Month: Sep 2026

Oracle Fusion Cloud Payroll 26D: Small Changes, Real Benefits

~ K8 Mead ~ Leave a comment

It’s quarterly release time again, and while Payroll 26D doesn’t contain the sort of headline-grabbing feature that will completely transform how payroll teams work, it does include a collection of enhancements that solve real-world problems. There’s continued progress on Oracle’s Redwood journey, some useful legislative updates for UK and Irish payroll, stronger visibility into tax calculations for US payroll teams, and a handful of practical improvements that should reduce administration effort and simplify troubleshooting.

What stood out to me this quarter is that many of the enhancements focus on making payroll easier to manage rather than simply adding new functionality. Several address common frustrations that payroll teams have been dealing with for years, while others provide much-needed transparency into processes that have traditionally felt like a black box. As always, Oracle may introduce additional features over the coming weeks, but here’s what has caught my attention so far.

One theme that won’t surprise anyone by now is Redwood. Oracle continues to replace classic payroll pages with their modern Redwood equivalents, and 26D brings another significant batch of payroll administration pages across. At this stage, most payroll customers understand that the question is no longer whether Redwood is coming, but when they’re going to adopt it. Releases like 26D continue to chip away at the remaining classic pages and make that transition increasingly inevitable. While not every Redwood page introduces brand new functionality, many do improve usability and create a more consistent experience across HCM Cloud.

The Legal Entity Calculation Card and Legal Reporting Unit Calculation Card have now moved to Redwood. These cards hold payroll statutory unit and tax reporting unit defaults, making them some of the more important configuration pages within Payroll. For customers already using Redwood profile options, the new experience is enabled automatically. Functionally, very little changes, but it continues Oracle’s journey towards a consistent user experience across the application.

The Fast Formula migration is probably the Redwood enhancement that will attract the most attention from payroll specialists. The new page introduces a genuinely modern code editor experience, including syntax highlighting and quicker access to database items and functions. Anyone who spends their day building or troubleshooting formulas will likely find it easier to navigate than the classic version. That said, there is one notable omission. Expression Builder isn’t available in the Redwood experience yet, which may influence how quickly some organisations choose to move over. It’s not a blocker for everyone, but it’s definitely something worth testing before making the switch.

Oracle has also moved a further six payroll setup pages into Redwood: Balance Exceptions, Balance Exceptions and Reports, Element Security Profiles, Features by Country or Territory, Organisation Payment Methods and Run Types. It should be noted that these pages are enabled by default. One point worth highlighting relates to Organisation Payment Methods. If you’ve previously granted access through custom job roles, you’ll need to review those roles and ensure they include both the Organisation Payment Method Management Duty role and the Manage Organisation Payment Method function privilege.

One Redwood enhancement I’m particularly pleased to see is the update to Balance Adjustments. Historically, making multiple balance corrections could be a fairly manual process, particularly when trying to understand the wider impact of those changes. The new experience allows administrators to work with multiple adjustments in a single transaction while immediately seeing the before and after effect across affected balances.

The ability to apply separate costing to individual adjustments and navigate directly from Balance Results into Balance Adjustment creates a much smoother experience than before. It’s the sort of enhancement that won’t generate much excitement in release announcements, but for payroll teams dealing with corrections and reconciliations it could save a significant amount of time.

The Retropay enhancement is another feature that feels small on paper but addresses an issue that has caught a number of organisations out in practice. Where employees are processed through multiple payroll runs within the same period, for example a bonus run followed by the regular payroll run, previous behaviour could sometimes create duplicate retro entries or unnecessary offset adjustments. Those situations could take time to understand and even longer to explain.

The new logic helps Oracle determine whether the entry has already been processed within a later payroll run before generating retrospective adjustments, creating a cleaner and more predictable outcome. This feature is disabled by default and requires the Set Late Recurring Retro Entry Earliest Date process to be run, so customers will want to carefully consider when to enable it.

There are a number of UK-specific enhancements in 26D and, I’ve called out three that address genuine operational scenarios rather than simply introducing administrative changes. The first on is Process Results Enhancements. Anyone who regularly analyses payroll results will appreciate this one. The Run Pension Automatic Enrolment Letters process now displays the employee name and payroll relationship number. Send HMRC XML results show the flow name instead of the payroll action ID, and Pension Assessor Updates include employee details alongside a direct link to the pension component within Earnings and Deductions. These aren’t transformational changes, but they’re exactly the sort of usability improvements that reduce investigation time when payroll teams are trying to locate information quickly.

This Enhanced Statutory Parental Bereavement Leave and Pay for Northern Ireland Employees enhancement delivers support for legislative changes effective from 6 April 2026. Oracle now supports the expanded eligibility requirements for Northern Ireland employees, including miscarriage-related absences and day-one eligibility. The system also records and reports qualifying payments separately from existing statutory parental bereavement pay arrangements. The enhancement is automatically enabled and requires no customer action.

The next one is the Use Published Schedules to Determine UK Statutory Sick Pay Qualifying Days. Customers using Workforce Management alongside UK Statutory Sick Pay should pay close attention to this enhancement. Where a published schedule exists before the absence begins, Oracle can now use that published schedule to determine SSP qualifying days rather than relying solely on the employee’s work pattern. For organisations with complex scheduling arrangements, this should help ensure SSP calculations more accurately reflect planned working patterns. Customers planning to use this functionality should review the Schedule Hierarchy Starting Point configuration within relevant sickness absence types.

The US payroll enhancements arguably provide the strongest collection of updates this quarter, combining compliance improvements, increased transparency, and continued investment in AI-assisted payroll analysis. Managing SECURE 603 eligibility has often required manual effort, particularly for organisations with large employee populations. Oracle now automates the determination of catch-up eligibility outcomes through the Start-of-Year process, evaluating high-earner status based on payroll statutory units, tax reporting units, or tax groups depending on configuration. The inclusion of a draft mode is particularly welcome, allowing payroll teams to review outcomes before committing them in final mode. Some complex organisational structures will still require manual intervention, but for many employers this should significantly reduce annual administration effort.

