Artificial Intelligence and the Evolution of Accounting: Transforming Roles, Skills, and Professional Practices

This research investigates how artificial intelligence is transforming accounting tasks and examines how practitioners adapt in professional environments that now demand strategic thinking, analytical skills, and digital proficiency. The findings indicate that artificial intelligence technologies, particularly robotic process automation and machine learning, are automating repetitive, process-based tasks in accounting, such as data entry, bank reconciliations, and tax calculations. In contrast, accounting professionals are increasingly responsible for higher-value activities, including data analysis, strategic advising, and planning that require advanced digital competencies, communication skills, and ethical judgment. Primary data were collected from a sample of 20 skilled accountants, equally divided between early-career and experienced professionals. The results reveal that the most substantial adoption of artificial intelligence occurs in corporate finance, while audit and public practice sectors have been slower to adopt due to regulatory barriers and resource constraints. The study also highlights a significant skills gap, particularly among senior staff and those in smaller firms, pointing to the urgent need for targeted reskilling initiatives and curricular revisions in accounting education. Concerns about algorithmic bias, data privacy, and transparency remain key barriers to artificial intelligence adoption, underscoring the necessity for comprehensive governance frameworks. Overall, the study concludes that artificial intelligence is redefining accounting roles rather than replacing them, emphasizing the importance of continuous workforce training, industry leadership, and support from educational institutions to meet evolving professional requirements. The research offers practical recommendations for policymakers, educators, and accountancy firms seeking to implement fair and sustainable artificial intelligence integration strategies that optimize the complementary strengths of human expertise and machine capability for improved business outcomes.