Tag: Financials

Oracle ERP AI Agents in 26D: Less Processing, More Decision Making

~ K8 Mead ~ 2 Comments

If Release 26D tells us anything, it’s that Oracle’s vision for finance is no longer about giving users better screens. It’s about giving them less work to do in the first place. That might sound like marketing speak, but this quarter’s ERP updates genuinely feel different. Across Payables, Payments, Expenses, Billing, Fixed Assets and Budgetary Control, Oracle continues to move beyond AI assistance and deeper into agent-led execution. In many cases, the software isn’t just helping users do the work. It’s identifying issues, recommending actions and increasingly resolving routine tasks on their behalf. The common theme throughout 26D is simple: finance professionals spend less time chasing transactions and more time focusing on decisions that genuinely need human judgement.

If you’ve read any of my previous AI blogs, you’ll know I keep coming back to Payables. That’s because it’s one of the clearest examples of where agentic AI can deliver measurable business value. Invoice processing is still surprisingly manual in many organisations. Someone uploads an invoice, someone investigates an exception, someone releases a hold, and someone else spends time trying to understand why the same issue keeps appearing month after month. Oracle is steadily removing those touchpoints.

The Payables Agent now supports more of the invoice lifecycle than ever before. Invoice ingestion has been enhanced with broader document support and improved integration options, making it easier to bring invoices into Oracle regardless of the format or source system. For organisations dealing with different supplier standards, languages and document types, that’s a practical improvement that should reduce manual effort from day one.

The feature that stood out most to me, however, is Actionable Insights. Rather than finance teams having to trawl through reports looking for recurring issues, Oracle now highlights patterns automatically. If users are repeatedly overriding exceptions or releasing holds without addressing the root cause, the system identifies the behaviour and recommends corrective action. This is where AI starts becoming genuinely useful. Rather than simply helping users process invoices faster, it helps organisations understand why problems occur in the first place.

Oracle has also expanded automated exception resolution, allowing more invoice import errors to be addressed through predefined resolution paths rather than manual intervention. Combined with enhanced matching controls and business-specific tolerance rules, organisations have more flexibility to reduce unnecessary holds while still maintaining appropriate financial controls.

Another welcome addition is the new Payables Period Close Workspace. Month-end close is often less about processing transactions and more about coordinating people. Teams spend significant time identifying what still needs attention, chasing outstanding items and managing exceptions across multiple reports and spreadsheets. Oracle now brings those activities together into a single workspace that highlights priority actions, identifies high-value exceptions and guides users through the close process. For customers still relying on spreadsheets, email chains and manual status updates during close, this could make a significant difference.

One of the criticisms I’ve had of some early AI assistants is that they often stop at telling users what they should do next. That’s useful, but it’s only half the journey. In 26D, Oracle is starting to close that gap. The Payments Agent can now support activities such as virtual card offers, dynamic discounting and supply chain financing, allowing payment specialists to move from opportunity identification into execution within the same experience.

What I find particularly interesting is Oracle’s focus on working capital optimisation. Rather than treating financing options as separate initiatives, the platform can compare multiple strategies and help users determine which approach is most appropriate for a particular supplier or payment population.

There’s also a practical enhancement that many finance teams will probably value more than the headline AI announcements. When payment processes fail, the agent can now explain the issue in business language and recommend a course of action. Anyone who has spent time trying to decipher technical process logs during a payment run will understand the value of that immediately.

Let’s be honest. Expense management isn’t usually anyone’s favourite process. It’s one of those areas where frustration tends to come from lots of small inefficiencies rather than one major issue. Missing receipts, incomplete itemisation, attendee information, rejected claims and lengthy approval cycles all add up. Oracle is tackling several of those issues in 26D.

The Expenses Agent can now collect missing itemisation and attendee details through email interactions, allowing employees to provide information using natural language rather than navigating back into the application. That may sound like a small change, but anyone involved in expense administration knows that itemised expenses and entertainment claims often generate disproportionate amounts of back-and-forth communication. Capturing that information before the approval process begins should reduce delays and improve approval cycle times.

