In her presentation, “Demystifying Generative AI and Its Benefits for Business,” Natalia Rachelson, Oracle’s Group Vice President of Applications Development, laid out a compelling vision for the role of AI in driving business transformation. Rachelson underscored Oracle’s commitment to innovation by setting the stage with a key message: in a world filled with unpredictability, businesses need advanced tools to stay agile and ahead.
Why Oracle’s AI Leads the Market: Data, Technology, and Agility
Generative AI is all about content creation. This created content is produced in a wide range of formats, such as texts, charts, and explanations. Over time, the number of potential formats will only grow, but AI is not just about creating content. Instead, it is about creating content that is meaningful and relevant. This is one thing that sets Oracle’s generative AI apart from something like ChatGPT. If you are working within Oracle, you will get hyper-relevant results. As Rachelson noted, Oracle focuses on pace of change acceleration to allow customers to accomplish more in a highly uncertain world.
In 2017 and 2018, Rachelson stated Oracle’s customers’ key concern was the idea of disruptions, such as how Amazon and Uber were transforming the business landscape. Faced with uncertainty and disruptions, businesses recognized they must be ready and able to pivot to respond to potential threats. Seeing this, Oracle stepped up and demonstrated they would provide the technology and tools customers needed to adapt.
What sets Oracle’s AI Apart
Rachelson presented a clear argument for what makes Oracle’s AI the best on the market —combining the best data and the best technology. She emphasized Oracle’s longstanding expertise in data, underscoring its robust capabilities in data management. Oracle leads with purpose-built AI infrastructure, rich data sources, and sovereign solutions, all designed for superior performance. Its cloud architecture also stands apart from competitors, with a key advantage being Oracle’s agility in adapting and evolving its technology to consistently deliver top-tier results.
All of that adds up to the best AI. Features of Oracle’s AI include out of the box features to speed up adoption, guardrails for improved accuracy, and diligent human oversight. As Rachelson conclusively stated, Oracle does not price differently for “dumb” versus “smart” systems, because Oracle believes everyone deserves access to smart systems.
A key part of this new and improved toolbox was Fusion Cloud applications. Even if Oracle cannot predict the next big shock to the system, Fusion Cloud allows businesses to absorb and then address these shocks. Given this capability, it should not be surprising an impressive roster of companies, including the Mayo Clinic, Uber, Zoom, and Hilton, signed up for Fusion Cloud services.
While many companies address AI in a piecemeal fashion, Oracle takes a comprehensive, four-pronged approach. First, it integrates AI directly into existing workflows to accelerate adoption and enable users to quickly experience its benefits. The second step involves ongoing performance monitoring, measurement, and refinement. Next, Oracle provides continuous improvements, typically each quarter, with real-time updates when possible. Finally, Oracle’s strategy includes extensibility, allowing the technology to adapt and scale for new use cases as they arise.
Customer Success with Oracle AI
Rachelson also detailed customer success stories. For example, Western Digital dramatically improved its ETA accuracy, Kroger used AI to increase candidate to applicant conversion, and Aon now predicts opportunity-to-win conversion with lead scoring.
After presenting these success stories, Rachelson highlighted a wide range of classic AI features in supply chain management (SCM), as well as customer experience (CX) and enterprise resource planning (ERP).
Generative AI is useful for SCM in producing negotiation summaries and supplier recommendations, and Rachelson also noted it can generate item descriptions — something that many business owners may struggle with. In CX, AI enables capabilities like fatigue analysis and intelligent shift management. Rachelson highlighted preparing sales content, creating interview content, and offering recommendations for marketing collateral. ERP key AI features include dynamic discounting and predictive cash forecasting, including creating financial reporting narratives and predictive forecast explanations.
Rachelson also added how AI can be beneficial in the human capital management (HCM) sphere, by drafting job postings, creating goals, and writing up performance review summaries.
In addition to walking listeners through these different examples, Rachelson presented several different simulations that showed what actual generative AI would look like.
Afterwards, she offered words of wisdom to companies just beginning to embark on their generative AI journey. As she articulated, companies need to think big and bold, tempering that by starting small, but stay ready to move extremely quickly.
To view Natalia Rachelson’s full presentation, please watch the recording from BLUEPRINT 4D 2024.