The next feature is the Tax Calculation Statement Page: Federal Income Tax. This is probably my favourite enhancement in the US payroll release. Payroll teams are regularly asked why a particular tax deduction was calculated in a certain way, yet historically obtaining that answer often meant navigating several screens or performing manual calculations. Oracle has introduced a new Tax Calculation Statement view that provides complete visibility into Federal Income Tax calculations. Administrators can either review the calculation components directly or work through a step-by-step breakdown showing intermediate values and calculation logic. For troubleshooting and employee query resolution alone, this has the potential to save a huge amount of time.

Oracle continues to expand the capabilities of its Payroll Run Analyst AI Agent. The agent can now answer natural language questions relating to Federal Income Tax calculations, allowing administrators to ask questions such as why a calculation was performed a particular way or which attributes contributed to the result. This is one of the more practical examples of AI within payroll. Rather than trying to automate the payroll process itself, Oracle is using AI to make it easier for payroll professionals to understand and investigate payroll outcomes.

Oracle has added a new Tax Enforcement Level field within the Federal component of the employee Tax Withholding card. This allows administrators to determine whether annual limit tax tracking should occur at the PSU, TRU, or tax group level. Because the setting exists at employee level, it can also override organisation-level defaults when required. For organisations with more complex employment structures, the additional flexibility will be welcome.

Oracle has also improved how USOPTE statutory tax rule overrides are managed. Payroll administrators can now create, update, delete, and end-date override records directly from the Statutory Rules interface, while also reviewing override history over previous years. It brings what has sometimes been tracked externally back into Oracle in a much more controlled and auditable way.

Oracle continues to invest heavily in Irish payroll, and that’s entirely understandable. Irish Payroll is still relatively new within Oracle Fusion compared to some of the more mature localisations, and Oracle have been steadily expanding both functionality and legislative coverage release after release. The pace of delivery remains impressive, with large number of enhancements arriving in 26D alone. While some of these changes are legislative in nature, others help bring Irish Payroll into line with capabilities that customers in longer-established payroll localisations have already been benefiting from.

The Payroll Activity Centre is now available for Irish payroll customers. This provides administrators with a consolidated view of payroll activity, balances, and exceptions, including Irish-specific values such as PAYE, PRSI, USC, and My Future Fund deductions. The real value isn’t the visibility itself, but the ability to identify and resolve issues earlier in the payroll cycle before they become employee-facing problems.

Oracle has updated eligibility calculations for SSP and Illness Benefit so that they now use recorded sickness absence dates rather than medical certificate dates. It’s a relatively straightforward change, but one that better reflects how absences are typically managed in practice.

The Periodic Foreign Tax Credit enhancement allows payroll teams to apply periodic or annual foreign tax credits through the employee’s PAYE Additional Information card. Rather than waiting for relief to be claimed after year end, payroll can now reduce tax liability during payroll processing itself. For employees with cross-border tax obligations, that has the potential to improve cash flow and reduce the impact of dual taxation while relief is being processed.

Oracle now automatically applies the Department of Social Protection’s 15% net-pay deduction cap for applicable Notice of Attachment deductions. Whenever statutory limits apply, the payroll calculation automatically uses the lower of the requested deduction amount or the permitted cap.

The final enhancement supports deletion requests for previously submitted My Future Fund contribution records. The Send File Submission process can now determine whether an earlier submission exists and automatically generate either an initial submission or a deletion request as appropriate. Additional audit reporting has also been introduced to maintain visibility of deleted contribution records.

Overall, I wouldn’t describe 26D as a blockbuster Payroll release, but that’s not necessarily a criticism. Some of the most valuable payroll enhancements aren’t the flashy ones. They’re the improvements that make investigations quicker, reduce administration effort, improve compliance, or remove manual work that payroll teams have quietly accepted as part of daily life.

For me, the stand-out areas this quarter are the continued maturity of the Redwood payroll experience, the Retropay processing enhancement, and the new transparency around US Federal Income Tax calculations. Together they show Oracle continuing to focus on usability and operational efficiency rather than simply adding more functionality.

If you’re planning your 26D review, I’d recommend paying particular attention to the Redwood changes and checking whether there are opportunities to simplify payroll administration processes as part of your wider upgrade planning. And as always, keep an eye on the What’s New documentation throughout the release cycle. Oracle occasionally slips in additional gems after the initial announcement, and payroll is no exception.

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

Oracle Learning 26D: Smarter Learning Through Practical AI

~ K8 Mead ~ Leave a comment

It’s quarterly release season again and Oracle Learning has delivered a surprisingly strong set of updates in 26D. What stood out to me wasn’t any individual feature. It was the direction of travel. Over the last couple of years, we’ve seen Oracle talk extensively about AI, skills intelligence, digital assistants and, more recently, Agentic Apps. For many customers, the question has been whether these capabilities would genuinely change the way people work or simply provide another layer of technology to navigate. With 26D, Oracle Learning starts to answer that question.

Several of the headline updates focus on something far more practical than flashy AI demonstrations. They help managers understand whether learning is driving development, reduce administrative effort for learning teams, and make it easier for employees to manage their own learning journeys.

What’s particularly noticeable is that Oracle is investing across the entire learning ecosystem. Managers gain better visibility into skill development, learning specialists receive more powerful AI-assisted administration tools, and learners benefit from a significantly upgraded self-service experience. As always, Oracle may add additional functionality as the quarter progresses, but let’s take a look at the highlights announced so far.

