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What Oracle’s AI Agent Applications mean for Fusion users
It used to be just at Oracle OpenWorld, their annual show, that big advances in technology and applications were made. But now, with application updates pushed out every three months, announcements come much quicker. So it was not unexpected that there would be new announcements at the AI World roadshow in London last month.
What’s new: Oracle’s AI Agent Applications
In London in March, Oracle announced the AI Agent Applications, which they’re calling Fusion Agentic Applications—the next level in this fast‑paced AI revolution.
In just a few years, we have gone from redefining what is meant by AI, to the introduction of generative AI to help us create content, AI agents to help us do repetitive tasks, AI Studio to build your own, adding workflow… and now applying those agents to making decisions based on outcomes we define.
Watch this interview with Steve Miranda from Bob Evans of Cloud Wars. Bob always peels away the hype and quickly gets to the point. Many others have posted their précis on LinkedIn, but I thought I would concentrate on what it means for users.
It took a while for people to get their heads around what was meant by AI, and I’ve previously said that I’ve started many a presentation with an AI explanation. But that’s no different from where we were 15 years ago when we were explaining what was meant by ‘cloud.’
Generative AI almost crept up on us. ChatGPT was a phenomenon that frightened us. We thought it was going to take away every brain cell from our children and allow cheating in every possible academic scenario. But now we see it used for good (and sometimes bad) in our everyday lives. In many instances, it has become the default, and if there is an option, it’s usually to turn it off.
In our applications, it’s slightly different. For Fusion Applications, the prerequisite was the move to Redwood, but once that profile option is flipped, generative AI is everywhere. I have a presentation where I talk about us at Inoapps using Fusion in our goal‑setting process. There is good research showing that organizations using goals are more effective in supporting their employees, and it certainly helped speed up the goal‑setting process in our organization, where individuals and managers had access to generative AI.
The introduction of AI agents is currently where most thinking is. Recent commentary says we’ve moved beyond proof of concept into execution, but I know that many organizations are still hesitant and still not sure where the value is for them. I read a really good article over the weekend that talked about the most effective people having the most to lose with AI. If their processes are effective today, the risk of AI reducing that effectiveness is a bigger concern than for an organization that has a long way to go. It’s worth a read—change management is still a big consideration for your AI strategy.
Oracle quoted that 64% of Fusion customers are using AI, but in my discussions, that covers any type of AI, not just AI agents. They also mentioned that those using agents were using fewer than five. I think that number is important. AI for AI’s sake is not what people should be looking for. AI should be used to smooth out some of our challenges.
How our customers are exploring AI in context
I have one customer who was at AI World in London who is currently looking at how AI agents can help with their monthly payroll processes. I understand why. The manual checking they do each month is high stakes. No one wants to get payroll wrong.
Oracle’s announcement of their AI agent applications gave us a better way to frame that conversation. To my mind, it moves it from “how do I build an agent?’ to “how do I apply an agent to an outcome that matters in my organization?”
So instead of telling your agents to check things at the end of each cycle, why not have them checking all the time—working inside Fusion with the same data and guardrails—and telling you early when you need to course correct?
I use the analogy of the Ever Given boat in the Suez Canal. When it left port, it was on the right course, and its failure—the reason it became stuck—was that it didn’t alter that course as tides, winds, and life in general got in the way. If you’re using an AI application, it is looking at the outcome you need. The destination. And it can help you make those small course corrections.
Built in, not bolted on: AI where you need it
I really do believe that AI is changing the world we live in, and I’m honored to work in the technology that allows us to adopt it quickly and safely. One of the things I really appreciate is that our data lives inside our organization, right there in the application. That means that most of what an AI application needs to ‘understand’ us is already in the application. Oracle’s strategy, as I define it, is about making AI available wherever you need it. In their words, it’s ‘built in, not bolted on.’ That’s why we don’t need to reinvent the wheel every time there’s something new we want to try. We can adapt as the technology evolves, without starting from scratch every time.
There was also small update in how AI is charged. Within Fusion Applications, AI is included as part of your subscription. If you want to extend AI agents or applications beyond Fusion—say to other Oracle services or external data—there is a small charge once you go beyond the base allowance.
While I’ve focused on Fusion Applications here, it’s worth remembering that the underlying technology powering these AI agents is part of the broader Oracle technology stack. This means you can extend these capabilities to other Oracle services, or your own data, whenever you’re ready.
Ready to explore what’s possible?
If you’re curious about what Oracle’s AI agentic applications could do for your business, get in touch with the AI experts at Inoapps to explore the possibilities.
Debra originally published this in her blog: Debra's Thoughts on Oracle.