Finance Automation in Detail

Advances in software that automates financial management tasks are redefining the role that finance teams play inside companies. With finance automation technology handling previously manual tasks, such as data entry, invoice matching, and reconciliation, finance teams have the bandwidth to focus on strategic, value-added tasks.

With these automation tools, finance teams have more time to focus on analyzing areas such as what drove the past quarter’s revenue and profit and forecasting what the coming quarter looks like, since it takes them less time and effort to close the books and report the results. And AI shows potential to automate many more finance tasks and processes. As CFOs reimagine how the finance department operates, finance automation is a crucial step in creating a more autonomous function that can deliver more accurate results faster and provides greater visibility and understanding of the results—all while reducing costs.

What Is Finance Automation?

Finance automation refers to the use of technology to complete processes that historically have been done manually. It allows for areas with time-consuming, repetitive tasks, such as accounts payable, accounts receivable, and payroll administration, to be automated with little to no need for human intervention. Companies embrace finance automation because it helps lower labor costs and can reduce errors due to manual data entry and calculations. It can also speed up processes, such as the financial close, by automating steps like account reconciliation. Using finance automation to get accurate data into the hands of business leaders sooner can help them to make better decisions around budgets, investments, hiring, cash management, and more.

Key Takeaways:

• Finance automation is the use of technology to take over previously manual, time-consuming tasks in the finance department.
• Technologies facilitating finance automation include ERP software, robotic process automation, artificial intelligence, machine learning, and cloud computing.
• Prime areas for automation include accounts payable, accounts receivable, payroll, and expense management.
• Benefits of finance automation can include error reduction, time and cost savings, increased efficiency, and fraud reduction.
• Advancements in artificial intelligence are driving the capabilities of finance automation forward.

Finance Automation Explained

Finance automation uses advanced technology—such as ERP software, robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML)—to automate time-consuming, manual processes within the finance department. Automating these finance processes encompasses setting up a series of tasks into what is called a workflow, which specifies the predefined steps needed to execute a task—such as paying a bill or checking that sales and inventory levels match. Finance automation software triggers each step in that workflow and executes it out so the entire process can be handled with limited or no human intervention.

The finance function is a prime area for automation because it has a lot of high-volume, repetitive processes, such as data entry, reconciliation, invoicing, and approvals. An example of an automated reconciliation could be a company’s software continually comparing product sales with inventory levels to spot any imbalances, which could suggest theft if inventory levels are lower than sales would dictate. Finance automation technology can handle these manual activities at a faster speed with fewer errors, allowing the finance team to focus on creating value and driving strategy for the organization. In our sales-and-inventory reconciliation example, finance teams could work with operations to root out the cause of any imbalance.

Which Financial Processes Should Be Automated?

When thinking about which financial processes to automate, consider two big factors: What’s the benefit from automating, and how much of the process can be automated. Look for processes where the technology exists to run an entire process, or entire element within a process, with little or no human involvement. That level of automation will deliver on the main benefit measures: lower cost, faster output, and, possibly, greater accuracy. With that criteria in mind, here are six finance workflows ripe for automation with examples of how elements of that workflow can be automated.

Accounts Payable (AP)

1. Invoice capture: Using optical character recognition (OCR) technology, paper invoices can be automatically scanned, read, and converted into digital data, eliminating the need for manual invoice data entry.
   
   
2. Matching and verification: After capturing invoice data, finance automation technology automatically compares and matches invoices against corresponding purchase orders and delivery receipts.
   
   
3. Approval workflow: Based on predefined rules set by the organization, invoices are routed to the relevant personnel or department for approval. Automatic alerts and reminders can also be set up to expedite the approval process.
   
   
4. Payment execution: Once an invoice is approved, the payment is made to the vendor automatically or with minimal human intervention.
   
   
5. Reconciliation and reporting: After payment, an automated reconciliation process is conducted to match payment transactions with bank statements to verify that amounts and beneficiaries align. Financial automation technology in AP can also generate detailed reports on metrics such as spending patterns, vendor performances, and potential cost-saving opportunities.
   
   
6. Cash optimization: Using predictive analytics and ML, companies can automatically compile data from all relevant sources to continuously predict future cash flows. AI can then suggest optimal payment schedules based on those findings to make sure bills are paid on time while still maintaining healthy cash reserves.
   