If you’ve been following Oracle’s Agentic Apps journey, the Team Learning and Development Workspace for Managers is perhaps the most interesting Learning enhancement in 26D. One of the challenges managers often face is connecting learning activity with actual employee development. Completion rates and learning hours tell part of the story, but they rarely answer the question that really matters: is this learning helping people develop the skills they need? Oracle is clearly trying to bridge that gap.

The previous Skills Development by Skill and Skills Development by Direct panels have been replaced with two new views: Directs’ Progress on Development Objectives and Directs’ Learning Alignment with Development Objectives. Rather than simply showing learning activity, managers can now see whether development goals are progressing and whether completed learning is contributing towards those goals.

The Directs’ Progress on Development Objectives panel highlights which team members are making progress against assigned development skills during a 90-day evaluation period. Managers can take action directly from the workspace through delivered email actions, either nudging employees who haven’t started progressing or recognising those who have. The Directs’ Learning Alignment with Development Objectives panel provides a different perspective. It helps managers understand whether completed non-compliance learning aligns with an employee’s development objectives, using completion outcomes and learning context to make those connections visible.

One of the concerns I often hear when discussing AI in HR is whether we’re removing too much human judgement from people processes. Oracle has struck a sensible balance here. The agent analyses learning activity, identifies who may need support and drafts appropriate communications, but managers remain firmly in control. Nothing is sent automatically. The manager decides whether intervention is needed and whether the suggested communication is appropriate. To me, that’s where enterprise AI delivers the most value. Not by replacing managers, but by helping them spend less time finding issues and more time acting on them.

You may remember the Learning Creation Assistant, first introduced in 25D and enhanced further in 26B. In 26D, it has been renamed the Learning Catalog Management Assistant, and Oracle continues to expand what it can do. The main enhancement is support for questionnaire-based self-paced learning.

Learning specialists can now provide a questionnaire title or code and instruct the assistant to create the associated learning item. The assistant validates the questionnaire, determines whether it should be implemented as an assessment or observation checklist, and creates the learning in draft status ready for review and activation.

At first glance this might feel like a relatively small enhancement. In reality, it’s another step towards natural language administration. Learning specialists can focus on what they’re trying to achieve rather than remembering every configuration step required to get there. By allowing administrators to describe the learning experience they want to create and letting the assistant build the underlying structure, Oracle continues to remove friction from content administration. It’s exactly the type of repetitive setup activity that AI should be helping with. The assistant can also capture additional details such as mastery scores, attempt limits and visibility settings as part of the prompt, reducing the amount of manual configuration required.

Customers who already implemented the earlier Learning Creation Assistant should note that the property on the agent must be updated to reference the new delivered runnable agent. Any customisations made against copied templates will also need to be reapplied.

One of my favourite enhancements in 26D is also one of the simplest. Learning specialists can now create task-based self-paced learning directly from rich text instructions, removing the need for a supporting content asset. That may not sound revolutionary, but anyone who has implemented Learning Cloud will recognise the problem it solves.

Many organisations need to track activities that happen outside the platform. Reading a policy, completing an offline activity, attending an external event or carrying out a workplace task are all valid learning experiences, yet administrators have often needed to create workaround content simply to make those activities available in Learning Cloud. 26D removes that complexity entirely.

Learning specialists can simply enter instructions directly within the Redwood learning experience. Learners see those instructions as part of the enrolment details page and complete the activity according to the configured completion rules. Where learner confirmation is enabled, employees can mark the activity as completed themselves. Where administrator verification is required, that option is hidden and completion remains under administrative control.

It’s not necessarily the most exciting feature in the release, but I suspect it will become one of the most useful. The feature is enabled automatically and requires no additional configuration.

This enhancement originated in Oracle Ideas Lab, which is always encouraging to see. Learning specialists can now add self-paced learning directly into a course structure, allowing learners to access online content through courses in the same way they access instructor-led or virtual offerings. From the course details page, administrators can either attach an existing self-paced learning item or create a new one directly within the workflow.

The standout capability, however, is the new Replace with Self-Paced Learning action. I particularly like the inclusion of the replacement capability. Replacing learning content in large catalogues can be surprisingly challenging. Organisations need to modernise content without losing visibility of historical completions, compliance records and in-progress learning.

Oracle has clearly thought beyond simply enabling a new feature and considered the operational reality of managing learning catalogues over time. When a legacy offering is replaced, completed and in-progress learning records are preserved for reporting and audit purposes. Learners already progressing through an offering can still complete it, while future assignments are redirected towards the new self-paced learning. Deprecated offerings become read-only and are no longer available for enrolment, assignment or discovery within the catalogue.

The final enhancement that caught my attention is the continued evolution of My Learning Assistant. We’ve moved well beyond the stage where conversational assistants simply answer questions. Oracle is increasingly positioning learning assistants as task-oriented experiences, helping users complete actions rather than just retrieve information. In 26D, learners can review assignments, explore recommendations, enrol onto learning and access key learning processes from a single conversation. That moves the assistant much closer to becoming a genuine learning companion rather than simply a search tool.

The assistant can now answer questions about active, overdue, mandatory, upcoming, self-enrolled and completed learning. It can recommend content from the catalogue, support enrolment directly where eligibility allows, and launch processes such as Record External Learning and Request Noncatalog Learning. Recommendation cards are also richer, displaying details including learning type, effort, pricing information, AI-generated reasoning and links to catalogue information.

Just as importantly, Oracle continues to ground responses in actual Learning data and workflows. If information doesn’t exist, the assistant won’t invent it. That may sound obvious, but trust is one of the most important factors in successful enterprise AI adoption. Users need confidence that recommendations and answers are based on real information, particularly when they’re making decisions about compliance or professional development.

Customers who deployed My Learning Assistant using the original 25D template should take note. Oracle recommends replacing the existing template with the updated delivered version to avoid inconsistent behaviour. Depending on your deployment approach, guided journeys used to surface the assistant through the Ask Oracle banner may also require updates.

