AI in ERP-Finance and accounting professionals are under constant pressure from the C-suite to elevate the strategic relevance of their function. At the same time, they are under day-to-day pressure to help their organizations stay ahead of audit and compliance requirements, report on financial results, and manage ongoing accounting activities.
These activities are all critical for business growth. As enterprise resource planning is meant to be both the primary source of truth and technology used to perform these tasks, it can play a critical role in improving the ease and accuracy with which they are completed. Having the right ERP technology can make or break a finance team’s ability to focus on the strategic instead of the tactical.
Unfortunately, many finance departments are still mired in paper-based processes and manual data entry, and often conduct reporting and forecasting using tried-and-true spreadsheets with data aggregated from multiple sources. These outdated approaches consume excess time and resources, complicate what could be simple tasks for finance and accounting, and prevent a business from obtaining a holistic view of its financial health. In a recent survey conducted by Bottomline Technologies and Strategic Treasurer, finance professionals indicated that cash flow forecasting, invoice processing, and payment receipt and reconciliation all remain inefficient, manual financial processes.
This day-to-day reality at work is in painfully sharp contrast to finance professionals’ personal lives, where everything from managing their household finances to shopping online to composing a text message have transformed into more automatic and personalized experiences. This is thanks in large part to artificial intelligence — more specifically, machine learning and natural language processing.
The disparity between professional and personal does not need to exist, because this same technology exists within ERP systems today. Much of the continued reliance by finance and accounting teams on manual processes at work can be attributed to inertia and comfort, versus a lack of options. AI and its offshoots are still intimidating concepts for many people, regardless of their profession. It can be difficult to determine where and how to implement these innovative technologies in practical ways.