Generative AI in Finance: 5 Use Cases Transforming AP, AR, and Cash Forecasting

CFOs are ramping up AI investment: in a recent survey, 79% plan to increase their AI budgets for 2025, while the rest will maintain spend. It’s no surprise, because 94% of finance leaders say generative AI can strongly benefit at least one area of their finance operations. Finance chiefs are realizing that AI isn’t just hype – it’s already showing real benefits across finance workflows.

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For CFOs and finance managers, the question has shifted from “Should we use AI?” to “Where can AI make the biggest impact?” The answer: pretty much everywhere in your financial operations. Generative AI and machine learning are already streamlining accounts payable (AP) tasks, improving accounts receivable (AR) collections, and bringing more accuracy to cash forecasting. Let’s explore five practical use cases where AI is transforming finance processes today – and see how solutions like Centime are turning these possibilities into reality.

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1. Invoice Processing & Coding

One of the most tedious parts of accounts payable is handling incoming invoices and coding them to the right general ledger (GL) accounts. Traditionally, this meant piles of paper or PDF invoices and hours of manual data entry. Today, AI is changing the game. Modern AP automation tools use a combination of OCR (Optical Character Recognition) and machine learning to extract invoice details and even predict the correct GL codes for each invoice. In other words, the software can read vendor invoices automatically and suggest how to categorize them in your accounting system.

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Automatic data capture: AI-driven OCR scans vendor invoices (PDFs, images, emails) and pulls out key details like supplier name, invoice number, dates, line items, and amounts – no more typing them in by hand.
Smart GL code predictions: Machine learning models, trained on your company’s historical data, learn how you typically code expenses. They can then suggest the appropriate GL account for each line item (for example, identifying an invoice as office supplies vs. software expense) with impressive accuracy.
Faster approvals: With data capture and coding done by AI, invoices can move through approval workflows much quicker. Your team spends less time on data entry and error-correction, and more time on reviewing exceptions or analyzing spending.

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In short, AI is taking the drudgery out of invoice processing. Centime leverages these capabilities to accelerate AP workflows – its platform reads incoming invoices, auto-populates the invoice data, and applies AI-powered coding suggestions for each line. Your AP staff can simply review the AI’s suggestions, make any needed tweaks, and approve. The result is fewer errors (no typos or mis-codings) and a much faster accounts payable process from invoice receipt to payment.

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2. Anomaly & Fraud Detection

When you’re processing thousands of payments and invoices, it’s easy for mistakes or even fraud to slip through if you rely only on human oversight. This is another area where AI shines: anomaly detection in AP. AI models can analyze payment requests and invoice data at scale to flag anything that looks “off” or out of the ordinary.

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For example, a well-trained AP automation system will catch a duplicate invoice – if the same invoice number or amount shows up twice, the AI can alert the team to prevent paying it twice. It can also detect if an invoice amount is significantly higher than usual for a particular vendor, or if an invoice is submitted from an unknown supplier that isn’t in your system (a potential red flag for fraud). Unlike manual reviews that might sample a few transactions, AI reviews all transactions and finds the needle in the haystack within seconds.

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Duplicate payments: AI can cross-check new invoices against those already processed, flagging duplicates or repeated invoice numbers so you don’t accidentally pay the same bill twice.
Unusual patterns: By learning “normal” spending patterns (typical invoice sizes, frequencies, approved vendors), the system can spot anomalies – say, a one-off invoice that is 5× the usual amount, or a rush payment request outside of normal procedures. These outliers get flagged for investigation.
Fraud signals: AI-driven fraud detection looks for combinations of factors that hint at fraud, such as mismatched vendor details, invoices from suspicious domains, or sequential invoice numbers that don’t align with a legitimate vendor’s history. If something looks fishy, the system raises an alert before the payment is processed.

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Centime’s AP platform, for instance, includes real-time fraud monitoring to catch these issues early. It will automatically flag duplicates and suspicious transactions in your payables – giving you a chance to review or stop a payment before it becomes a costly problem. By using AI to watch over your transactions, you significantly reduce the risk of overpayments or fraudulent disbursements, keeping your company’s coffers secure.

