In 2023, the United Arab Emirates (UAE) Digital Government Strategy 2025 required government entities and companies to participate in transforming the country into a smart nation. The first phase named “digital transformation” focuses on digitizing all operations. As such, accounting information systems (AISs)—which collect, organize, and report financial data—must evolve in alignment with this vision. This study explores how professionals in the UAE’s government-owned aviation industry view AIS adaptation to meet national digital transformation goals. Data were gathered through semi-structured interviews with 17 AIS experts, each with at least two years of experience in both AIS and digital transitions. The responses were then open-coded into themes centered around the objectives, benefits, challenges, and organizational impacts of AIS transformation. The findings reveal that a variety of new technologies are being used. For example, blockchain is being applied to supply chains to enhance partner traceability. AI is being used to analyze large data sets, automate repetitive tasks, and integrate non-financial data, such as for fair value assessments, to support IFRS compliance. AI is also helping to improve GDPR compliance by identifying data vulnerabilities and triggering automated safeguards. Cloud computing is also being adopted to reduce idle capacity and offer scalable flexibility. Nevertheless, some challenges were noted, such as limited employee competence and resistance to adopting new systems.

Internal audit is a bulwark ensuring the integrity of financial statements, a linchpin for stakeholder trust and informed corporate decision-making. With the proliferation of complex financial transactions, audit teams face mounting challenges in deciphering voluminous transactional data to safeguard financial reporting quality. Machine learning has the potential to identify signifiers of financial reporting quality. Within the Design Science Methodology framework, we apply the Random Forest Classifier technique to metrics such as the error rate to enhance financial reporting. We find that the Random Forest Classifier identifies that certain parameters are critical to error detection, which enhance account receivable accuracy, lower receivable account control risk. This research advances the argument that technologically-enhanced internal audit procedures can play a pivotal role in ensuring that financial reporting mirrors the economic reality of the company.