What accounts payable AI actually does for an AP team
Most AP teams have heard the pitch for AI by now. Fewer have a clear picture of which daily tasks it can take off their plate. If you spend your days keying in invoice data, sorting out coding on non-PO invoices, or answering the same supplier emails about payment status, the gap between the hype and your actual workload is real. This ebook from Esker closes that gap with nine practical uses of accounts payable AI, each tied to a specific AP chore you'll recognize.
It's written for AP managers, finance leaders and procure-to-pay professionals who are considering AP automation and want to know where AI earns its place. You won't find abstract promises about transformation. Each use case lays out the problem in plain terms, explains how the technology handles it, and describes what changes for your team once it's in place.
Nine AP workflow automation use cases, from onboarding to payment
The use cases follow the AP process roughly in order. They start before the first invoice arrives, with supplier onboarding, then move through invoice capture, coding, review, payment timing and supplier communication. Along the way you'll see where AI handles the grunt work outright and where it drafts or suggests something for a person to review and confirm. That distinction matters if your team is wary of handing over control.
A few of the areas covered:
- Invoice data extraction from headers, footers and line items, including paper invoices, and how accuracy improves as users correct the system
- Predictive invoice coding for non-PO invoices that need splitting across G/L accounts and cost centers
- Anomaly detection that flags unusual amounts or quantities before an erroneous payment goes out
- Email triage and AI-drafted replies for a crowded shared AP inbox
Other chapters look at building supplier questionnaires, splitting scanned invoice batches, spotting invoices at risk of being paid late, and using a chat-style assistant to pull up invoice status, filtered lists and reports on request. Each chapter closes with a short "what's the big deal" section. These connect the capability to outcomes AP leaders are measured on, such as on-time payments, fewer errors, captured early payment discounts and less burnout from repetitive work. If you need to build a business case for AP automation, those sections give you ready language for it.
The AI behind supplier invoice automation, explained plainly
Before the use cases, the ebook offers a brief primer on the types of AI that matter for business processes, from machine learning and deep learning to generative AI and agentic AI. It's a handy reference when you need to explain to colleagues why "AI" in one product can mean something quite different in another, or why some tasks call for a large language model and others don't.
Examples throughout draw on Esker's own AI platform, with product screenshots, a quote from an AP manager about reduced manual work, and links to short demo videos for several use cases. You get a concrete sense of what each capability looks like on screen, which is far more useful than a feature list when you're picturing it in your own workflow.
The ebook also takes on the questions that surface in nearly every AI evaluation. A closing section covers how customer data is hosted and protected, the company's regulatory standing under the EU AI Act, and its approach to the environmental cost of running large models. If IT, security or compliance will weigh in on your decision, this part gives you a head start on that conversation.
Get the full ebook
AI is already part of many AP departments, and the teams getting value from it are the ones who matched specific tools to specific problems. This ebook helps you do the same, so you can focus on the use cases that will make the biggest difference to your invoice volume, your suppliers and your staff.
Download 9 Actually Helpful Ways to Use AI in Accounts Payable to get all nine use cases with explanations of how each one works, the benefits for your team, the AI primer, product examples with demo links, and Esker's approach to security and responsible AI. Fill out the short form to get your copy.