AI and machine learning have the potential to revolutionize the accounting industry by helping teams move towards a zero-day close. The financial close process is often time-consuming, cumbersome, and prone to errors, putting additional stress on an already overburdened workforce. To combat this, advancements in AI and machine learning can automate and streamline workflows, making data processing faster and more accurate, and reducing the time and effort required to complete the close.
Accounting professionals are increasingly seeking better work-life balance and support for their mental health, as burnout is a serious risk in the industry. According to a report by the Association of Chartered Certified Accountants, 88% of accounting professionals are looking for better work-life balance, and 71% want more help from their workplaces to manage their mental health. As organizations struggle to find and retain finance talent, addressing these concerns becomes crucial.
The good news is that finance executives have shown enthusiasm for embracing AI and machine learning. A recent Gartner survey revealed that 55% of finance executives aim to achieve a touchless financial close by 2025. While the goal of a zero-day close may sound daunting, it is an incremental journey that brings benefits with each process improvement and task automation.
Intelligent automation is a key component in achieving a zero-day close. Modernizing accounting practices without AI and machine learning is simply not feasible. Leaders should focus on areas where time can be saved and efficiencies created, without compromising accuracy. The ultimate goal is to enhance and augment the performance of accounting teams, not replace humans.
There are several use cases for leveraging embedded AI and machine learning technology in the financial close process. One example is streamlining inputs into the system through natural language processing technology. This technology can convert unstructured data, such as emails, invoices, and receipts, into structured data that can be easily processed and analyzed, eliminating the need for manual data entry.
Another use case is the ability of AI and machine learning algorithms to surface anomalies. These algorithms can analyze large volumes of data quickly and precisely, detecting patterns and outliers that may be missed by human analysts. By identifying errors and risks early on, accounting professionals can address them faster, preventing reconciliation headaches during the close.
Furthermore, AI and machine learning models can automate analysis by analyzing historical financial data, trends, and patterns to model potential future outcomes.
While AI and machine learning are gaining attention for their potential to revolutionize accounting, it is important to remember that technology is just one piece of the puzzle. The human element is crucial, as is integrating all the pieces together. The future of accounting may be uncertain, but it is clear that companies need adaptable leaders who can navigate ambiguity and evolve their capabilities as the industry evolves. By embracing AI and machine learning while prioritizing the well-being of their workforce, organizations can move closer to achieving a zero-day close and drive success in the accounting profession.