   

Accounts Receivable

1. Customer outreach: With finance automation, tailored communications can be automatically sent to customers to remind them of upcoming or past due payments.
   
   
2. Invoicing: Invoices are generated automatically and delivered to customers digitally. If VAT or sales tax applies, an automated system will identify the applicable tax rate for each transaction to ensure the correct amount of tax is collected.
   
   
3. Digital payment processing: With a digital payment process, customers have access to a variety of payment options and can establish autorecurring payments. After a company receives payments, an automated system sends payment receipt notices to customers.
   
   
4. AR analysis: AI in finance automation software can help companies use customers’ payment histories to tailor payment discount programs to each supplier, in a process known as dynamic discounting.
   
   

Payroll

1. Data transfer: With connected systems in place, data can automatically be transferred to and from HR, timesheet, and accounting systems.
   
   
2. Tax calculation: The calculations and deposits for federal, state, and local taxes plus all quarterly and annual federal, state, and local tax form filings are automatically calculated.
   
   
3. Benefits deduction: Employee benefits, such as health insurance and retirement plans, are computed and deducted.
   
   
4. Wage calculation: Wages, including situations such as variable hourly wages, bonuses, overtime, holiday pay, paid time off, and retroactive pay are automatically calculated.
   
   
5. Payment scheduling and issuing: Finance automation handles the issuance of employee payments via electronic direct deposits of paychecks.
   
   
6. General ledger posting: General ledger postings for payroll are automatic to keep accounts up to date and in balance.
   
   

Expense Management

1. Receipt capture: Finance automation eliminates the need for manual data entry by using OCR to automatically extract relevant receipt data, such as vendor name, amount, date, and category.
   
   
2. Expense report creation and categorization: Using data from receipts, expense reports are automatically generated and categorized based on predefined rules.
   
   
3. Policy compliance checks: Policy compliance checks are automated with the technology comparing submitted expenses against company spending policies and guidelines. Noncompliant expenses are automatically flagged for further review.
   
   
4. Approval workflows: Automation technology routes expense reports to designated approvers based on predefined rules, such as expense amount or employee hierarchy, and notifies approvers when action is required.
   
   
5. Reimbursement processing: The reimbursement process is automated with tools calculating the approved expenses and reimbursable amounts based on company policies. The system generates reimbursement reports and initiates payments to employees.
   
   
6. Exception management: As machine learning capabilities evolve, expense management systems may be able to make judgments on which expenses need human review and which can be automatically approved. Managers would then only have to approve flagged expense exceptions.
   
   

Financial Planning

1. Data collection and integration: Finance automation technology extracts relevant information from various data sources across the business. It can then clean and process data by identifying errors, inconsistencies, or missing values and notifying finance staff of the areas needing attention.
   
   
2. Data analysis: Machine learning technology can scan data to help uncover correlations, outliers, or exceptions—helping to improve the accuracy of planning and greatly reduce time spent on planning processes and analyzing data.
   
   
3. Reporting and dashboarding: Financial reports, such as income statements, balance sheets, and cash flow statements, are automatically created. It can also generate dynamic dashboards and visualizations that provide real-time insights into key financial metrics for stakeholders.
   
   
4. Budgeting and forecasting: Tedious companywide and departmental budgeting processes are automated. Budget templates can be dynamically populated and updated from a company’s general ledger. Advanced finance automation technologies enable companies to update forecasts in real time as key drivers change; conduct automated variance analyses; quickly incorporate ongoing streams of financial, operational, and third-party data; and use predictive planning capabilities to gauge the impact of potential future outcomes.
   
   
5. Scenario planning: In-depth “what-if” scenarios and models are quickly created to gauge the impact of each decision and are automatically updated based on shifting drivers.
   
   

Purchasing and Procurement

1. Sourcing: Teams can source suppliers through a structured and automated process with a centralized platform to communicate, compare bids, store sourcing-related documents, and evaluate negotiations against savings goals.
   
   
2. Procurement contracts: Finance automation speeds up RFx creation using AI-supported guided authoring and preapproved templates and legal clauses. Built-in collaboration and approval flows speed up contract completion. It can also automatically deliver advance alerts of expiring contracts.
   
   
3. Purchasing: Purchase order creation and workflows for PO routing to approvers are automated. Approval rules are configured to ensure spend compliance, and any exceptions or anomalies are automatically identified.
   