The new Expenses landing page is another welcome addition. Employees and delegates now have a single view showing reports requiring attention, reports ready for submission, recent payments and other key activities. For delegates managing expenses on behalf of multiple employees, this is particularly useful. Instead of jumping between multiple users and screens, they can manage activity from a single location and quickly identify where action is required. Oracle has already confirmed this will become the default experience in 27B, so now is probably a good time for organisations to start evaluating it.

If there is one release area that genuinely feels different, it’s Billing. The new Billing Operations Workspace isn’t simply another dashboard. It’s built around the idea that agents should continuously perform routine work, while people focus on exceptions and decisions. The workspace covers project billing readiness, invoice generation and dispute resolution.

On the project billing side, the agent monitors overdue approvals, sends reminders and escalations according to defined procedures and identifies billing issues before they become month-end surprises. It can even update existing draft invoices when held transactions are released, eliminating manual rework that many project accounting teams know all too well.

For invoice generation and delivery, the agent handles qualifying activities automatically and surfaces only those situations requiring human review. Dispute management follows a similar pattern. Customer billing queries received by email can be converted into disputes, assessed by the agent and, where appropriate, resolved automatically or routed for review with supporting evidence. This is probably one of the strongest examples in 26D of Oracle’s broader vision for agent-led business processes.

Fixed Assets rarely gets the same attention as Payables, Procurement or Financials, but Oracle has introduced several genuinely useful assistants in this area. New capabilities support asset additions, depreciation forecasting, acquisition cost analysis and capital expenditure planning. What’s interesting is that Oracle hasn’t focused on flashy demonstrations here. Instead, the emphasis is on reducing spreadsheet dependency.

The Asset Additions Assistant helps users create assets through a guided conversational experience. The Depreciation Projection Assistant provides on-demand forecasting from live data. Additional tools analyse acquisition costs and support capital expenditure planning activities. None of these capabilities are likely to dominate conversations, but they address real activities that finance teams perform every month. In my experience, that’s often where the biggest productivity gains come from.

The Budget Adjustment Assistant first appeared in 26C, but Oracle has continued to build on it in 26D. The most significant enhancement is policy validation. Budget transfers can now be validated against organisational policies before they enter the approval process, helping prevent invalid adjustments from progressing and creating unnecessary rework.

When validation issues are identified, the assistant explains the issue in plain language and provides guidance on how to resolve it. The approval process and audit trail are managed as part of the overall workflow. It’s worth noting that this enhanced capability is currently available through a controlled release, so customers interested in evaluating it will need to engage Oracle Support.

When Oracle first started talking about AI agents, I think many customers wondered whether they would be genuinely useful or simply another layer on top of existing processes. Release 26D provides some of the clearest evidence yet that Oracle is serious about changing how finance work gets done.

What stands out isn’t any single feature. It’s the number of areas where Oracle is systematically removing repetitive effort. Whether that’s invoice exceptions, payment investigations, expense administration, billing disputes, fixed asset analysis or budget adjustments, the goal is increasingly the same: let the system handle routine work and focus human attention where it adds the most value.

We’re still some distance away from a fully autonomous finance function, and frankly I don’t think most organisations would want that anyway. But we are moving closer to a world where finance professionals spend less time moving transactions between stages and more time applying judgement, managing risk and supporting the business. For me, that’s where the real value of AI sits. Not replacing finance teams, but helping them spend more time doing the work only they can do.

Oracle regularly introduces additional functionality throughout the quarter, so it’s worth keeping an eye on the What’s New documentation as Release 26D progresses. If any significant new ERP capabilities appear, I’ll be sure to cover them in a future update.

Please note all screenshots are the property of Oracle and are used in accordance with Oracle’s Copyright Guidelines.

Oracle Payables Agent: The Licensing and Security Questions Everyone Is Asking

~ K8 Mead ~ Leave a comment

When Oracle talks about the future of touchless Accounts Payable, most of the attention naturally goes to AI-powered invoice processing, anomaly detection and automation. What I’m finding in customer conversations, though, is that the first questions are rarely about functionality. They’re usually much more practical.

