Why Generative AI Isn’t Enough for Invoice Capture
For businesses aiming to reduce manual workloads and embrace automation, invoice capture is often one of the first areas explored. Traditional paper invoicing can take around 23 days to process, provided there are no issues. When errors are involved, processing times can stretch to as long as 90 days, a delay many businesses can’t afford while waiting on vital cash flow.
At first glance, using generative AI (GenAI) for invoice capture may appear to be the most accessible solution, especially if your team is already familiar with it in other areas of the business. While GenAI can help automate parts of the accounts payable process, it isn’t built specifically for the structured, accuracy-critical nature of financial documents. Not all AI technologies are created equal, and when it comes to invoice processing, generative AI has several key limitations.
In this article, we’ll explore why GenAI is not the best tool for optimising financial workflows and why specialised AI software like Xtracta is more effective for automated invoice scanning.
What Is Generative AI in Invoice Capture?
Generative AI (GenAI), commonly associated with large language models like ChatGPT, is designed to understand and generate human-like language based on patterns learned from massive datasets. In the context of invoice capture, it attempts to automate the reading, extraction, and classification of invoice data, regardless of layout or complexity, by uploading documents and prompting the AI for specific information.
The goal of AI-powered invoicing is to eliminate repetitive tasks in the accounts payable process, such as extracting text, identifying totals, and classifying fields. While GenAI has shown impressive progress in conversational applications and content generation, its capabilities in structured document processing, especially for complex financial data where absolute accuracy is critical, remain limited.
Why Generative AI Invoice Capture Falls Short
The main issue with generative AI invoice capture is that the underlying technology is not designed with the structure and precision required for financial documents. These models are generalists, not specialists, and that’s a problem when accuracy is critical.
Firstly, generative models lack the domain expertise to reliably interpret financial documents across currencies, tax structures, and country-specific compliance rules. They may generate plausible-looking outputs, but without a true understanding of invoice semantics, the risk of incorrect extraction remains high.
Secondly, invoice capture relies on accurately extracting structured fields, such as invoice numbers and dates. Generative AI is inherently probabilistic, making it less reliable for tasks requiring precise interpretation and identification. As a result, businesses often find themselves reviewing or correcting outputs, which undermines the goal of automation. For high-volume documents like invoices, AI hallucinations (where the model generates incorrect or invented information) pose an unacceptable risk.
For repetitive, rule-driven tasks like invoice data capture, an accounting automation solution that doesn’t require double and triple-checking is worth the investment, and that’s where specialised AI models like those of Xtracta come in.
How Xtracta Delivers Smarter Invoice Capture
Xtracta’s AI OCR scanner takes a fundamentally different approach. Rather than relying on a general-purpose language model, Xtracta’s specialised AI engine and models are designed specifically for precise document data extraction.
Trained on thousands of invoice formats, Xtracta’s system delivers high accuracy when extracting key fields such as invoice numbers, supplier names, line items, and tax amounts, even from poorly scanned or unusually formatted documents. It learns continuously from user feedback, eliminating the need for manual setup or template creation. With integrations available for major accounting software, Xtracta fits seamlessly into your workflow, handling the complex processing so your team can focus on higher-value tasks.
Its machine learning engine constantly updates itself, producing refined results as users correct and train the system, even as part of their normal daily task to process documents and fix any mistakes. Xtracta helps organisations process large volumes of invoices in seconds, not hours, minimising human error and improving workflow efficiency.
Choose Specialised AI for Invoice Capture
Generative AI invoice capture may sound like an appealing shortcut to automation, but the reality is that its generalised capabilities aren’t fit for purpose in financial document processing. It lacks the precision, structure, and domain intelligence that businesses need to reliably extract and validate invoice data. Specialised tools like Xtracta are built with this complexity in mind.
By focusing on the specific needs of invoicing workflows, Xtracta’s AI-powered invoicing engine offers superior accuracy, faster processing, and easier integration, resulting in more efficient operations and a better return on investment.
For businesses seeking to optimise their accounts payable process, reduce manual work, and save time, the smarter choice is clear: choose the technology built for the task. Get in touch with an Xtracta expert to get started with automating your invoice processing today.