   
4. Procurement analytics: AI automates spend classification and also delivers actionable insights to help companies increase business value. For instance, AI can pinpoint spend patterns to help procurement teams rationalize a company’s supply base and negotiate better pricing; identify changes in supply and buying needs to find the best suppliers for the business; and gain insight into supplier performance against contractual obligations, such as price, service, and delivery performance.
   
   
5. Invoice management: Tasks around the receipt of ordered items, processing invoices, and remitting payments are automated. After a purchase order, receipt, and bill have been entered into the system, financial automation can also perform a three-way match to correlate data on these documents.
   
   
6. Supplier management: Supplier change requests are automatically tracked, routed, and approved to help maintain controls.
   
   

What Technologies Are Used in Finance Automation?

Finance automation depends on software, including ERP applications that manage companies’ core financial data and help them automate manual processes in areas such as billing, procurement, account reconciliation, and financial reporting. At a more foundational level, here are some of the broad technologies used in finance automation.

• Robotic process automation (RPA): RPA is a form of business process automation that uses software bots to automate high-volume, repetitive business tasks. RPA is process-driven, which means it follows rules and processes defined by an end user to mimic human actions. Examples of what RPA can do include extracting and processing structured data from documents, copying and pasting data, opening emails, downloading attachments, and processing transactions in structured digital environments.
• Artificial intelligence (AI) and machine learning (ML): AI and ML technologies are a step up from RPA, making the jump from process-driven to data-driven automation. While process-driven technologies, such as RPA, mimic human action, data-driven tools mimic human thought. AI and ML are guided by data and context, allowing them to use unstructured inputs, apply their own logic, and handle less-rote processes—significantly extending the range of processes that can be automated. Natural language processing (NLP), which enables computers to comprehend, generate, and manipulate human language, falls under the umbrella of AI. AI also encompasses generative AI (GenAI), which can produce various types of content, including text, images, code, audio, music, and videos. Examples of AI and ML capabilities include speech and image recognition, predictive modeling, customized recommendations generation, anomaly detection, pattern recognition, and the extraction of both structured and unstructured data from documents.
• Cloud computing: Cloud computing plays a crucial role in finance automation, decreasing some of the barriers to entry by providing scalable, flexible, cost-effective, and powerful infrastructure and services for organizations. Cloud-based ERP systems let companies access sophisticated finance capabilities, with frequent feature updates and less maintenance requirements. Cloud applications also allow for scalability, accommodating shifting needs and growing businesses. Organizations can tap platforms for infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS), and depending on their needs, to quickly deploy computing capacity; develop custom applications; and tap sophisticated, ready-to-run financial applications. Many cloud computing applications provide powerful data analytics capabilities to drive real-time insights—accessible anywhere, including via smartphones.

Benefits of Finance Automation

CFOs and their teams have a long to-do list—and it just keeps growing. Companies still need their finance teams to complete important tasks, such as processing payments and closing the books, while also taking on more strategic, analytical, and advisory roles. Finance automation can help deliver the efficiency, visibility, and accuracy needed to thrive in this new reality. These are examples of some of the benefits.