Is Payables Agent included in my existing licence? Do I need additional subscriptions for Document IO? Will this consume AI Units? How do I secure it? And how will all of this fit alongside the Agentic Apps Oracle keeps talking about?

The answers aren’t always obvious, particularly now that Oracle has introduced Document IO, Compliance and Control, new Redwood experiences and an expanding portfolio of AI services. In this article, I’ll walk through the areas that seem to generate the most confusion and explain what customers should understand before they start implementing Payables Agent.

One of the biggest misconceptions is that Payables Agent is somehow the same thing as Oracle’s broader Agentic AI strategy. It isn’t. Payables Agent is focused on invoice processing. Its purpose is to extract information from invoices, identify exceptions, apply controls and help AP teams move towards exception-based processing. The Agentic Apps Oracle has been demonstrating are designed to tackle a different problem, helping users make decisions and drive business outcomes rather than simply automating transaction processing.

That distinction matters because customers are often concerned that adopting Payables Agent today could mean investing in something that will soon be replaced. Oracle’s messaging has been fairly consistent here. Payables Agent remains part of the Fusion roadmap and sits alongside, rather than underneath, the broader Agentic Apps strategy.

The second area that causes confusion is Document IO. For organisations using invoice imaging, Document IO is now the default invoice recognition engine. The functionality itself is straightforward enough, but the licensing position is something worth validating before implementation begins.

I’ve already seen customers assume that because Payables Agent is part of their Fusion estate, everything associated with invoice recognition must be included too. That isn’t necessarily the case. Depending on your commercial arrangement and the services you’re using, additional subscriptions may be required for document recognition and imaging workloads.

My advice is simple: don’t leave this conversation until go-live. Confirm your position early, particularly if PDF invoice processing forms a significant part of your AP operation. It’s much easier to address licensing questions during design than during deployment.

Whenever Oracle introduces a new AI capability, the next question is almost always about consumption and cost. The good news is that Payables Agent isn’t currently positioned as a major AI Unit consumer. Document IO and invoice processing use Oracle’s basic AI capabilities rather than the enhanced models that drive some of Oracle’s more advanced AI services.

That’s reassuring for customers who are trying to understand and manage AI Unit consumption across multiple Fusion modules. However, Oracle’s licensing documentation continues to evolve, so it remains important to validate assumptions against the current service descriptions rather than relying on historic guidance.

The most successful implementations I’ve seen tend to treat security as a design activity rather than a technical task completed at the end of a project. Payables Agent introduces new capabilities around document training, compliance configuration, exception management and operational monitoring. Not every user should have access to all of those functions.

For example, the people responsible for training document extraction models may not be the same people who maintain compliance policies. Similarly, those investigating invoice exceptions may not need access to the controls that govern how anomalies are detected in the first place. Oracle’s newer Redwood experience and consolidated duty roles make this easier than it has been in previous releases, but organisations still need to think carefully about who should own each responsibility.

What I find particularly interesting is that AI governance often becomes more important than technical configuration. Giving someone access to train extraction models sounds relatively harmless until you realise they’re influencing how future invoices will be interpreted. Allowing users to modify compliance policies sounds straightforward until those policies begin driving accounting decisions, tax determinations or project coding.

As organisations adopt more AI-enabled functionality within Fusion, governance becomes increasingly important. Who approves changes? Who reviews model performance? Who monitors recognition accuracy? And who is accountable when exceptions occur? Those questions are often more difficult than the technical implementation itself.

Another reason to get security right now is that Payables Agent is unlikely to be the final stop on Oracle’s AI journey. As Agentic Apps become available across Fusion, many organisations will find themselves managing multiple AI-enabled services with different responsibilities, different user communities and potentially different control requirements. Building a strong governance model today gives organisations a foundation they can reuse as those additional capabilities arrive.

The technology behind Payables Agent is impressive, but most implementation challenges won’t come from invoice recognition or anomaly detection. They’ll come from licensing assumptions, security design and governance decisions. Customers that take the time to understand those areas early tend to have a smoother implementation experience and a clearer path towards the touchless AP model Oracle is aiming for.

