Oracle Intelligent UX (AI-UX) is a technology devised by the team that created Oracle AI apps, which have embedded AI into the Oracle Fusion Cloud suite of applications. Oracle AI-UX enables Oracle Cloud Applications to adapt to each user and the context they work in at any given time. As a result, the user experience is highly personalized with aspects of routine data entry automated and suggested actions surfaced in the user interface. Oracle AI-UX is bringing as much user-friendliness typical of modern consumer applications to enterprise software, with the critical distinction that these capabilities are tailored uniquely to individuals in the roles that they occupy within a business, instead of as a private user. Oracle AI-UX is being introduced as part of the base functionality for key Oracle software-as-a-service (SaaS) applications.
AI-UX learns who you are and what you and other users like you have done in the past to predict what actions you’re most likely to take and what choices you’re likely to make in the following steps:
To protect your privacy, AI-UX doesn’t use personally identifiable information (PII) for predictions. It ingests no user profile attributes indicating any protected characteristics, such as race, age, or gender. Any user with unique profile attribute values is purged before training the AI. Algorithms and prediction strategies are deployed with multiple customers, but customer data is never shared or commingled.
For more information on Oracle AI apps and Oracle Intelligent UX, see Oracle Artificial Intelligence.
Unlike many vendors, Oracle approaches AI from a pragmatic perspective. We want to ensure that our solutions fulfill a specific need and deliver tangible value to your business. This philosophy drives us to uncover and solve real problems in both front- and back- office functions, where many incremental improvements can lead to an amplified level of value for the business overall.
Part of this pragmatic philosophy extends to how AI is delivered to our customers. For customers to realize the value of AI, they need widespread adoption of the AI capabilities provided. Oracle is embedding AI within its Fusion applications so that insights, data outputs, and personalized recommendations are surfaced directly inside the environments in which users of Oracle business software spend most of their working day. This automated surfacing of AI capabilities avoids issues of the past, where using products that provided more data and insights carried with them an overhead, such as switching to another system and importing data. Instead, using Oracle AI is a seamless experience that helps users accelerate their workflow, get more done, and become more effective in their role every day.
To ensure that we build AI features that solve real problems, we undertake a process known as AI capability mapping. This strategic activity shows how data and AI can work together to achieve optimized, AI-driven outcomes for a given business process. Every capability map defines a cohesive set of use cases that help visualize what you can accomplish when solutions work together over time.
AI capability maps start with the goal in mind. Every map begins by establishing an understanding of an optimized end-state that customers hope to achieve, such as growing pipeline, reducing manual labor, increasing retention, and lower costs.
Every AI capability map begins with a strong data foundation. The power of any AI outcome lies within the data it consumes. The first step in every map is to define a quality data foundation to set expectations on how to achieve your wanted AI outcomes. Without a solid data foundation, even the smartest AI algorithms can’t supply you with optimized, actionable outcomes. What makes Oracle unique is our human-in-the-loop process, which identifies anomalies and validates data accuracy for the data assets that we provide to augment your own customer data.
AI capability maps aren’t strictly linear. While they provide a guide on what capabilities are needed, you can build capability maps in nonchronological order when a suitable data foundation exists. So, you can skip some steps listed in the map and focus on your top business priorities then.
When considering data-driven and AI-powered solutions, we typically look to derive the following benefits:
AI capability maps provide an array of use cases that are suited to data-driven and AI feature development, as shown in the following graphic:
To optimize performance over time, our AI-powered capabilities are self-recalibrating. We designed our AI capabilities with automatic feedback loops, so they learn from user interactions directly through our SaaS applications to retrain models and provide more intelligent outcomes. With a growing number of AI apps embedded into our SaaS applications, Oracle is uniquely positioned to deliver value that increases over time directly through the business software that our customers are using every day to run their business.
For more information on Oracle AI apps, see Oracle Artificial Intelligence.