If I had to summarise Oracle Learning 26D in a single phrase, it would be practical AI. There are no headline-grabbing announcements or futuristic concepts here. Instead, Oracle continues to focus on helping managers, learning specialists and learners spend less time navigating systems and more time focusing on development.

What I find particularly interesting is that Learning is becoming one of the strongest showcases for Oracle’s broader AI strategy. Across multiple features, Oracle isn’t attempting to remove people from the process. The technology is being used to surface insights, reduce administration and support decision-making while keeping humans firmly in control. That’s where I believe enterprise AI creates the greatest value. Not by replacing expertise, but by helping people apply it more effectively. And if Oracle continues along this path, Learning could become one of the strongest examples of AI delivering measurable business value within Oracle Fusion Applications.

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

What’s New in Core HR: Oracle Fusion HCM Cloud Release 26D

~ K8 Mead ~ Leave a comment

It’s that time again, quarterly release time, and 26D brings a solid set of updates for Core HR teams. There’s a meaningful enhancement to the Assignment Change Assistant, a quiet but important fix for position synchronisation via HCM Data Loader (HDL), continued evolution of the Activity Centre experience, and a deprecation notice that anyone who built agents in the last couple of releases needs to act on. As usual, Oracle may add further features throughout the month, so let’s take a look at what’s been introduced so far.

First introduced in 26C, the Assignment Change Assistant, now referred to as the Employment Updates Agent, has been extended considerably in 26D. The original release allowed managers and HR specialists to initiate assignment changes conversationally through the AI agent framework. In 26D, Oracle has addressed one of the natural limitations of that first version: users can now ask the agent for information before deciding what to change.

So rather than jumping straight into a transaction, a manager can open a conversation and ask something like “Who is David’s current manager?” or “What job is this person assigned to?” and get a direct answer from the agent before initiating any update. That’s a genuinely useful shift in how the assistant works. It moves from being a transaction tool to being a decision-support tool as well.

Beyond information retrieval, the supported transaction scope has grown. Change Working Hours and Change Manager are now supported processes alongside the original capabilities. Salary updates are also now handled directly through the agent: managers or HR specialists can specify either a new salary amount or a percentage increase , which covers the majority of straightforward salary adjustment scenarios without needing to exit to a quick action. For anything more complex, Oracle’s guidance is to use the standard quick actions, which is sensible.

Two other additions worth noting: Business Title can now be derived automatically from the selected Job or Position and presented in the review summary before submission, and on the review page, users can now click Request Change to modify any supported assignment attribute before submitting, not just the manager notes as was the case in 26C.

One thing to note: salary update access through the agent requires the user to already hold the privilege and data access needed to create a salary change through the standard application. The agent doesn’t grant any additional access beyond what the user already has.

The next feature I want to highlight is Blank Position Values Now Synchronise Correctly via HDL. This one might look small on paper, but if you’ve ever had to unpick mismatched position and assignment data after a bulk load, you’ll appreciate exactly why it matters.

Prior to 26D, when a position attribute configured for synchronisation was cleared, running an HCM Data Loader (HDL) load would not propagate that blank value down to the assignment. The result was that the assignment retained a old value even though the corresponding position attribute had been removed. For organisations that rely on position synchronisation to keep assignment data consistent, this created a category of data discrepancy that was difficult to detect and time-consuming to resolve.

From 26D, blank values are synchronised to the assignment provided the attribute is configured for position synchronisation. The logic is straightforward: if Grade Ladder is a synchronised attribute and it’s removed from a position, the next HDL load can now clear that value on the corresponding assignments. In addition, Position Name can now be configured to synchronise with Assignment Name through HDL, so the Assignment Name is derived from the Position Name as part of the synchronisation process.

If your organisation built agents in 26A or 26B using either the Personal Information Assistant or the Person Legislative Information supervisor agent templates, this is the announcement you need to pay attention to. Both templates are deprecated in 26D. Agents already created from these templates will continue to function for now, but Oracle has confirmed these templates will no longer be enhanced. The replacement is the Person Data Assistant, introduced in 26C as a workflow agent that extends person data management with workflow-based child agents for selected data areas.

The practical implication is clear: any new development should be on Person Data Assistant, and existing agents built on the deprecated templates should be migrated. If your organisation has already deployed either of the old agents in production, now is the right time to start your migration planning. The agents won’t break overnight, but you’ll be building on a foundation that Oracle is no longer investing in, and the gap between the deprecated templates and Person Data Assistant will only widen with each subsequent release.

Start by reviewing what data areas your existing agents cover, map those to the Person Data Assistant’s workflow-based child agent structure, and assess the configuration effort involved. There’s no need to rush into a weekend migration, but equally don’t leave this until the deprecated templates stop functioning without warning.

The HCM Professional Activity Centre was introduced in 26C and is already a firm favourite. 26D brings a couple of enhancements that make it meaningfully easier to use for both HR professionals and the administrators who configure it. Applications and quick actions are now consolidated into a single list under the Quick Actions section. Previously these were presented separately, which added navigation steps for users looking to get to a specific action or application. Now, selecting View More in the Quick Actions section shows pinned quick actions first, followed by other quick actions, and then the list of applications in one continuous view.

The second enhancement is organisation-level default pinning. Administrators can now define a default set of pinned quick actions for all users via the Structure tool. If a user hasn’t set their own pins, they’ll see the organisation defaults. If they have already personalised their pins, those personal choices remain and aren’t overridden. This gives administrators a sensible way to surface the most commonly needed actions for their user population without forcing any individual into a rigid layout.

One thing to note: navigation to a future hire’s person activity centre from search results has been disabled in this release.