If you’re planning a Payables Agent implementation, I would spend as much time understanding the licensing and security model as you do exploring the functionality itself. Both are essential if you want to move from a successful proof of concept to a production-ready solution.

Please note that all screenshots are the property of Oracle and are used in accordance with Oracle’s Copyright Guidelines.

Oracle Payables Agent: Is Touchless AP Finally Becoming Reality?

~ K8 Mead ~ Leave a comment

Most finance teams have heard the promise for years: invoices arrive, the system processes them automatically, and AP teams focus on exceptions rather than data entry. The reality has often been different. Supplier formats vary, invoice data is inconsistent, and teams still spend significant time correcting, validating and chasing issues before invoices can be paid.

Oracle’s latest Payables Agent capabilities feel like a more realistic attempt to solve that problem. What makes this release interesting isn’t a single AI feature. It’s how Oracle has combined document recognition, compliance controls and operational monitoring into a single process.

One of the biggest changes is Oracle’s move from Intelligent Document Recognition (IDR) to Document IO. For customers, the important point isn’t the technology change. It’s the outcome. Oracle can now recognise a broader range of invoice formats, including handwritten invoices, while continuing to benefit from existing IDR learning.

When new supplier formats arrive, users can map fields once and allow future invoices to be processed automatically. Functional teams can manage this themselves without relying on technical development. That has the potential to reduce one of the most common bottlenecks in invoice processing: onboarding new suppliers.

What interested me most wasn’t document recognition. It’s Oracle’s shift towards exception-based processing. Rather than asking AP teams to review every invoice, Oracle is attempting to surface only the transactions that genuinely need attention. That includes duplicate detection, policy validation, account coding checks and anomaly identification before invoices reach the payment stage. For organisations with high invoice volumes, that’s where the real efficiency gains are likely to be found.

One capability that may be overlooked is Compliance and Control. This sits alongside existing Oracle defaulting rules rather than replacing them. It helps fill gaps by completing missing information and continuously assessing invoices against defined policies. The result is fewer manual reviews and more consistent application of controls.

For finance leaders focused on auditability and compliance, this could prove just as valuable as the AI-powered document recognition itself. The success of Payables Agent won’t be determined by how impressive the technology sounds. It will depend on three things:

  • The quality of the document training.
  • How well compliance policies are configured.
  • Whether teams embrace exception-based working practices.

Get those right and AP teams can spend less time entering data and more time resolving issues that genuinely need human judgement.

What Oracle is building here feels less like another AI announcement and more like a practical evolution of Accounts Payable automation. The combination of Document IO, Compliance and Control, and the Payables Operations Workspace gives organisations a clearer path towards touchless invoice processing than we’ve seen before. It’s not completely hands-off, and it still requires thoughtful configuration. But for organisations looking to reduce manual effort while improving control and visibility, there’s plenty here worth exploring.

Please note that all screenshots are the property of Oracle and are used in accordance with Oracle’s Copyright Guidelines.

AI for Managing Cash in Oracle Fusion ERP

~ K8 Mead ~ Leave a comment

Cash management has traditionally relied on a combination of spreadsheets, separate banking platforms and a significant amount of manual effort to build forecasts, manage liquidity and chase overdue payments. Oracle is taking a different approach by embedding AI directly into Oracle Fusion Cloud ERP, helping finance teams make better decisions using the same platform where transactions already exist.

Recent developments across cash forecasting, banking connectivity, payments and collections all point towards a common goal: helping finance and treasury teams spend less time gathering information and more time acting on it. Rather than introducing another standalone tool, Oracle is bringing intelligence directly into day-to-day finance processes.

For many organisations, obtaining an accurate view of future cash position remains a challenge. Forecasting often relies on multiple spreadsheets, assumptions and manual updates, making it difficult to respond quickly when circumstances change.

Oracle’s Predictive Cash Forecasting capability aims to improve visibility by bringing together current cash balances, expected inflows, expected outflows and cash flow projections into a single rolling forecast. Finance and treasury teams can view projected cash positions over future periods, supported by visual cash flow analysis and cash position forecasting.