• Error reduction: Finance automation helps minimize this risk by automating areas prone to human error, such as data entry and calculations. It can also automate data validation to help ensure the accuracy and quality of data.
• Time and cost savings: With finance teams facing pressure to do more with less, cost and time savings is one of the top benefits of automation. In a 2024 survey by Duke University’s Fuqua School of Business and the Federal Reserve Banks of Richmond and Atlanta, 87% of surveyed CFOs said they were implementing automation for the cost-savings benefits. And, in American Express’ 2023 Amex Trendex: B2B Edition report, 36% of surveyed businesses said payment automation alone was saving their finance team more than 500 hours per year.
• Increased visibility: Finance automation platforms can consolidate financial data from disparate sources into a central repository, allowing for everyone in the organization to have access to the right information, based on their access privileges. They can generate real-time reports, dashboards, and analytics, so finance teams can monitor financial performance, track KPIs, and observe trends with up-to-date information. These tools also maintain comprehensive audit trails that document financial transactions, activities, and changes made within the system, helping organizations to demonstrate adherence to audit standards and internal controls. With real-time access to accurate financial data, insights, and analytics from across the organization, stakeholders can make better-informed decisions.
• Improved efficiency: Automation can drastically accelerate the pace of financial operations, often while improving accuracy. Finance automation allows organizations to raise efficiency and enhance business performance by automating data entry and processing, streamlining workflows, accelerating transaction processing, providing real-time reporting and analytics, reducing error rates, optimizing resource allocation, enforcing compliance, and more.
• Enhanced collaboration: The integration of automation into the finance department can enhance collaboration in multiple ways. With many organizations embracing finance automation through cloud computing platforms, remote and distributed access improves, meaning teams in multiple locations can interact around one shared data source. Centralized information, workflows, data, and communications allow team members to work together more effectively. And, with fewer manual tasks, the finance function has the bandwidth to collaborate on strategic initiatives across different functional areas and departments within the organization.
• Fraud reduction: One of the biggest benefits of finance automation is around fraud reduction—and CFOs are taking note. In an October 2023 report by PYMNTS, 63% of CFOs surveyed reported using some level of specialized automation for fraud prevention in the previous six months. Automated systems can analyze vast amounts of data, detect patterns, and identify suspicious transactions or behaviors much more quickly than humans, making them ideal tools to help organizations proactively detect and prevent fraud. AI shows strong potential for fraud detection, since it can quickly analyze large data sets to spot anomalies and imbalances that might signal a problem.
• Real-time reporting: Traditional, manual processes meant that finance functions required significant turnaround time to generate reports. These reports would be focused on historical insights, which meant that by the time they reached stakeholders the insights would likely be obsolete. The speed and accuracy of finance automation allows for real-time monitoring and reporting of critical financial data, enabling quicker decision-making and proactive course correction.
• Improved risk mitigation: By leveraging finance automation, organizations can enforce compliance by automating compliance checks, validation rules, and approval workflows. The technology maintains comprehensive audit trails and documentation, providing a detailed and chronological record of financial activities. Finance automation systems monitor financial transactions, activities, and anomalies in real time, generating alerts for potential risks or suspicious activities.

Risks of Finance Automation

Finance leaders must address the potential risks as well as benefits that come with finance automation. Failure to appropriately address these risks may result in companies making decisions based on inaccurate data or facing increased compliance risk. Here are some of the key areas to consider when assessing the potential risks.

• Compliance: An automated finance system without the proper controls and safeguards can heighten compliance risk. Automated finance processes rely on accurate and reliable financial data for decision-making and reporting. If there are inaccuracies or errors in the data the technology is given, it could lead to compliance violations or misstatements in financial reporting. Finance automation systems also must comply with regulatory requirements and industry standards governing data privacy, security, and financial transactions. To mitigate compliance risks, organizations should implement a robust compliance management framework that includes policies, procedures, controls, monitoring mechanisms, and regular audits. It’s critical that companies know exactly where and how these technologies are being used in the organization.
• Skills/talent: In a 2023 survey of business executives by Forrester, employee concern about being replaced by automation was one of the top three issues hindering the adoption of finance and accounting task automation. When not managed appropriately, embracing finance automation can scare off some of your top talent. Companies also may need to upskill their workforce as they automate, to help people make the leap from completing rote tasks to doing deeper analytical work. That said, the talent risk of not embracing automation may be larger. The same survey finds more than half of respondents struggling with employee retention due to the high volume of low-value, manual work. To ease employee apprehension around automation, leadership needs to create and communicate a compelling vision where everyone can see their role alongside automation and understand how automation will make their jobs better. Executives need to allocate funding and employee time for finance professionals to gain the skills needed to thrive in an automation-augmented environment.
• Technology: Technology implementation inherently carries some risk. Poorly designed or implemented technology, ineffective integration with existing systems, or the wrong choice of software for the business can kill a finance automation project’s ROI. Performance problems may occur if the company’s IT infrastructure doesn’t have the capacity or scalability to run new finance automation tools. Finance automation systems might not be compatible with the company’s IT infrastructure. It’s critical for organizations to assess their existing IT infrastructure, potential issues, and how best to mitigate them. Successfully adding finance automation may take more than a simple technology add on and instead require a comprehensive reevaluation of existing systems and processes.
• Security: The wrong automation system, or one that is not implemented or managed effectively, can introduce security risks including data breaches, insider threats, and malware and ransomware attacks. Because automation of finance processes tends to involve the handling of sensitive financial data, including customer information, payment details, and transaction records, companies must take the appropriate steps to secure data and follow all applicable privacy regulations. Not all automation systems are created equal, so companies should investigate how each handles data encryption, authentication, authorization, and backup, as well as the security standards and certifications it follows. Internally, companies should implement access controls, audit trails, and training for employees on security risks and responsibilities that come with automated finance processes.
• Skills gaps and training: The rapid advancement of automation has changed the skills needed in finance, so finance leaders are seeking to build a workforce with knowledge of the technology and how to work effectively alongside it. Research indicates many organizations are falling short. In a 2024 report by Pluralsight, 95% of surveyed executives believed AI initiatives would fail without staff who could effectively use these tools. Yet, a 2023 survey by the Boston Consulting Group found that, while 86% of workers believed they would need training in AI and automation, only 14% reported receiving any training to date. Without closing the skills gap, the full ROI of finance automation is unlikely to be realized.
• Legacy systems: Difficulty integrating new technology with legacy systems was cited as one of the top issues hindering the adoption of finance automation, according to the Forrester survey. Legacy systems pose significant challenges to finance automation initiatives due to their outdated technology, complexity, and limitations. Obsolete systems lack modern application programming interfaces (APIs) and integration capabilities, making it difficult—if not impossible—to connect with newer automation software. Since legacy systems don’t integrate, they create data silos and inconsistencies, which cause issues in the extraction, aggregation, and normalization of data for automation purposes. They also likely lack the scalability and performance capabilities required by automation tools and possibly the appropriate security infrastructure. Organizations that attempt to make automation initiatives work in their legacy systems risk high costs, extensive customization, and other obstacles that can hinder or prevent the success of automation efforts.

