Ai has been the buzzword for AP automation for a few years. It is an expected feature of an automation solution, but where is it most powerful in your invoice processing and are you making the most of it?
We used industry insights from companies such as Forrester and checked in with our Customers to see where they reap the most benefits from our AI powered solutions. Listed below are the top 5 processes where Ai powered automation has been a game changer.
1. Data & Document Capture
The days of OCR and low capture rates are long gone. AI-powered automation now uses a combination of agentic AI, machine learning, and large language models (LLMs) to intelligently capture data from invoices and related documents. These technologies work together to extract structured data from unstructured formats—whether it’s a scanned PDF, an email attachment, or a photograph of a paper invoice. Unlike traditional OCR, which relies heavily on templates and formatting rules, AI adapts to a wide variety of layouts and languages, improving accuracy and reducing the need for manual corrections.
One of the key advantages of AI in this area is its ability to understand context. For example, if an invoice lists multiple line items with varying tax rates, AI can accurately associate each tax amount with the correct item, even if the layout is non-standard. It can also distinguish between similar fields like invoice number and PO number based on their position, labels, and historical patterns. This contextual understanding is especially valuable when dealing with international suppliers, where formats and terminology can vary widely.
A global logistics company reported a 90% straight-through processing rate after implementing AI-powered capture, compared to just 60% with their previous OCR-based system. The AI not only extracts the data but also validates it against known vendor records and business rules before posting it to the ERP system. This reduces errors, accelerates processing times, and ensures that invoices are ready for matching and approval without unnecessary delays.
2. Invoice matching
Invoice matching is one of the most time-consuming and error-prone tasks in accounts payable. Traditionally, it required manual cross-referencing of invoices with purchase orders and goods receipts, often leading to delays and discrepancies. AI-powered automation transforms this process by intelligently matching invoices to the correct POs and GRNs, even when data is incomplete or formatted inconsistently. This is achieved through machine learning models trained on historical data, which learn to identify patterns and anomalies, reducing the need for human intervention.
For example, if an invoice arrives with a slightly different vendor name or a missing PO number, AI will flag exceptions and suggest corrective actions, allowing the AP team to focus on resolving only the most complex issues.
Our customers have reported up to a 70% reduction in manual touchpoints for invoice matching since implementing AI-driven solutions. One global manufacturing client shared that their three-way matching process, which previously took days, now completes in minutes with over 95% accuracy. This has freed up their AP team to focus on strategic tasks like vendor relationship management and cash flow optimization.
3. Reporting and dashboarding with Power BI
AI-powered reporting and dashboarding, especially when integrated with tools like Power BI, gives AP teams unprecedented visibility into their processes. Rather than just tracking metrics, AI helps uncover the root causes of inefficiencies by analysing patterns and anomalies in real time. This enables finance leaders to make data-driven decisions that improve performance and reduce delays.
For example, AI reporting can identify recurring bottlenecks such as suppliers consistently submitting invoices with missing or incorrect information. It can also highlight internal issues, such as team members failing to receipt goods in a timely manner, which prevents automatic three-way matching. These insights are visualized in intuitive dashboards, allowing AP managers to quickly pinpoint where intervention is needed.
One of our clients used AI-enhanced Power BI dashboards to uncover that over 30% of their invoice processing delays were due to late goods receipting by a specific department. By addressing this issue with targeted training and process adjustments, they reduced invoice cycle times by 45% within two months. This kind of actionable intelligence turns reporting from a passive activity into a proactive tool for continuous improvement.
4. Fraud management
Fraud detection is a critical area where AI has significantly enhanced the capabilities of accounts payable teams. Traditional rule-based systems often fall short when it comes to identifying complex or evolving fraud schemes. AI, however, uses advanced techniques such as anomaly detection and behavioural analysis to monitor transactions in real time and flag suspicious activity with greater accuracy.
For instance, AI can learn the typical behaviour of each vendor—such as invoice frequency, amounts, and submission patterns—and detect deviations that may indicate fraud. If an invoice is submitted from an unfamiliar bank account or outside of normal business hours, the system can automatically flag it for review. This level of intelligent monitoring helps organizations catch issues early, before they result in financial loss.
5. E-invoicing and tax compliance
E-invoicing and tax compliance are becoming more complex as governments around the world introduce new regulations and digital mandates. AI-powered automation helps organisations stay compliant by automatically validating invoices against local tax rules, formatting requirements, and e-invoicing standards. This ensures that invoices are submitted correctly the first time, avoiding costly rejections and penalties.
For example, in countries with mandatory e-invoicing like Italy or India, AI can ensure that invoices are structured according to government schemas and include all required data fields. It can also validate VAT numbers, calculate tax amounts, and generate audit trails for regulatory reporting. This is particularly useful for multinational companies operating across multiple jurisdictions with varying compliance requirements.
