By: Seth Duda, Director of R&D for SquareWorks Automate
Elevate your financial processes – and meet a C-suite top priority – by implementing these four AI use cases.
The adoption of AI and generative AI has moved slower among finance teams than in other business areas, but that doesn’t mean the Office of the CFO doesn’t see value in the innovation. A 2024 study from McKinsey & Company shows that nearly all CFOs believe the technology will create value for the finance function.
Seth Duda, Director of R&D for SquareWorks Automate, has seen firsthand how AI-driven solutions can transform financial processes. With a focus on developing innovative tools for finance teams, Seth emphasizes the importance of building trust in AI outputs while addressing bandwidth challenges to digitize workflows.
In 2025, AI reliance will accelerate in finance. While CFOs weigh rewards against risk and define appropriate use cases, many boards are mandating implementations. Leveraging AI is a top priority for the C-suite because of the growing processing demand on the finance team and the technology’s tremendous upside.
But its challenges are twofold: building trust in the outputs among key stakeholders and finding the bandwidth to digitize financial processes. As Seth notes, overcoming these hurdles can lead to increased efficiency and accuracy for finance teams navigating high demands.
Cultural hesitation
AI is uniquely valuable for quickly extracting and understanding large volumes of unstructured data. It also surpasses human capabilities in data analysis and pattern identification and is adept at helping predict outcomes based on past and current data.
But using bad or poorly trained data, AI can also fabricate results to make those predictions, leading to little understanding of how results were derived or, worse, incorrect or misleading outputs. This is the primary driver behind cultural hesitation surrounding AI. Unexplainable financial calculations and false positives have no place in an organization’s financials. A concentration on improved model training will help close the gap to fabricated results in 2025.
Overworked finance teams
Another contributing factor behind slow automation progress is already demanding workloads for the finance team, according to 70% of CFOs in the McKinsey study. The Institute of Finance & Management (IOFM) 2024 Automation and Technology Benchmarking Report identifies the time required to get the technology working properly as practitioners’ greatest concern over automating processes.
Start with AP
As with any technology implementation, the best way to begin is by selecting a small number of use cases in areas where ROI is high. Within finance, accounts payable is a great place to start. AI algorithms can automate processes, reduce human effort, and improve accuracy. Here are four use cases where AI will elevate your AP team.
1. Invoice entry
Without the latest AI innovations, businesses using manual or legacy Optical Character Recognition (OCR) technology will be left behind. Template-based data extractions can be error-prone and time-consuming, given the endless variations in invoice formats. AI can extract text and the underlying business context with little to no manual effort required with greater accuracy. Learn how SquareWorks Consulting’s AI-enabled invoice scanning can help automate the data extraction process: Invoice AI
2. Invoice matching
Matching invoices to purchase orders and receipts is often handled in spreadsheets outside your ERP system, if not overlooked entirely. A limited ability to automatically ensure invoices haven’t exceeded tolerances compared to purchase orders and receipts invites significant financial risk. Invoice matching (2-way or 3-way matching) ensures higher accuracy and efficiency. AI automates invoice matching against predefined thresholds and analyzes historical matching patterns to identify deviations. Learn how SquareWorks Consulting helps NetSuite users run validations in real-time to identify any variance violations: 3-Way Matching
3. Risk mitigation
Mitigating risk and compliance in invoice management is a top process area that respondents want to improve using AI, according to the 2024 IFOL AP Automation Trends Report (64%). This is second only to the invoice payment authorization process (68%). AI will help identify fraudulent invoicing actions like duplicate, fake or inflated invoices by leveraging your own historical data and vendor profiles. Also read: 3 Ways to Combat Payment Fraud with AP Automation
4. Expense insights and forecasting
AI allows for rapid and dynamic data analysis across internal data stored in your ERP, including invoices and purchase orders. AI will also further optimize user interactions throughout the entire invoicing process, improving your vendor relationships.
AI is a powerful tool for automating financial processes and reducing human effort. As technology advances and model training improves, finance teams will be well served to rely on AI for insights and forecasting to elevate their financial planning in 2025 and beyond.
Whether for process improvement or mining new insights, the SquareWorks Consulting team can help you navigate existing capabilities and new innovations. Get started here.
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