The Team Activity Centre enhancements in 26D follow a similar pattern to the Professional Activity Centre improvements above, with the addition of a genuinely useful capability for managers around goal assignment. Managers can now assign a performance or development goal to multiple direct and indirect reports selected through Team Activity Centre filters, all in a single action. Previously, assigning the same goal to a group of employees meant repeating the process person by person. For managers cascading goals across a team or department, that was a real time cost. This feature removes it.

The same quick actions and applications consolidation available in the Professional Activity Centre applies here too. Quick actions and applications are now in a single list under View More, with pinned actions appearing first. Organisation-level default pins work the same way.

Overall, 26D is another incremental but worthwhile update for Core HR. The headline change is the deprecation of the older personal information templates, so if you’ve built agents using those templates it’s worth starting your migration planning sooner rather than later. Beyond that, Oracle continues to refine both the AI and user experience story, with improvements that should make everyday HR processes a little smoother. As always, keep an eye on the readiness materials throughout the quarter, as Oracle sometimes introduces additional enhancements after the initial announcement.

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

GPT-5.6 Luna Is Here: What Oracle’s Latest LLM Change Means for AI Agent Studio Customers

~ K8 Mead ~ Leave a comment

One of the questions I’m asked most often about Oracle AI Agent Studio is simple: “Which model should we be using?” Until recently, many customers were selecting GPT-4.1 Mini or GPT-5 Mini for their AI Agents. That option is now changing.

Oracle has introduced a new model, GPT-5.6 Luna, as the recommended Large Language Model (LLM) for Fusion AI Agent Studio workloads. At the same time, Oracle has announced the planned deprecation and retirement of GPT-4.1 Mini and GPT-5 Mini, with both models scheduled to be fully retired in Oracle Fusion Cloud Update 27B in April 2027.

The good news is that there is no immediate action required. The important thing is understanding what is changing, who is affected, and what you should be planning for over the next few releases.

With Update 26C, GPT-5.6 Luna becomes Oracle’s recommended model for new AI Agent Studio configurations. Oracle states that Luna delivers improved response quality, lower latency and better cost efficiency for most Fusion AI workloads compared to the models it replaces. As a result, GPT-4.1 Mini and GPT-5 Mini are entering a phased retirement process:

  • 26C (available now): Luna becomes available and recommended for new configurations.
  • 26D (October 2026): GPT-4.1 Mini and GPT-5 Mini can no longer be selected for new configurations.
  • 27A (January 2027): Existing configurations continue to run unchanged.
  • 27B (April 2027): GPT-4.1 Mini and GPT-5 Mini are fully retired and any remaining configurations are automatically migrated to a supported replacement model.

If you’ve already built agents using either of these models, nothing stops working tomorrow. Oracle is giving customers a clear migration window.

The key point here is that this only impacts customers using AI Agent Studio workloads built on GPT-4.1 Mini or GPT-5 Mini. If you’re using the free OSS model, you’re not affected by this announcement and no action is required. Likewise, organisations using Bring Your Own LLM (BYOLLM) configurations are unaffected. That’s an important distinction because I’ve already seen some confusion online from customers assuming every AI Agent Studio implementation needs immediate remediation. That simply isn’t the case.

Model retirement is a normal part of the AI lifecycle. Unlike traditional software components that may remain unchanged for years, AI models evolve rapidly. Newer models typically deliver better accuracy, lower operating costs and improved performance.

Oracle’s position is that GPT-5.6 Luna provides the best balance of response quality, performance, latency and cost efficiency for the majority of Fusion AI workloads. Rather than continuing to support multiple generations of similar models indefinitely, Oracle is concentrating investment, testing and support around a newer foundation. From a customer perspective, that’s generally positive. The challenge is making sure your agents continue to behave the way you expect after migration.

The Real Question: Will My Agent Behave Differently? Possibly. This is the part of the announcement that deserves the most attention. Oracle is very clear that customers should re-test prompts when moving to Luna because model behaviour can vary. Even when two models are performing the same business task, the outputs may not be identical. If you’ve spent time fine-tuning prompts for question answering agents, planning agents, tool-calling workflows or process automation scenarios then you should assume validation testing is required before moving to production.

In my experience, this is often where organisations underestimate the effort involved in AI lifecycle management. The migration itself may take minutes. Proving that the business outcome remains acceptable often takes significantly longer.

For existing implementations, my advice is straightforward. Don’t panic, but don’t ignore it either. There is no immediate requirement to migrate. Existing configurations continue running through Update 27A. However, I would recommend that organisations start planning their testing approach well before 27B arrives.

A practical approach would be:

  1. Identify any agents currently using GPT-4.1 Mini or GPT-5 Mini.
  2. Create a test environment if one does not already exist.
  3. Switch the agent to GPT-5.6 Luna.
  4. Run representative business scenarios.
  5. Compare outputs.
  6. Adjust prompts if required.
  7. Schedule production migration before Update 27B.

Oracle’s own migration guidance suggests making expected outputs more explicit, clearly separating user-facing responses from internal processing logic, and testing thoroughly before deployment.

What About Licensing and Cost? Fortunately, this is one area where customers are unlikely to see much change. Oracle classifies GPT-4.1 Mini, GPT-5 Mini and GPT-5.6 Luna within the same Balanced (previously Premium) model category, consuming AI Units under the existing Fusion AI pricing model. Oracle states that the overall impact should be cost neutral.

That’s welcome news given the number of conversations currently taking place around AI costs and maintaining business value from AI investments. I actually see this announcement as a sign that Oracle’s Fusion AI platform is maturing. We’re moving beyond a world where organisations simply “pick an LLM” and hope for the best. Instead, we’re seeing proper lifecycle management, defined retirement schedules, migration paths and testing guidance.

The important message is this: If you’re using GPT-4.1 Mini or GPT-5 Mini today, you have time. Nothing requires immediate action. But if you want to remain in control of your model selection and ensure your agents continue to behave as expected, now is the right time to start planning your migration and testing strategy. And if you’re creating new AI Agents in Oracle Fusion AI Agent Studio today, Oracle’s recommendation is clear: start with GPT-5.6 Luna.