How to Set Up Financial Automation

Implementing financial automation can be a considerable undertaking—particularly for companies still using legacy systems. To get the most out of their investment, companies should follow a measured, thorough process that evaluates the setup already in place, identifies the resources required to update it, and details an implementation strategy. Even after implementation, companies will need to monitor, iterate, and improve upon automated processes to ensure everything is working as expected. Here’s a high-level roadmap to get you started.

1. Assess current processes: Evaluate your existing finance processes to identify automation opportunities. Not every process is a good candidate for automation, particularly in the initial stages of automation deployment. Prioritize tasks that are repetitive, high-volume, and don’t require a high level of human thought. The outcome of this step is a comprehensive, prioritized list of what you want to automate in your organization.
   
   
2. Evaluate existing setup: Analyze the systems the company already has in place. Do you struggle with data silos or disconnected business processes? Are your systems integrated? Because finance automation relies on connected systems with reliable data, your organization may need to make changes to ensure the solution has a strong foundation on which to operate.
   
   
3. Select automation tools: Research and select the automation tools that meet your organization’s needs, requirements, and budget. Important things to consider when evaluating solutions are functionality, scalability, security, ease-of-use, integration capabilities, and vendor reputation. Can the solution integrate with your current system? Does it meet the needs you outlined in earlier steps? Will it give your company room to grow and change—including adding new AI and GenAI capabilities—as it evolves and expands?
   
   
4. Plan implementation strategy: Develop a detailed implementation strategy that outlines the scope, timeline, resources, and milestones. Be sure to define roles and responsibilities for key stakeholders. Designate KPIs that will measure the impact and success of your finance automation initiative.
   
   
5. Set up workflows: Set up workflows by first identifying the tasks that make up the job. Then create the rules and logic that govern how those tasks should be done. The rules and logic are often a series of if-then statements that act like instructions telling the program what actions to take and how to move from one task to the next. For instance, an expense management workflow might consist of the following:
   • An employee submits an expense report.
   • An email is automatically sent to the employee’s manager to notify them of the expense report.
   • Manager approves expense report.
   • Notification sent to the finance team of the approved expense report.
   • Finance approves expense report.
   • Reimbursement is made.
   • Receipt, expense, and report are stored.
     
     
6. Test workflows: Test automation workflows, data integration, and system performance in a controlled environment to ensure automation is working as expected. Gather feedback from users to identify any issues or areas for improvement.
   
   
7. Deploy and monitor: Deploy the automated processes into production and closely monitor their performance, effectiveness, and impact on business operations. Be sure to keep an eye on KPIs and user feedback to assess the success of the automation initiative and make adjustments as needed.
   
