The News: Oracle announced new artificial intelligence (AI) capabilities within Oracle Fusion Cloud Customer Experience that are designed to automate time-consuming tasks and help marketers, sellers, and service agents more precisely target, engage, and serve buyers. The new capabilities include GenAI-Assisted Answer Generation, Assisted Scheduling for Field Service, Opportunity Qualification Scoring, GenAI-Assisted Authoring for Marketing and Sales, and Seller Engagement Recommendations.
You can read the press release announcing this news here.
Oracle Announces New AI Capabilities in Oracle Cloud CX
Analyst Take: Oracle announced several new AI capabilities within Oracle Fusion Cloud Customer Experience that are designed to automate time-consuming and repetitive tasks and help marketers, sellers, and service agents target, engage, and serve buyers with more precision, speed, and efficiency.
The new AI capabilities in Oracle Cloud CX further expand the AI capabilities within Oracle Fusion Cloud Applications Suite, which are built on Oracle Cloud Infrastructure (OCI) and support more than 50 generative AI use cases.
It is no surprise that Oracle and other major SaaS vendors have chosen to focus their initial generative AI use cases on tasks that are easily repeatable, which enables scalability and relatively fast time to value. Notably, Futurum Intelligence projects that global SaaS spending on text, generation, and analysis will reach $4.5 billion by 2027, up from $2.3 billion in 2023.
New AI Capabilities in Oracle Cloud CX Focused on Improving Efficiency and Engagement
The new generative AI features that are included within Oracle Cloud CX are designed to improve the efficiency of marketers, sellers, and support workers by reducing or eliminating the need to manually initiate and carry out repetitive tasks that consume time and effort. The key features announced by Oracle include:
- GenAI-Assisted Answer Generation: Within Oracle Service, agents can leverage Oracle Digital Assistant to automatically craft contextually-aware responses to customer questions, improving agent response times and freeing service agents to focus on more complex questions. As the data used to ground the AI models comes from an organization’s own knowledge base and service-interaction history, the consistency and accuracy of responses may exceed the performance of unassisted agents.
- Assisted Scheduling for Field Service: This feature is designed to assist field service technicians in optimizing their schedules, automatically recommending relevant jobs by incorporating key factors, including a technician’s availability, location, skills, and billing status, among others. By utilizing AI to automatically recommend and schedule jobs based on the estimated job duration and travel time, customers can be provided with more visibility into the service experience, resulting in greater customer satisfaction. Schedule optimization may become a key factor in helping organizations differentiate their offerings from competitors, as both B2C and B2B customers increasingly demand more visibility and transparency around service appointments.
- Opportunity Qualification Scoring: The new AI scoring capabilities included in Oracle Unity CDP are designed to assist organizations to grow account-based revenue and generate more B2B deals by helping to identify the right contacts at target accounts and improve the opportunity qualification process. By analyzing a greater amount of data from a variety of sources in real-time, the algorithm can update the opportunity score based on the most recent information available, increasing the chance of conversion.
- GenAI-Assisted Authoring for Marketing and Sales: Within Oracle Marketing and Oracle Sales, this AI feature is designed to automatically produce targeted content for marketing and sales collateral, such as recommended copy for emails and landing pages, based on relevant data held within the company’s systems, ensuring personalized and timely engagement. Using AI to generate content can help improve the consistency of messaging and ensure that all responses comply with brand guidelines and best practices.
- Seller Engagement Recommendations: Within Oracle Sales, AI-driven Seller Engagement Recommendations are designed to help sellers to generate more business by delivering highly targeted recommendations on specific products to offer, insights on the buyers’ role and engagement level, and additional contacts for key opportunities. Key to this function is the availability of clean, labeled, and segmented data that is always kept up-to-date and accessible.
Generative AI Safeguards Built Into OCI
The new capabilities are built on OCI and leverage its AI services, which are designed to respect customers’ enterprise data, privacy, and security. According to Oracle, OCI Generative AI Service does not share any customer data with large language model (LLM) providers, nor is it viewable by other customers. In addition, an individual customer is the only entity allowed to use custom models trained on its data. To further protect sensitive information, role-based security is embedded directly into Oracle Fusion Applications workflows that only recommends content that end users are entitled to view.
Embedding AI Across Workflows and Processes
Generative AI has become table stakes for SaaS vendors, and Oracle has stepped up to embed these capabilities within its suite of applications. As part of Oracle Fusion Applications, Oracle Cloud CX is designed to connect data and workflows across all departments that interact with customers, including sales, marketing, and service.
One of the advantages Oracle enjoys is its ownership of the entire technology stack, from the compute used to train AI models and handle inference tasks, to the models themselves, and, of course, all of the applications that are embedded with AI. This enables Oracle to tightly manage and optimize the performance of its generative AI models, while addressing the backend cost structure, particularly as generative AI use scales up.
More importantly, Oracle’s control over the entire stack will help the company deliver as it continues to deepen its push into specific verticals. For example, regulated industries such as healthcare require a streamlined and efficient platform to deliver ROI while adhering to increasingly stringent regulations.
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.
