The News: Oracle announced at CloudWorld London that it has added several new generative AI capabilities to its Oracle Fusion Cloud Applications Suite, including new capabilities for finance, supply chain, HR, customer experience, and more, with the goal of helping organizations be more competitive, boost productivity, and reduce cost of doing business. Oracle’s implementation of generative AI capabilities is designed to support better decision making and enhance the employee and customer experience within the flow of work. You can read the original release from Oracle on its website.
Oracle Fusion Cloud Applications Suite Adds New GenAI Capabilities
Analyst Take: Oracle announced at CloudWorld London a number of new generative AI capabilities within the Oracle Fusion Cloud Applications Suite that are designed to help customers improve decision-making and enhance the employee and customer experience. Generative AI capabilities are embedded within the existing workflows across finance, supply chain, HR, sales, marketing, and service. The enhancements also include an expansion of the Oracle Guided Journeys’ extensibility framework to enable customers and partners to incorporate more generative AI capabilities to support their individual industry and competitive needs. The announcement from Oracle was chock-full of news, but the key takeaways are as follows:
Oracle is embedding more than 50 generative AI capabilities, built on Oracle Cloud Infrastructure (OCI), and leveraging its leading AI services. In addition to providing a robust set of use cases and tools for harnessing the power of generative AI within Oracle Fusion Applications, the company has clearly stated that no customer data is shared with large language model (LLM) providers or seen by other customers.
Most interestingly, Oracle says that an individual customer is the only entity allowed to use custom models trained on its data, and role-based security is embedded directly into Oracle Fusion Applications workflows that only recommends content that end users are entitled to view. The clarity around these data safeguards/guardrails are particularly welcome for enterprise customers that cannot afford missteps around data leakage.
Oracle is taking an application and function-specific approach to rolling out generative AI, debuting specific generative AI use cases for its Oracle Fusion Cloud Enterprise Resource Planning (ERP), Oracle Fusion Cloud Supply Chain and Manufacturing (SCM), Oracle Fusion Cloud Human Capital Management (HCM), and Oracle Fusion Cloud Customer Experience (CX) offerings.
Each platform features very specific generative AI use cases that are trained on the specific business processes and flows included within each platform, rather than on public LLM data, ensuring that processes can be accurately automated, insights can be generated quickly and confidently, and outputs clearly explained.
Interesting Use Cases for Enterprises
The company’s press release highlights a variety of interesting generative AI use cases that have been embedded into Oracle’s platform, but I found the following ones particularly interesting.
Predictive forecast explanations within Oracle Fusion Cloud ERP: This capability is designed to help finance professionals generate contextual commentary to explain forecasts produced by predictive models and key factors driving the prediction. According to Oracle, these generative AI-powered explanations will help demystify the inner workings of predictive models, build trust and confidence in forecasts, and enable broader adoption of predictive forecasting models.
From an enterprise perspective, Oracle’s generative AI can be viewed as a force multiplier that will elicit real business benefits beyond simply reducing repetitive tasks. This specific capability will help organizations rely on the power of predictive models and forecasting, which has often been viewed as “black boxes,” or too complex to fully unpack, particularly when inputs or assumptions are changed.
Negotiation summaries within Oracle Fusion Cloud SCM: Designed to assist procurement professionals, this tool will help procurement professionals quickly generate a customized cover page summary for a specific negotiation. As large-scale negotiations often include dozens to hundreds of specific elements, generative AI-powered assistance can ensure that relevant information is captured and incorporated into a concise and accurate summary, helping to speed up negotiations, increase savings, reduce risk, and maximize supplier outcomes.
Candidate assistant within Oracle Fusion Cloud HCM: This tool is designed to help candidates find answers to common questions about the company, benefits, and job-specific requirements in a simple conversational experience. The true value provided by generative AI revolves around supporting engagement with prospects and candidates, while enabling HR professionals to focus their time and resources on other strategic tasks.
Assisted authoring for sales content within Oracle Fusion Cloud CX: This tool helps salespeople improve productivity by generating customer success stories from closed-won account history. This is a very useful tool, as it ensures that salespeople are not slowed down tackling tasks for which most are not well suited and enables creative salespeople to send out multiple variations of success stories to stakeholders on the same buying teams, demonstrating more breadth and relevancy to each stakeholder.
Generative AI Extensibility with Oracle Guided Journeys
Oracle announced that Oracle Guided Journeys now provides an extensibility framework that allows Oracle Cloud HCM and Oracle Cloud SCM customers and partners to add their own generative AI capabilities that complement and seamlessly integrate with their existing Oracle Fusion Application investments. Customers can select their preferred LLM provider to support their unique industry and competitive needs.
As organizations expand use of generative AI into more complex use cases, the need for flexibility and use of multiple LLMs will only increase, and it is good to see Oracle is supporting this open approach to generative AI.
Oracle’s Position of Strength, and an Opportunity
These generative announcements from Oracle clearly demonstrate the company is taking a thoughtful approach to rolling out generative AI functionality where it can deliver business benefits. Oracle’s solid RAG-based approach to grounding the models in vetted data will help deliver reliable results, and its explicit statements on model guardrails is a welcome message to nervous IT and business leaders that have seen generative AI generate headlines for the wrong reasons.
One significant opportunity for Oracle lies in its approach to supporting other types of LLMs. If Oracle is able to match specific use cases with one or two LLMs that demonstrate a high degree of utility, functionality, or accuracy, there is a significant opportunity to come to market with true industry- or vertical-specific offerings. I believe these will be in high demand over the next few years as enterprises seek to maximize the ROI and efficiency of their generative AI investments.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
