If you work as part of a finance team, you understand how time savings can impact the bottom line. Hours saved means you can do more without adding to your headcount. It also means that employees are less stressed and generally happier in their jobs. While it’s tricky to calculate the financial impact of retention, once you think about the resources needed to hire and onboard new employees, it’s a clear advantage to keep good professionals around.
It only makes sense, then, that finance teams are exploring how to use AI to save time and reduce the stress of manual work like creating invoices and POs, maintaining audit trails, and processing expense claims.
But AI should never come with trade-offs in data security or compliance. For example, most AI applications require you to move data to a central location before being able to process it or use it in conjunction with data from other sources. This can cause problems when working with financial information, since as soon as it leaves your ERP or ledger, it’s more at risk for being intercepted. When financial data falls under the Sarbanes-Oxley Act (SOX), General Data Protection Regulation (GDPR), or other data residency laws, it might be subject to regulations that specify where it can be processed. Managing compliance with these regulations can be expensive and time-consuming. One recent survey found that the average cost of an organization’s SOX program increased by 44% over the past two years, with 32% more hours spent.
At Kamiwaza, we created an Intelligent Document Processing (IDP) solution for finance that can process data at the source. It also provides AI orchestration to coordinate data from different sources, facilitating more complex workflows. This way, we can empower finance teams to automate repetitive tasks and save time, without creating data security or compliance issues.
On average, finance teams spend about 3.5 hours a day on repetitive tasks, or nearly half a day. Accounts payable teams may spend a full week each month just processing invoices. Finance professionals are some of the most sought-after talent around, and using their skills for manual work is a waste. According to a recent study, 93% of finance and accounting leaders said they had difficulties securing qualified professionals.
Unfortunately, it also leads to burnout. Somewhere around 74% of finance professionals have thought about quitting their jobs because of the repetitive nature of their work. Skilled professionals should be focusing on intellectually stimulating and high-value activities, like cash flow analysis and forecasting. After all, strategy can set high-performance finance teams apart from the competition and further boost the bottom line.
There’s another problem with relying on humans, even the most skilled ones, for manual tasks: people make mistakes. According to Gartner, 59% of controllers say their teams make several errors per month. Sometimes these mistakes are small and can be corrected easily. But larger mistakes can cause hours of remediation and headaches for the whole team. Even worse, they can hurt client or supplier trust.
Organizations of all sizes are using AI-enabled document automation for finance workflows, especially for accounts payable tasks. Instead of relying on a human to copy data between systems or manually format and send files, AI tools can create new documents from templates, extract data from existing documents, integrate with ERP systems, and request reviews and approvals.
Some common document automation tasks in finance include:
It’s easy to get excited about what AI can do, but it’s important to first ask what you want it to do. Finance teams should work together to define a set of use cases, starting with specific pain points to address. For example, matching invoices to purchase orders or creating new quotes would be a good place to start.
It’s critical to consider how any AI workflows will impact compliance and auditability. A strong document automation solution can help you maintain a clean audit trail and standardized approvals to stay compliant with regulations.
Finally, define how you’ll measure the results of each use case. Can you track the number of hours saved? The increased speed of automated approval workflows? Team satisfaction?
The chart below summarizes some tips for picking the best accounts payable automation software.
|
Feature |
Why it Matters |
|
Local data processing |
By choosing a solution that can process data at the source, finance teams can avoid problems with privacy and data residency compliance. |
|
IDP vs RPA |
Traditional robotic process automation (RPA) works by matching fields. Intelligent document processing (IDP) uses AI and visual models to understand a document’s context, which is especially helpful if you have unstructured data, like PDFs and scanned documents. |
|
Agentic AI |
AI agents can automatically route documents for approvals and review for more streamlined workflows that require less human intervention. |
|
Three-way matching |
Three-way matching automatically checks the information between invoices, purchase orders, and goods receipts, flagging any inconsistencies to help prevent fraud. |
|
Integration |
Accounts payable AI tools should integrate with your ERP, vendor invoice system, and other accounting systems. |
|
Audit trail |
Solutions that can automatically document approvals and other processes can create an audit trail for finance teams. |
|
Scalability |
A decentralized solution can make it easier to scale document automation workflows across large organizations with multiple locations and databases. |
Typical AI solutions start by pulling all data into a centralized location and then processing it. But this can be a problem for finance teams that need to keep data in certain geographic areas, behind firewalls, or within a private cloud.
IDP from Kamiwaza is unique in that it brings processing to the data, instead of the other way around. This eliminates the security risk of data transfer while ensuring regulatory compliance.
We’ve augmented our IDP solution with agentic workflows, which move beyond OCR-based data extraction to automate complex, multi-step processes. As an AI orchestrator, Kamiwaza can connect fragmented systems and provide truly end-to-end solutions that save hours of time for your finance teams.
Kamiwaza’s agentic AI for accounts payable can automate invoice processing, expense reports, and document auditing. Features like precision data extraction and automated three-way matching help prevent errors and potential fraud. Vision models can read the image to understand the layout and placement of data. If information is missing, the agent gathers more data to complete the task or flags it for human review.
Kamiwaza’s accounts payable automation can reduce invoice processing costs to as low as $3–$5 per invoice, and we’ve seen processing time reduced by 87%. Compared to manual data entry, Kamiwaza IDP can reduce error rates by up to 90%.
Kamiwaza IDP also acts as an internal control accelerator, securely capturing data and automating the audit trail. This enforces consistency and provides real-time tracking of financial entries. With role-based access, only the permitted users can make approvals, while other users can view entries.
Another unique feature of our solution is our intelligent data bridge, which connects disparate systems. This is useful in organizations where documents are scattered across hard drives and inboxes. IDP helps ensure data accuracy and completeness across this landscape. We’ve found that our automated data extraction ensures 99% accuracy, giving finance teams reliable data for strategic decision-making.
By orchestrating accounts payable workflows, Kamiwaza helps finance teams move from reactive task management to proactive business support. Learn more about the finance use cases for document automation with local processing and agentic AI.