singapore Palgrave Macmillan. researchgate.net's_Digitised_Creative_Sectors/links/60941c18458515d315ffd2be/Diversification-and-Specialisation-in-the-Gulfs-Digitised-Creative-Sectors.pdf Mitan, J. (2024). Enhancing Audit Quality through Artificial Intelligence: An External Auditing Perspective [Accounting Undergraduate Honors Theses]. scholarworks.uark.edu National Council for Artificial Intelligence [NCAI]. (2025). Egypt National Artificial Intelligence Strategy: Second Edition (2025–2030). National Council for Artificial Intelligence. ai.gov.eg Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic Analysis: Striving to Meet the Trustworthiness Criteria. International Journal of Qualitative Methods, 16(1), 1609406917733847. doi.org Orlikowski, W. J. (2007). Sociomaterial Practices: Exploring Technology at Work. Organization Studies, 28(9), 1435–1448. doi.org Pedrosa, I., Costa, C. J., & Aparicio, M. (2020). Determinants adoption of computer assisted auditing tools (CAATs). Cognition, Technology & Work, 22(3), 565–583. doi.org Powell, K., Fishman, E. K., Chu, L. C., Rowe, S. P., & Crawford, C. K. (2026). Agentic Artificial Intelligence: The Power to Change Medicine and Our World. Journal of the American College of Radiology, 23(2), 306–308. doi.org Power, M. (1997). The Audit society: Rituals of Verification. OUP Oxford. books.google.ae Pressman, J. L., & Wildavsky, A. B. (1973). Implementation: How Great Expectations in Washington Are Dashed in Oakland: Or, Why It’s Amazing That Federal Programs Work at All, This Being a Saga of the Economic Development Administration as Told by Two Sympathetic Observers Who Seek to Build Morals on a Foundation of Ruined Hopes (illustrated, reprint, Vol. 2). University of California Press. books.google.ae PricewaterhouseCoopers [PwC]. (2021). Transparency Report 2021. In PwC. pwc.com PricewaterhouseCoopers [PwC]. (2022). Transparency Report 2022. In PwC. pwc.com PricewaterhouseCoopers [PwC]. (2023). Transparency Report 2023. In PwC. pwc.com PricewaterhouseCoopers [PwC]. (2024). Transparency Report 2024. In PwC. pwc.com PricewaterhouseCoopers [PwC]. (2025). Transparency Report 2025. In PwC. pwc.com Rahman, M. J., Zhu, H., & Yue, L. (2024). Does the Adoption of Artificial Intelligence by Audit Firms and Their Clients Affect Audit Quality and efficiency? Evidence from China. Managerial Auditing Journal, 39(6), 668–699. doi.org Salijeni, G., Samsonova-Taddei, A., & Turley, S. (2021). Understanding How Big Data Technologies Reconfigure the Nature and Organization of Financial Statement Audits: A Sociomaterial Analysis. European Accounting Review, 30. doi.org Saunders, M. N. K., Lewis, P., & Thornhill, A. (2023). Research Methods for Business Students (9th ed.). Pearson Education Limited. Schreier, M. (2012). Qualitative Content Analysis in Practice (First Edition, Vol. 1–0). SAGE Publications Ltd. doi.org Schreyer, M., Gu, H., Moffitt, K., & Vasarhelyi, M. A. (2024). Artificial Intelligence Agentic Auditing. SSRN. ssrn.com Seethamraju, R., & Hecimovic, A. (2022). Adoption of Artificial Intelligence in auditing: an Exploratory Study. Australian Journal of Management, 48(4), 780–800. doi.org Soete, L. (2005). On the Dynamics of Innovation Policy: a Dutch Perspective. In D. G. Peter & H. Schenk (Eds.), Multidisciplinary Economics: The Birth of a New Economics Faculty in the Netherlands (pp. 127–149). Springer US. doi.org Suchman, M. C. (1995). Managing Legitimacy: Strategic and Institutional Approaches. The Academy of Management Review, 20(3), 571–610. JSTOR. doi.org Sutton, S. G., Holt, M., & Arnold, V. (2016). “The Reports of My Death Are Greatly exaggerated”—Artificial Intelligence Research in Accounting. International Journal of Accounting Information Systems, 22, 60–73. doi.org Thottoli, M. M., Ahmed, E. R., & Thomas, K. V. (2022). Emerging technology and auditing practice: analysis for future directions. European Journal of Management Studies, 27(1), 99–119. doi.org Tourangeau, R., & Yan, T. (2007). Sensitive Questions in Surveys. Psychological Bulletin, 133(5), 859–883. doi.org Federal Decree Law No. 45/2021 on the Protection of Personal Data, (2021). ai.gov.ae United Arab Emirates National Program for Artificial Intelligence. (2018). UAE National Strategy for Artificial Intelligence 2031. United Arab Emirates Minister of State for Artificial Intelligence Office. staticcdn.mbzuai.ac.ae van Hulst, M., & Visser, E. L. (2025). Abductive Analysis in Qualitative Research. PAR. Public Administration Review, 85(2), 567–580. doi.org Vitali, S., & Giuliani, M. (2024). Emerging Digital Technologies and Auditing firms: Opportunities and Challenges. International Journal of Accounting Information Systems, 53, 100676. doi.org Weber, M. (1978). Economy and Society: an Outline of Interpretive Sociology (G. Roth & C. Wittich, Eds.; v. 2). University of California Press.