In Finance teams, recurring expense reports often require significant time due to manual classification, data review, and validation. By adopting an AI-powered tool, suggestion-division, developed by the Tech team, these repetitive tasks can be streamlined and largely automated. The tool applies AI-driven logic to suggest appropriate budget items for each transaction, reducing the need for manual checking and rework.
A key use case of suggestion-division is in weekly and monthly expense reporting. Previously, preparing and classifying expense data typically took around 60 minutes per week, as each transaction had to be reviewed and mapped manually. After implementing the AI tool, the same process can be completed in a much shorter time, as most expenses are automatically categorized with high accuracy. This results in a time saving of approximately 60 minutes per week, while also improving consistency across reports.
By reducing time spent on repetitive operational tasks, the use of AI allows the team to focus more on higher-value activities, such as cost monitoring, variance analysis, and budget planning. Overall, suggestion-division demonstrates how AI can effectively save time, improve efficiency, and support faster reporting cycles, especially during high-pressure periods such as month-end and budget reviews.