One particularly useful feature is the ability to compare forecasted and actual cash flows across successive periods. This helps identify variances early, allowing treasury teams to investigate unusual spending patterns or unexpected changes in cash movement before they become larger issues.

The AI capability becomes more apparent through Oracle’s forecasting methods. Organisations can review forecasts generated using different approaches, including machine learning models, statistical forecasting techniques, moving averages and trend-based methods. Rather than relying on a single forecasting model for every scenario, finance teams can select the most appropriate forecasting approach for different periods within the forecast horizon.

This flexibility can help improve forecast accuracy while giving users greater confidence in the forecasts they rely on for decision-making.

Before planning an implementation, it is worth noting that Predictive Cash Forecasting requires Oracle EPM Planning licensing. Organisations should confirm their current licensing position and security roles before including it within their roadmap. Businesses already using the standalone Predictive Cash Forecasting capability within Oracle EPM can continue to do so, as the existing solution remains fully supported.

Banking connectivity has often been an area where finance teams depend on custom integrations, file transfers and manual reconciliation activities. Oracle’s embedded banking strategy seeks to simplify these processes by connecting Oracle Fusion Cloud ERP more directly with participating banking partners.

The capability supports a range of services including virtual card payments, direct banking connectivity, supply chain finance, bank account validation and real-time banking information. Oracle continues to expand its ecosystem of banking partnerships to support these services.

From an operational perspective, embedded banking simplifies several key activities, including bank account setup, receipt processing, bank statement processing, payment execution and balance visibility. Standard support for ISO 20022 payment formats also reduces the effort traditionally associated with formatting payments for different banking providers.

One feature attracting particular attention is supplier bank account validation. During supplier onboarding, bank account details can be validated automatically, helping organisations confirm account ownership and reduce payment risks before transactions are processed. The immediate benefits are clear. Finance teams can reduce failed payments, improve supplier data quality and strengthen controls designed to prevent payment fraud.

Organisations should be aware that bank account validation currently has geographical and banking partner limitations. If this capability forms part of your business case, it is worth discussing current coverage with Oracle before implementation to ensure it aligns with your supplier population and operating regions.

Within Accounts Payable, Oracle’s Payments Agent focuses on helping organisations make better payment decisions while improving processing efficiency. For many finance teams, payment runs are often viewed as an administrative activity. However, payment timing can have a significant impact on working capital, supplier relationships and available discounts.

Oracle’s Payments work area provides visibility of payment proposals, supplier offers and outstanding balances within a single workspace. This makes it easier for AP teams to identify early payment discounts, supplier incentives and rebate opportunities that may otherwise be overlooked.

Additional views allow users to analyse payment information at supplier level, providing insight into balances, payment terms and instalment arrangements. This helps finance teams validate payment recommendations and understand the potential impact of alternative payment decisions. The result is a more informed approach to payment management, where teams can balance cash preservation with supplier engagement and commercial opportunities.

While all of these developments are valuable, the most significant day-to-day impact may come from Oracle’s AI-driven Collections Workspace. Managing collections has traditionally been heavily dependent on individual collector experience. Determining who to contact, which accounts present the highest risk and how best to approach each customer can consume a significant amount of time.

Oracle’s Collections Workspace brings this information together in a prioritised view, helping teams focus on the accounts that require immediate attention. Customers can be ranked based on overdue balances, risk factors, broken payment commitments and unresolved disputes.

The embedded AI assistant provides collectors with account summaries, collection histories and recommended next actions. Rather than spending time researching account details before every customer interaction, collectors can access the information they need in a single workspace.

Perhaps most impressive is the ability to generate suggested call preparation notes based on a customer’s payment history and current account status. This helps collectors enter conversations better prepared and with a clearer understanding of the issues that need to be resolved.

The workspace also supports post-call follow-up activities. By analysing conversation records and account information, Oracle can identify actions that may require attention and help route information to the appropriate teams.

For collections teams, the practical benefit is simple: less time spent preparing for conversations and more time focused on resolving outstanding debt and improving cash collection performance. It is important to note that the Collections Workspace forms part of Oracle’s Agentic Applications strategy and requires the appropriate licence to be enabled.