Oracle Has Moved the SCM Redwood Deadline. Here’s Why You Still Need to Act Now

~ K8 Mead ~ Leave a comment

For many Oracle Fusion SCM customers, Tuesday’s announcement will have come as welcome news. The mandatory Redwood adoption deadline has moved from before 27A to before 27B, giving organisations approximately another three months to complete their transition. Oracle’s latest guidance now places mandatory adoption before 27B for most SCM products, rather than before 27A.

If you’ve been worried about fitting testing, change management, personalisation reviews and training into an already busy roadmap, that extra quarter will undoubtedly help. But if you’re interpreting this as an opportunity to pause your Redwood programme, I think that would be a mistake. The deadline has moved. The amount of work required has not.

The reality is that many customers have been asking for more time. Across Procurement, Inventory, Manufacturing, Order Management and other SCM modules, Redwood adoption isn’t simply a technical upgrade. It requires organisations to review processes, retrain users, validate extensions, revisit personalisations and test end-to-end business flows.

The additional quarter gives customers breathing space to do those activities properly rather than rushing to meet an arbitrary date. That’s a positive outcome. It also allows Oracle to continue delivering the final Redwood experiences and setup pages that are still being completed across parts of the SCM portfolio. Oracle’s recent communications highlight continued delivery of Redwood functionality alongside a growing catalogue of Redwood-only features and AI capabilities.

What the extension does not change is Oracle’s strategic direction. Classic remains on the retirement path. Redwood remains the future. A year ago, many conversations about Redwood in Supply Chain focused on colours, layouts and navigation. Today that feels increasingly outdated.

Almost every release introduces new capabilities that are built specifically for Redwood pages. Across Procurement and SCM, Oracle is investing heavily in AI Agents, Agentic Apps, enhanced analytics, intelligent search experiences and workflow automation that simply do not exist in classic pages.

Examples include:

  • Autonomous supplier research
  • Purchase order advisory agents
  • Sourcing Command Centre Agentic Apps
  • AI-assisted contract capabilities
  • Redwood-only procurement administration pages
  • Enhanced receiving approvals and workflows

These aren’t cosmetic improvements. They fundamentally change how users interact with Oracle Fusion SCM. The risk of delaying Redwood adoption is no longer just missing a compliance deadline. It’s falling behind on innovation.

Whenever I talk to customers about Redwood, I often hear concerns about profile options, configuration settings or deployment approaches. Those things matter. But they are rarely the hardest part. The bigger challenge is behavioural change.

Many organisations successfully enable Redwood but continue allowing users to navigate through familiar legacy pathways. Users naturally revert to what they know, training materials remain based on old screenshots, and business processes continue reflecting classic ways of working. The result is that Redwood becomes technically deployed but operationally underused. That’s important because many new capabilities assume users are operating within Redwood experiences. If users never fully transition, organisations struggle to realise the value Oracle is delivering.

One of the reasons Redwood projects are frequently underestimated is because the technical enablement is usually only a small part of the overall effort. The work that catches organisations out tends to include:

  • Reviewing existing Page Composer personalisations
  • Assessing extensions and integrations
  • Updating training materials
  • Revising support documentation
  • Testing business-critical scenarios
  • Running end-to-end process validation across multiple modules
  • Preparing suppliers and external users for interface changes
  • Supporting adoption after go-live

These activities take time. More importantly, they require availability from business users who are typically balancing day jobs alongside project responsibilities. An additional quarter definitely helps. It should not be wasted.

Interestingly, the organisations that benefit most from this timeline change probably won’t be the ones that slow down. They will be the ones that use the additional time strategically. Instead of rushing towards a deadline, they can:

  • Perform more comprehensive testing
  • Complete personalisation assessments properly
  • Validate role-based access thoroughly
  • Deliver stronger training and communications
  • Run pilots with business users
  • Resolve adoption challenges before they impact operations

Those activities reduce risk significantly more than simply delaying action for another three months.

Although Oracle has moved the mandatory deadline to before 27B, my recommendation remains largely unchanged. Plan for 27A. Deliver by 27A if possible. Use the additional quarter as contingency rather than scheduling your entire programme around it. Projects rarely run exactly to plan. Key resources become unavailable. Testing uncovers unexpected issues. New quarterly updates introduce further considerations. Competing priorities emerge. Organisations that reach readiness by 27A will have flexibility. Organisations that wait until the final possible moment may find themselves under pressure once again.

Perhaps the most important thing to remember is that Redwood was never supposed to be a simple compliance activity. Oracle’s long-term investment in user experience, automation, AI Agents and Agentic Apps is increasingly centred around Redwood. Every quarterly update widens the gap between what is available in Redwood and what remains available in classic experiences.

Yes, customers have gained another quarter. That is undoubtedly helpful. But the organisations that see the greatest benefit won’t be those that use the time to delay. They will be the ones that use the time to prepare properly, drive adoption effectively and put themselves in the best position to take advantage of everything Oracle is building next. The clock hasn’t stopped. Oracle has simply given you three more months to get it right.

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

Beyond the Technology: Where Agentic Apps Could Take Oracle Fusion Next

~ K8 Mead ~ Leave a comment

Over the course of this series, I’ve explored how Oracle Fusion AI Agent Studio is changing, why the Builder Assistant matters, the building blocks that sit behind Agentic Apps, and some of the design principles that can help organisations create meaningful solutions. Throughout all of those discussions, one theme has consistently emerged. The technology itself is only part of the story. What’s really interesting is where this might lead.

