A new study from Stanford University and MIT Sloan has provided some of the first real-world evidence on how generative artificial intelligence is reshaping the accounting profession. For Maldivian firms exploring digital transformation, the findings highlight both the opportunities and risks of adopting AI in financial management.
Drawing on survey data from 277 accountants and transaction-level field data from 79 small and mid-sized firms, the research documents sharp productivity gains where AI has been introduced into workflows. Accountants using AI-supported tools managed 55 percent more clients per week and shifted around 8.5 percent of their time away from manual data entry towards higher-value work such as client communication and quality assurance.
The benefits also extend to reporting quality. Firms adopting AI-based systems recorded a 12 percent increase in the detail of their ledgers and closed their monthly books an average of 7.5 days faster. For businesses reliant on timely, accurate reporting to satisfy lenders or investors, this could make a meaningful difference.
However, the study also warns of uneven adoption and potential pitfalls. While many accountants see AI as a way to automate repetitive work and improve accuracy, 62 percent expressed concern about errors in AI-generated outputs, alongside worries about data security and the erosion of human judgment. The research suggests that experienced accountants tend to use AI more strategically, stepping in when confidence scores are low, while less experienced staff either rely too heavily on AI or under-utilise its capabilities.
For the Maldives, where finance teams in both corporates and SMEs often operate with lean resources, AI tools could free up valuable time for advisory and compliance work. Yet the findings also reinforce that human oversight remains essential. Generative AI is most effective as an assistant, not a replacement.
As more Maldivian firms experiment with AI-powered solutions in accounting, the lessons from this early evidence are clear: efficiency gains are real, but so are the risks. Success will depend on pairing technology with professional judgment and ensuring strong safeguards around accuracy and data integrity.