As with any new capability, success depends on understanding the prerequisites before embarking on an implementation. Predictive Cash Forecasting requires Oracle EPM Planning licensing, whether accessed through Oracle ERP or a standalone EPM environment. Appropriate security roles should also be reviewed early in the project lifecycle. Organisations considering bank account validation should confirm current banking partner support and geographical coverage before building business processes around the capability.

The good news is that these innovations do not require a complete finance transformation programme to begin delivering value. Many organisations can adopt individual capabilities incrementally, allowing them to target specific business challenges while building towards a wider AI-enabled finance strategy.

What stands out across all of these developments is that Oracle is focusing on practical outcomes rather than AI for its own sake. Whether it is improving cash forecasting accuracy, reducing payment risk, identifying supplier discount opportunities or helping collections teams recover debt more effectively, the emphasis is on solving real business problems.

For organisations looking to improve liquidity management, strengthen financial controls and increase efficiency across finance operations, these capabilities are well worth exploring.

Please note all screenshots are the property of Oracle and are used according to their Copyright Guidelines

Oracle ERP Cloud Financials 26C

~ K8 Mead ~ Leave a comment

It’s quarterly release time again, and there are some genuinely strong updates in Financials this quarter. I don’t often cover ERP features, but I did last quarter for the same reason and 26C feels similar. As always, more may follow later in the month, but here’s what’s been announced so far and what’s caught my attention.

There are three Fixed Asset Agents in this release. The new Retirement Request Assistant makes it much easier for asset custodians to initiate and track asset retirements. Using a guided, conversational approach, users can submit requests for assets assigned to them or search for others using identifiers such as serial or tag number. They can capture key details like retirement date and reason, then track progress from submission through to completion. This removes the need for emails and manual coordination, giving users a simple self-service route that speeds things up and improves accountability.

Supporting this, the Retirement Assistant helps finance teams review and process those requests. Fixed asset accountants can manage retirements through the same conversational interface, whether dealing with individual assets, multiple assets or file-based uploads. The assistant guides users through the required steps, validates the data, and highlights failed transactions so they can be corrected and resubmitted without starting again. The result is less manual effort, less rework, and quicker, more controlled processing.

The assistant also improves how exceptions are handled. Finance users can review requests, update key details such as retirement dates or proceeds of sale, and post transactions directly within the same experience. Because everything is handled in one place, there is less need to switch between screens or rekey data, which helps reduce errors. Overall, it creates a smoother end-to-end process while supporting stronger governance as volumes grow.

Alongside this, the Fixed Asset Inquiry Assistant offers a much more intuitive way to access asset information. Users can ask questions in natural language to retrieve details across financials, depreciation and distributions, as well as view current period activity. This makes it easier to understand asset movements, validate transactions and respond to audit queries without relying on multiple reports. Taken together, these assistants represent a clear step forward in usability, helping teams reduce effort while improving visibility and control across the asset lifecycle.

The Budget Adjustment Assistant introduces a more straightforward way for budget office users to manage EPM control budgets. Using natural language, users can create and review budget entries, add or reduce budgets, transfer amounts between accounts or periods, and review balances or previously approved entries. The assistant also flags and helps resolve issues at the point of entry, reducing the likelihood of errors and avoiding rework later.

For organisations, this translates into better efficiency and control. Users no longer need to navigate multiple forms or screens, which speeds up processing and reduces effort. At the same time, built-in validation improves data quality before transactions reach the ledger. The result is faster adjustments, fewer issues, and a more streamlined experience for teams managing complex budgets.

The next two enhancements build on the Expenses Agent introduced previously, extending its conversational, touchless approach into more complex scenarios. Cost allocation now allows users to split expenses across multiple cost centres, projects or tasks directly within the agent. Instead of manually distributing costs across lines, users can simply instruct the agent how to allocate amounts. This improves both accuracy and efficiency, ensuring costs are recorded correctly with far less effort.

Another useful addition is the ability to apply cash advances during expense submission. Employees can select one or more available advances, or choose not to apply them and provide a justification where needed. The agent also handles rejected or withdrawn reports by automatically removing applied advances and notifying the user, helping maintain clarity throughout the process.