Whenever a new technology appears, there’s a tendency to focus on what it can do today. That’s understandable. Organisations want to understand the practical use cases, the risks, the costs and the potential benefits before investing time and effort. But sometimes it’s worth stepping back and thinking about the broader direction of travel. When I look at Agentic Apps, I don’t see another reporting tool, dashboard framework or application development platform. I see the beginnings of a different way of interacting with enterprise software.

For most of the history of business applications, software has been built around transactions. An employee updates their details. A manager approves a request. A finance team processes an invoice. A procurement specialist creates a purchase order. Applications have traditionally been designed to help users complete specific tasks as efficiently as possible. There’s nothing wrong with that approach. In many cases, it’s highly effective.

However, organisations today are dealing with increasing levels of complexity. Decisions are rarely based on a single transaction. They often require information from multiple systems, multiple teams and multiple business processes. This is where I think Agentic Apps become particularly interesting. Rather than simply helping users complete a transaction, they have the potential to help users navigate an entire business outcome. That’s a very different objective.

One of the ideas I find most compelling is the shift from process-centred thinking to journey-centred thinking. Take something as common as onboarding a new employee. Traditionally, onboarding spans numerous activities across HR, IT, Facilities, Security, Payroll, Learning and line management. Each team plays an important role, but the overall experience is often fragmented because it spans multiple systems and processes. From the employee’s perspective, however, there is only one journey. The same principle applies to customer experiences, supplier management, project delivery and countless other business activities.

We tend to organise systems around organisational structures. People experience them as journeys. Agentic Apps have the potential to bridge that gap by bringing together information, actions and communications from across multiple processes into a single, outcome-focused experience. Instead of asking users to navigate organisational complexity, the technology could increasingly help manage that complexity on their behalf.

Many of today’s business challenges don’t fit neatly within departmental boundaries. Employee retention isn’t just an HR issue. Supplier performance isn’t just a procurement issue. Project success isn’t just a project management issue. The factors influencing those outcomes often span multiple teams, multiple data sources and multiple business processes. This is where traditional applications can sometimes struggle. Each application does its job well, but no individual application has visibility of the complete picture.

Agentic Apps offer the possibility of bringing those perspectives together. Imagine a manager being able to view workforce data, project commitments, learning progress and performance indicators in a single context when making a resourcing decision. Imagine procurement, finance and supply chain teams working from the same set of insights when managing a critical supplier issue. Imagine employees receiving support that reflects their entire journey rather than the individual processes sitting behind it. The technology is still evolving, but the direction feels increasingly clear.

One challenge I hear repeatedly from customers is that the pace of business continues to accelerate whilst organisational complexity continues to increase. There are more systems. More data. More regulations. More stakeholders. More expectations. The result is that people spend an increasing amount of time gathering information and coordinating activities rather than focusing on high-value decision making.

I don’t believe Agentic Apps will eliminate complexity. Business will always be complex. What they can potentially do is make that complexity easier to navigate. Rather than expecting individuals to manually bring together dozens of signals from across the organisation, an Agentic App can help surface what matters, explain why it matters and support the next action. In many ways, that feels like the natural evolution of enterprise software. For years we’ve focused on capturing information. The next phase may be helping organisations make better use of it.

Of course, technology alone isn’t enough. One thing I’ve learned from years of transformation programmes is that successful adoption rarely depends entirely on the software. Culture matters. Leadership matters. Governance matters. Trust matters.

Organisations exploring Agentic Apps should be thinking about these areas now. How much autonomy should agents have? Which decisions require human approval? How will recommendations be reviewed and governed? How will users understand and trust the outputs being generated? These questions are every bit as important as the technical architecture. In fact, I would argue they’re more important.

The organisations that achieve the greatest success with Agentic Apps are unlikely to be those with the most sophisticated technology. They’ll be the organisations with the clearest understanding of where AI can support people whilst maintaining appropriate governance and accountability.

Whenever discussions turn to AI, there is often concern that technology will replace human expertise. Personally, I don’t think that’s where the greatest opportunity lies. The most valuable decisions organisations make often require context, judgement, empathy and experience. These are qualities that remain fundamentally human.

What Agentic Apps can potentially do is reduce the amount of time spent gathering information, navigating systems and managing administrative tasks. That creates more time for the activities people are uniquely good at. Leading teams. Building relationships. Solving problems. Managing change. Making informed decisions. If organisations approach Agentic Apps with that mindset, the conversation becomes much more constructive. It stops being about replacing people and starts being about helping people be more effective.

Perhaps the thing that excites me most about the future of Agentic Apps isn’t a specific feature or capability. It’s the possibility of making enterprise software feel more human. For years, users have adapted to systems. They’ve learned processes, navigated menus, searched for information and worked around organisational boundaries. Agentic Apps have the potential to reverse that relationship. Instead of people adapting to software, software can increasingly adapt to people. It can understand context. It can bring together information. It can help guide users towards better outcomes. That’s a powerful idea. And whilst we’re still in the early stages of that journey, I think we’re beginning to see what that future could look like.

When I started exploring Oracle Fusion AI Agent Studio, I expected to spend most of my time learning about agents, prompts, workflows and integrations. Those things are important, and they will continue to evolve rapidly over the coming years.

But the more time I spend with these capabilities, the more convinced I become that the most important conversation isn’t about the technology itself. It’s about outcomes. It’s about helping organisations deal with increasing complexity. It’s about helping people make better decisions. And ultimately, it’s about creating experiences that feel less like software and more like support.

Whether you’re just starting to explore Agentic Apps or already experimenting with your first use cases, I think that’s the question worth keeping at the centre of the conversation. Not what the technology can do. But what outcomes it can help your organisation achieve.

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

What Makes a Good Agentic App?

~ K8 Mead ~ Leave a comment

Over the past few articles in this series, I’ve talked about how Oracle Fusion AI Agent Studio is shifting the conversation away from technology and towards business outcomes. I’ve explored how the Builder Assistant is helping reduce the gap between an idea and a working solution, and I’ve looked at the key building blocks that sit behind Agentic Apps.

