This study investigates organisational drivers, perceived benefits, and implementation challenges associated with adopting AI in internal auditing (IA) in Australia. By applying the Technology Acceptance Model (TAM) and the Technology-Organisation-Environment (TOE) framework, this research contributes new empirical insights into the emerging landscape of AI use in IA. Drawing on in-depth interviews with professionals from audit firms and corporations, the results revel that AI adoption is mainly motivated by expectations of improved efficiency, productivity and usefulness; client and regulatory pressures; competitive forces; employee behaviours and expectations; cost reductions, and responses to technological advancement. Though Al adoption remains in the early stage, organizations report benefits including improved accuracy and coverage, improved efficiency and quality, enhanced auditor roles, support in addressing labour shortages, bridging experience and knowledge gaps, and improved detection and reduction of risks and fraud. However, adoption is hindered by significant challenges. These includes limitation in accuracy and reliability, risks of over reliance without sufficient staff capability, knowledge gaps, resistance to change, lack of appetite and readiness, security and confidentiality concerns, governance and ethical issues, high costs, environmental impacts (carbon footprint), decentralised control environments, and increasing client expectations. Findings assist process improvements on AI adoption to IAF and facilitate broadening the avenues to sort labour shortage issues in auditing. Overall, the study highlights the need for strong governance and balanced use of AI to complement (not to replace) professional expertise, while contributing to the knowledge on AI use in (internal) audit practices guided by TAM and TOE framework.