The rise of artificial intelligence (AI) and machine learning (ML) is changing how businesses operate across industries. Accounting and finance teams, in particular, are not immune to this transformation.
As AI and ML become integral to these departments, accounting and finance teams must prepare themselves to adapt to these new technologies or risk falling behind. In this blog post, we'll explore some steps that accounting and finance teams can take to prepare themselves for this new era of technology.
Step 1: Evaluate the Current Process Flow
To evaluate the current process flow of accounting and finance teams, it is crucial to identify the areas that are currently manual and require automation. Processes such as order-to-cash reconciliation and revenue recognition are ideal for automation as they typically involve repetitive and time-consuming tasks. With the help of automation tools, these processes can be performed more efficiently and accurately with minimal human intervention.
However, it is important to note that not all processes can be fully automated. Certain tasks within these processes require human input, such as reviewing and approving financial statements. Accounting and finance teams need to identify these tasks and determine the level of human involvement required. This evaluation will help teams streamline their processes, reducing the time and effort required to complete them and increasing the department's overall efficiency.
Step 2: Find Areas to Automate Manual Processes
Once accounting and finance teams have evaluated their current process flow, the next step is identifying areas that can be automated with AI/ML technology. Some of the regions for automation may include, but are not limited to:
- Data entry
- General ledger entries
- Accounts payable/receivable
- Invoice processing
- Tax Preparation
Automating these processes increases overall efficiency and reduces the risk of human error and inconsistency.
Step 3: Review Options in the Market
As accounting and finance teams focus on improving their operational efficiency by adopting automation, they must pay special attention to the options available in the market. Machine learning algorithms have particularly emerged as a popular choice for businesses looking to leverage advanced technologies and streamline their processes. However, it's crucial to identify an AI/ML solution that suits their budget and aligns with their strategic and operational goals.
When evaluating potential vendors, teams must consider reputation, security policies, compliance standards, and scalability factors. Adopting automation and machine learning algorithms can significantly improve cost-efficiency, accuracy, and speed. But to achieve these benefits, businesses must implement reliable and scalable solutions that meet their needs and expectations.
Step 4: Find a Solution That Works Best for the Team and Can Streamline Across Systems
Once accounting and finance teams have identified and vetted AI/ML vendors, the next step is to find a solution that works best for their teams. The AI/ML solution selected must be intuitive, user-friendly, and provide real-time insights and analytics. Also, the AI/ML solution must integrate with current systems and software for seamless functionality.
How Can Blue Onion Help?
Blue Onion connects, syncs, pulls, cleans, matches, and reconciles all your order transaction data from your order systems to payment processors to the final bank payout. Powered by machine learning algorithms, Blue Onion's data engine transforms complex data sets into unified financials that produce auditable journal entries and transaction-level order-to-cash reconciliation details.
Embracing AI/ML in Accounting and Finance
Accounting and finance teams must prepare themselves to adapt to the new AI/ML era. Automating manual processes, implementing an AI/ML solution that best fits their team and aligns with their strategic goals, and monitoring and training the AI/ML system are critical to a successful transition. The AI/ML era is here, and accounting and finance teams that embrace it will benefit from increased productivity, efficiency, and accuracy in their operations.