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3. Collections & AR Forecasting

On the accounts receivable side, generative AI and predictive analytics are making it easier to collect cash and forecast when that cash will actually hit your bank account. A big challenge for finance teams is determining which customers to chase first and how much cash flow to expect from outstanding invoices in a given period. AI can help by analyzing your customers’ past payment behavior and current receivables data to provide guidance on both fronts.

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Imagine having an AI that combs through years of payment history to find patterns – it might reveal, for example, that Client A consistently pays 15 days late but eventually pays in full, while Client B often needs a reminder email to pay at all. With these insights, the AI can predict which invoices are at risk of being paid late or not at all. It can then prioritize your collections efforts (so your team knows which accounts to call or email first) and project more accurate timing for incoming cash. According to a recent analysis by Forrester, companies are already leveraging AI in this way: AI tools assess at-risk payments and forecast overdue invoice payments, allowing teams to tailor their collection strategies and improve efficiency. In other words, AI helps you focus on the right customers at the right time, rather than using a one-size-fits-all collections approach.

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Collection prioritization: AI-driven AR systems can rank customers by risk and urgency – for example, highlighting a customer with a large overdue balance who hasn’t responded yet, so your team can prioritize reaching out to them. This ensures effort is spent where it’s most likely to improve cash flow.
Payment date predictions: By examining historical trends (e.g. how quickly a particular client usually pays after invoice date, or after a reminder notice), the AI can forecast when each open invoice is likely to be paid. These predictions feed into your cash flow forecasts, giving you a more realistic view of incoming cash.
Dynamic AR forecasting: Instead of a static aging report, AI can produce a rolling AR forecast that updates as new invoices are issued or payments come in. It can say, for instance, “Based on current patterns, expect 80% of Q1 invoices to be paid by end of Q2, with the remainder spilling into Q3,” and adjust those predictions in real time.

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Centime’s AR tools embrace these capabilities to help finance teams stay ahead of receivables. The platform analyzes each customer’s payment habits and flags which invoices might need intervention (such as a friendly reminder or a phone call). It also uses machine learning to improve your AR forecasting accuracy – taking into account those customer behaviors, not just invoice due dates. The result is a clearer picture of your expected cash inflows and a smarter collections worklist for your team. Instead of guessing or relying solely on an aging report, you get data-driven insights into who will pay, when they’ll pay, and where to focus your collection efforts to reduce Days Sales Outstanding (DSO).

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4. Cash Flow Forecasting & Scenario Planning

For CFOs, few things are as critical as cash flow forecasting. Yet traditional forecasting (often done in giant Excel models) is static and labor-intensive, and it struggles to account for rapid changes or multiple what-if scenarios. AI is transforming cash forecasting by making it more dynamic, precise, and responsive. Rather than building a single static forecast and hoping for the best, AI-driven tools continuously integrate data from across your business – AP, AR, payroll, sales pipelines, banking transactions – to update and refine your cash flow projections in real time.

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One big advantage is the ability to run scenario planning with ease. Suppose you want to know the cash impact if a major customer payment is delayed 30 days, or conversely, if you draw on a line of credit next month. In a spreadsheet, you’d manually plug in numbers and maybe maintain separate versions for each scenario. An AI-powered forecasting tool can do this on the fly: you enter the assumptions (or simply ask a chatbot assistant, “what if our Q3 sales are 10% below forecast?”), and the system will instantly show you the projected cash flow under that scenario. You can generate multiple scenarios (best case, worst case, most likely) in seconds and compare them side by side. This not only saves huge amounts of time, but it also lets you proactively evaluate risks and opportunities by seeing how different actions or events might affect your liquidity.

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Real-time updates: AI keeps your cash forecast live. As new data comes in – a big invoice gets paid or a sudden expense hits – an AI-driven model can adjust your cash projections immediately. You always see the latest picture, unlike static models that might be updated only weekly or monthly.
Multi-factor modeling: AI considers patterns and factors humans might miss. It can recognize seasonality (e.g. if your business always sees a revenue dip in February or a surge in December, the AI will factor that in), and it adjusts for trends in payables and receivables. It’s not just a straight-line average; it learns from the nuances of your cash flow history to predict the future more accurately.
Easy scenario analysis: Because the AI model can handle complex calculations instantly, finance teams can stress-test their cash flow under various scenarios without breaking a sweat. Want to know the impact of delaying all non-essential spend by 60 days, or the cash outcome of an optimistic sales growth? You can model it in moments and use those insights to make better decisions (e.g. whether to secure a short-term loan or not).

