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Browsing SMC Projects, Theses and Dissertations by Author "Apondi, A. M."
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- ItemAssessing factors influencing adoption of Artificial Intelligence in audit of public entities in Kenya(Strathmore University, 2024) Apondi, A. M.The current digital era, industrial 4.0 and surge of financial transactions leading to a deluge of data has complicated the work of contemporary auditor rendering traditional auditing methodologies inadequate. This has birthed Artificial Intelligence (AI) with capacity to match the transmuting nature of fraud. As other professions rush to benefit from AI, auditing has lagged behind with low levels among the big four that includes Deloitte, PricewaterhouseCoopers, Ernst & Young and Klynveld Peat Marwick Goerdeler. Key stakeholders such as professional bodies and Supreme Audit Institutions are under pressure to include risk in audit an arduous task for auditors using traditional methodologies compelling exploration of robotic auditors born from AI. However, the desire to espousal remains low with several factors considered as encouraging or stifling the process. The purpose of this study was to assess factors influencing the adoption of AI in audit of public entities in Kenya. The specific objectives were to determine the influence of technological, organizational and environmental factors guided by Technology Organization Environment (TOE) framework and Diffusion of Innovation (DOI) theory. It targeted all the active audit personnel in the Office of Auditor General (OAG) who is the principal government auditor in Kenya. Simple random sampling was used to select 333 auditors to participate in the study with structured questionnaire to collect data. Validity and reliability of the research instrument was ascertained in a trial study. Data was analysed using both the descriptive and inferential statistics riding on Statistical Package of Social Sciences (SPSS). Descriptive statistics included percentages, means and standard deviations, while the inferential included the multinomial logistic regression, spearman rank correlation and factor analysis. Tables and figures were used in data presentation. The results revealed that technological, organizational and environmental factors positively influence the low adoption of AI in audit of public entities in Kenya with odds ratios that are higher than 1. Organizational factors showed a slight edge over technology, which came second with environmental factors scoring least. However, they collectively accounted for 86.170% of factors that influence adoption of AI in audit of public service entities. To overcome the limitation in smart auditing, the study recommends stakeholders to focus on addressing the factors associated with adoption to match the emerging challenges in the wake of torrential flow of transactional data.