Consolidated Entity & Multi-Currency Reporting

A 2025 study by MIT Sloan assistant professor Chloe Xie and Stanford University's Jung Ho Choi provides some of the most rigorous evidence of AI's impact on financial close processes. The researchers partnered with an AI-based accounting software provider and analyzed hundreds of thousands of transaction entries from 79 small and midsize firms while surveying 277 accountants. The study found that AI-using accountants support 55% more clients per week compared to non-users, with firms embracing AI able to finalize monthly financial statements almost within two weeks after month-end, whereas others take over a week longer. Experienced accountants leveraged AI more strategically, intervening when confidence scores were low and correcting potential misclassifications, yielding larger performance gains.

In a separate real-world implementation, a technology company's finance team leveraged AI to process compute usage data that had grown too complex for traditional spreadsheet-based workflows, achieving an 80% reduction in manual data processing time and significantly faster financial close periods, according to a 2026 Spendesk analysis. According to a 2025 Bain and Company report, a global consumer products company used traditional machine learning to reduce the time required to prepare a revenue forecast from two weeks to two hours, with accuracy rising to greater than 97%, and is now integrating generative AI to simulate scenarios and generate narrative summaries. These examples illustrate a consistent pattern: organizations that pair AI automation with experienced human oversight achieve the strongest results, while those that over-rely on AI without adequate professional judgment see diminished gains.