But there’s another question that’s arguably even more important. Just because we can build an Agentic App, does that mean we should? As organisations begin exploring AI Agents, there’s a natural temptation to automate everything. Every process starts to look like a candidate for AI. Every challenge appears to need an Agent. Every requirement seems to demand its own intelligent assistant. In my experience, that’s rarely the right approach.

The most successful Agentic Apps aren’t the ones using the most sophisticated technology. They’re the ones solving a genuine business problem in a way that feels intuitive, useful and trustworthy. The technology matters, of course. But good design matters more.

One of the biggest mistakes organisations make when introducing new technology is trying to recreate existing processes in a new tool. We’ve all seen it happen. Paper forms became electronic forms. Manual approvals became digital approvals. Reports became dashboards. The underlying process remained largely unchanged. There’s a risk of doing exactly the same thing with Agentic Apps.

Instead of asking how AI can support an existing process, I think organisations should start by asking a different question. What business outcome are we trying to achieve? For example, an organisation might say they want an AI solution for employee retention. But employee retention isn’t really the outcome. The outcome is helping managers identify people who need support before they choose to leave. Similarly, a procurement team might think they need an AI solution for supplier management. In reality, the outcome is reducing the likelihood of supplier issues disrupting operations. When you focus on outcomes rather than processes, the design conversation changes completely. You stop asking how to automate existing steps and start asking how to help people make better decisions.

This might sound strange coming from someone writing a series about Agentic Apps, but not every business challenge requires an Agent. Sometimes a report is enough. Sometimes an alert is enough. Sometimes a workflow already works perfectly well. I think one of the most important design principles is understanding where an Agent adds genuine value.

Generally speaking, I see Agentic Apps delivering the greatest benefits when people need to combine information from multiple sources, understand a situation, make a decision and take action. Those are activities that often involve context, judgement and prioritisation. By contrast, simple and highly structured processes are often better handled through traditional automation. If the answer is always the same and the outcome is completely predictable, an Agent may simply introduce unnecessary complexity. The goal shouldn’t be to build more Agents. The goal should be to solve more problems.

Most organisations don’t suffer from a lack of data. If anything, the opposite is true. The challenge is usually information overload. Managers have dashboards. Leaders have reports. Teams receive alerts. Yet people still struggle to know where to focus their attention. This is where I think many organisations can unlock the greatest value from Agentic Apps. A good Agentic App doesn’t simply surface more information. It helps users understand what matters.

Imagine two different approaches to workforce management. The first presents pages of employee data, engagement metrics, performance ratings, salary information and talent profiles. All the information is available, but the user still needs to interpret it and decide what to do next. The second identifies three employees who may require attention, explains why they have been highlighted and suggests possible next steps. The underlying data may be exactly the same. The experience is completely different. One focuses on information. The other focuses on decision-making. That’s where Agentic Apps should aim to deliver value.

Whenever AI becomes involved in business processes, governance inevitably becomes part of the conversation. And rightly so. The most successful implementations I’ve seen use AI to support decision-making rather than replace it. For example, if an Agent identifies that an employee’s visa is approaching expiry, it can highlight the issue, gather relevant information and even prepare a communication. But deciding whether to send that communication remains a human decision.

Similarly, if an Agent identifies a supplier risk, it can explain the concern and recommend an action, but accountability for the final decision remains with the person responsible for that supplier relationship. I think this balance is incredibly important. AI should help people make better decisions. It shouldn’t remove people from decisions that require judgement, accountability or context. The organisations that get this balance right are much more likely to build trust in their AI solutions.

One lesson I’ve learned from years of delivering technology projects is that users don’t adopt systems because they’re clever. They adopt systems because they’re useful and trustworthy. An Agent can generate incredibly sophisticated outputs, but if users don’t understand where the information came from or why a recommendation was made, trust quickly disappears. That’s why explainability matters. Users need confidence that recommendations are based on reliable information. They need to understand what data has been considered. They need to know when human review is required.

Most importantly, they need confidence that the system is helping them achieve better outcomes rather than creating additional work. A simple, transparent Agent that consistently provides useful guidance will almost always deliver more value than a complex Agent that nobody trusts.

One thing I’ve noticed when watching AI demonstrations is that they’re often designed to showcase what’s possible. Real business environments are different. The question isn’t whether an Agent can do something impressive. The question is whether people will use it on a busy Tuesday morning when they have ten competing priorities. That means designing experiences that fit naturally into the way people work. It means presenting recommendations in context. It means minimising unnecessary complexity. And it means ensuring users can act on insights quickly and confidently. The most successful Agentic Apps won’t necessarily be the most innovative. They’ll be the ones that people actually use.

Traditionally, technology projects have often been measured using delivery metrics. Did the system go live? Was it delivered on budget? Were the requirements completed? Whilst those measures remain important, I think Agentic Apps need additional measures of success. Are decisions being made more quickly? Are managers identifying issues earlier? Are employees receiving better support? Are risks being addressed before they become problems? Are users spending less time searching for information?

Ultimately, the value of an Agentic App isn’t determined by how many features it contains or how many AI models sit behind it. It’s determined by whether it helps people achieve better outcomes. That’s the measure that really matters.

As organisations continue exploring Agentic Apps, I believe the conversation will gradually move away from technology and towards design. The organisations that achieve the greatest success won’t necessarily have the most advanced AI. They’ll be the ones that understand the problems they’re trying to solve, focus on outcomes rather than processes and place people at the centre of the experience. Good Agentic Apps don’t exist because AI is available. They exist because there are business challenges worth solving. And that’s where every design conversation should begin.

In the final article in this series, I’ll look beyond today’s capabilities and explore where Agentic Apps could take Oracle Fusion next, along with some of the opportunities and challenges organisations should be thinking about as this technology continues to evolve.

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