Together, these updates strengthen the Expenses Agent by reducing manual intervention and improving financial control. Organisations benefit from more accurate allocations, fewer unapplied advances, and better visibility where advances are not used. Employees benefit from a simpler, more guided process that keeps expense reporting moving and reduces delays across the end-to-end lifecycle.

As always, Oracle may introduce additional ERP Agents later in the month. If anything else stands out, I’ll share a follow-up once the full picture is clearer.

Please note all screenshots are the property of Oracle and are used according to their Copyright Guidelines

Oracle ERP Cloud Financials 26B

~ K8 Mead ~ Leave a comment

Don’t worry, I haven’t abandoned the world of HCM for ERP just yet. My enthusiasm for Oracle AI is very much alive, and with four new AI agents landing in Financials this release, I simply couldn’t ignore it. I’d never claim to be a Financials expert, but I do know how long ERP users have been asking for meaningful AI capabilities, and this release feels like a real response to that demand. Oracle has clearly leaned in, and there’s plenty here worth getting excited about.

The long awaited Ledger Agent brings an intelligent, AI‑powered experience to General Ledger, helping finance teams work more efficiently and proactively. It continuously monitors balances, journals, and transactions using configurable prompts, surfacing clear, contextual insights only when attention is needed. Accountants can ask natural language questions about balances, variances, journals, and process statuses, and receive precise, easy‑to‑understand explanations backed by correlated ledger and subledger data. By combining proactive monitoring, root‑cause insight, and seamless access to related ledger actions in a single guided experience, the Ledger Agent reduces time spent navigating multiple screens or compiling information manually, supports earlier detection and resolution of issues, and helps teams maintain accurate, up‑to‑date financial positions while respecting existing security and access controls.

The Payables Agent delivers a modern, AI‑driven approach to invoice processing, helping organisations move towards a truly touchless Payables experience. It automates invoice ingestion, compliance, and control across multiple sources and formats, using GenAI to reduce manual effort, improve data accuracy, and surface only the exceptions that need attention. With unified capture, automated attribute defaulting, intelligent anomaly detection, and a single, streamlined view for managing invoices, teams gain full visibility and control across the invoice‑to‑pay lifecycle. The result is faster processing, stronger compliance, reduced risk of errors or fraud, and improved supplier satisfaction, allowing Payables to shift from a reactive cost centre to a value‑generating function that supports better financial outcomes.

The Payments Agent introduces a smarter, more strategic approach to supplier payments by helping organisations optimise how and when they pay, rather than simply executing scheduled runs. Using AI‑driven insights and conversational guidance, it supports users across the full payment lifecycle, from evaluating payment options such as dynamic discounting and virtual cards, through creating and managing supplier offers, to executing and monitoring payments securely. By assessing the financial impact of different payment programmes in real time and translating decisions seamlessly into action, the Payments Agent improves cash flow, generates incremental financial benefits, and strengthens operational control. The result is a more proactive, insight‑led Payables function that reduces manual effort, highlights exceptions early, and enables finance teams to focus on working capital optimisation and stronger supplier relationships.

The Expenses Agent simplifies expense reporting by allowing employees to complete and submit expenses entirely through email, using natural language. Employees can forward receipts directly to the agent, which automatically creates the expense and prompts for any missing details, such as justifications, attendee information, or cost centres, via a simple email reply. Once all required information is captured, the expense is ready for submission or can be auto‑submitted in line with company policy. This conversational, email‑based approach reduces manual data entry, minimises errors, and cuts down on back‑and‑forth, accelerating reimbursements while improving compliance and delivering a far more intuitive experience for both employees and finance teams.

To wrap up, this has been my first step into writing about ERP Cloud Financials, and I’ve genuinely enjoyed exploring what Oracle is doing in this space, particularly around AI. I’d really welcome your feedback on this post, whether it’s what resonated, what you’d like to see more of, or where I could go deeper. If there’s interest, I’d be more than happy to write further blogs on Financials and continue sharing my perspective as these capabilities evolve.