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Centime’s cash management solution is a great example of this new era of forecasting. It leverages AI to produce a rolling 13-week cash flow forecast that updates continuously, pulling data directly from your general ledger and bank transactions. The system highlights emerging trends (for instance, if expenses are creeping up faster than usual this month) and can automatically adjust forecasts to reflect those changes. Crucially, Centime also makes scenario planning simple – you can create scenarios with a few clicks (like adding a hypothetical loan or simulating a delay in customer payments) and immediately see how your future cash positions change. This dynamic, AI-enhanced approach goes well beyond the old static spreadsheet: it gives CFOs a powerful tool to anticipate problems, explore strategic moves, and ensure there’s enough cash on hand for both the expected and the unexpected.

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5. Chatbots & Assistants

A more recent development – and one that truly highlights the power of generative AI – is the rise of GPT-powered chatbots and assistants for finance teams. Think of these as intelligent virtual colleagues who can help answer questions, retrieve information, or even perform simple tasks via a chat interface. For busy CFOs and finance managers, such assistants can be a game-changer in terms of productivity and responsiveness.

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Consider accounts payable and receivable communications: Vendors often email the AP department with questions like “Has invoice #12345 been paid yet?” or employees ask finance “What’s our travel expense policy?” or “Can I get an updated budget vs. actual report for my department?” Normally, someone has to stop what they’re doing to find that information. A finance AI chatbot can handle many of these inquiries instantly. Using generative AI (like the technology behind ChatGPT), the chatbot can understand the question and pull the relevant data from your systems or knowledge base. It might reply to the vendor, “Invoice 12345 was paid on Aug 15, here’s the reference number,” or tell the employee, “Your company’s travel policy states X, Y, Z,” quoting the policy document. It can even generate on-the-spot reports or summaries – for example, you could ask, “Show me the current AR aging for customers over 90 days” and the assistant could return a quick breakdown.

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Vendor and customer inquiries: An AI assistant can be available 24/7 to answer routine questions from vendors or customers. Instead of back-and-forth emails, the chatbot integrated with your ERP/finance system can instantly provide invoice statuses, payment dates, or account balances when asked.
Employee support: Internally, finance teams can use chatbots to help other employees. Whether it’s providing the latest expense report, explaining a policy, or giving the CFO an update on today’s cash position, a GPT-powered assistant can retrieve and communicate that information in seconds. This reduces the time finance staff spend fielding emails and lets them focus on higher-value work.
Automating workflows via chat: Beyond Q&A, advanced assistants might even initiate simple workflows. For example, an employee could tell the chatbot “record a journal entry for office supplies for $500” or “start a purchase requisition for a new laptop,” and the AI (with proper controls in place) could kick off that process or guide the user through it conversationally.

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Centime is innovating in this space as well. By integrating generative AI into its platform, Centime aims to provide finance teams with a conversational assistant that can handle many of these tasks. Imagine asking the Centime assistant, “How much did we pay Vendor X last quarter?” or “Generate a PDF of our latest cash flow forecast,” and getting an immediate answer or document. This kind of GPT-powered helper can dramatically streamline your finance operations by reducing wait times for information and simplifying interactions with complex systems. It’s like having an extra team member who never sleeps and can instantly tap into your financial data (within the permissions you set, of course).

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In summary, AI in accounts payable, accounts receivable, and cash forecasting is no longer futuristic – it’s practical and delivering value right now. Finance leaders are embracing these tools to work smarter and focus on strategy over manual drudgery. And you don’t have to build these AI capabilities from scratch – solutions like Centime are making them accessible to finance teams today, helping companies automate tedious processes, catch problems early, and plan better for the future.

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Curious how Centime is using AI to streamline your finance operations? Explore our AI-driven features or book a demo today.

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Generative AI in Finance: 5 Use Cases Transforming AP, AR, and Cash Forecasting

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