   
8. Iterate and improve: Create a culture of continuous improvement around your finance automation initiative. Iterate and improve your processes based on feedback, insights, and lessons learned. Particularly considering the rapid advancement of AI in finance automation, there will always be room for further optimization, innovation, and expansion.
   
   

How to Tell if Finance Automation Is Right for Your Business

Determining organizational readiness for finance automation is multifaceted and involves evaluating several areas. From a foundational level, it’s first important to determine whether your current IT infrastructure can support finance automation and what it would take resourcewise to upgrade if not.

Buy-in from key stakeholders—such as the C-suite, finance teams, and IT departments—around finance automation will be a critical success factor. There is a very real fear of automation replacing jobs, which may result in a culture that’s unreceptive to change. Leaders must invest time and resources into effective change management. They need to show staff how automation will make finance jobs more interesting and rewarding, as well as improve their career prospects.

From a talent perspective, leadership needs to evaluate whether they have the necessary skills, expertise, and resources to implement and manage automation initiatives. As automation fundamentally shifts the nature of work, an upskilling program will prove invaluable to help people move from more manual tasks to higher-level, analytical, and collaborative work.

Finally, from a practical standpoint, there are the critical questions around cost and who will provide the finance automation software. For instance, do the potential costs and benefits of automation align with your organization’s budget and priorities? Can you make a clear business case for investing in ERP systems that support finance automation? Have you found the right technology provider for your organization? Implementing finance automation isn’t a one-off task but rather a long-term transformation initiative. You want to be sure you have the right partner onboard.

Embrace Automation with Oracle

The future of finance is here, and it’s already reshaping the competitive landscape for businesses. Organizations that don’t rethink their finance processes to incorporate advancing technologies face risks, including falling behind competitors, decreased talent attraction and retention, missed insights, inaccurate reporting, and reduced employee productivity. Investing in finance automation has a significant impact on an organization’s ability to make data-centric decisions and keep pace with continuous change in its industry and marketplace.

Oracle Fusion Cloud Enterprise Resource Planning (ERP) and Oracle Fusion Cloud Enterprise Performance Management (EPM) help companies automate and connect financial processes including receivables and payables, cash management, fixed assets, and reporting. AI capabilities in Oracle Fusion Cloud Applications include dynamic discounting to create customized supplier payment plans and cash forecasting to automatically generate weekly forecasts. Oracle Cloud Applications run on Oracle Cloud Infrastructure (OCI), providing a full suite of cloud applications on top of a next-generation cloud infrastructure specifically designed to run them. This unique combination lets organizations deploy powerful traditional and generative AI features embedded within Oracle Fusion Cloud Applications. The end result? Better data to work with and more time for the finance team to focus on putting that data to use.

Finance Automation FAQs

Will finance be fully automated?
Automation’s impact on the finance department is significant, with Accenture estimating that up to 80% of the function’s transactional work could be automated. However, it’s unlikely finance professionals will ever be entirely replaced by automation. The finance profession will still need human involvement to provide human creativity, judgment, emotional intelligence, relationship building, and critical thinking. Automation will handle the manual, repetitive tasks that traditionally took up significant bandwidth, allowing for finance staff to focus on more complex analysis and strategic decision-making.

What is RPA in finance?
RPA, or robotic process automation, uses low-code software bots to handle recurring, time-consuming processes in finance. RPA is ideal for automating rule-based processes with structured data sets in finance that require little or no human decision-making. Some examples include extracting data, filling out forms, and routing approvals.

What is intelligent automation in finance?
Intelligent automation (IA), also known as intelligent process automation, combines several advanced technologies, including RPA, machine learning, natural language processing, and AI to deliver more advanced capabilities than RPA alone. Unlike RPA, which completes tasks by following rules defined by humans in software scripts, IA can adapt and learn from experience. IA can analyze structured and unstructured data, adapt to changing circumstances, and improve performance over time by identifying patterns and making decisions based on past experiences. This allows IA to handle complex, cognitive tasks that require human-like decision-making and problem-solving abilities. For instance, when it comes to invoices, RPA can process invoices that follow predefined rules and templates that consist of structured data in the form of numbers and values. However, IA can interpret and extract data from diverse invoice formats that include unstructured data, learning vendor-specific formats and adapting to deviations.