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Oracle Artificial Intelligence Blog

Learn About Oracle's Artificial Intelligence Strategy

Justin Charness
Director, Product Marketing- Oracle AI

Register for our webinar to learn about Oracle’s AI strategy and product offerings and find out why Oracle is the right partner to guide your journey with AI.

 

There are no shortage of statistics to show that artificial intelligence (AI) and machine learning (ML) can add tremendous value to businesses. It is one of the most transformative technologies of our time, and a number of enabling technologies like cloud computing, a proliferation of open source tools, and the availability of data sources are making AI more accessible to organizations big and small.

Despite the much-acclaimed business opportunities of AI, organizations vary greatly in terms of their AI maturity and how much value they’re seeing from AI. Some organizations are just getting started and may have one or two data scientists supporting their business, while other organizations have hundreds of data scientists and agile methodologies for delivering AI-powered applications across global functional teams.

Regardless of an organization’s maturity, the common challenge emerges of how to accelerate AI adoption to increase revenue, improve operations, and beat competitors. There are an ever-growing number of use cases where AI can and should be applied, but real barriers exist to tackling more use cases faster in a scalable matter. According to a recent study conducted by McKinsey, among the top 5 most cited barriers to artificial intelligence adoption were a lack of clear strategy for AI (43%), a lack of talent with appropriate skill sets for AI work (42%), functional silos constraining end-to-end AI solutions (30%), and a lack of technology infrastructure to support AI (25%).  Building AI capabilities that scale is not a one size fits all approach and every organization must approach AI with a clear strategy for operations in addition to investments in talent and technology.

 

So where does Oracle come in?

 

For over 40 years, Oracle has helped the largest organizations around the world manage and get value from their data. Companies have been doing machine learning on Oracle databases for a very long time, and Oracle has been fortunate to witness machine learning evolve from it's use primarily in research settings to a widely adopted technology that will fundamentally change virtually every company on earth. As demand for artificial intelligence and machine learning has exploded, we’ve worked very closely with our customers to listen to their challenges and identify how we could help them drive more business value with AI.

Through these conversations, three strategic areas emerged to help our customers accelerate AI adoption.

First is with business teams, who are oftentimes the consumers of AI. These are marketing managers, human resources managers, and financial analysts, to name a few. The challenge for business teams is that AI is oftentimes not accessible to them in a way they can use or understand. For example, a marketing manager can spend weeks or months with data scientists and developers building a custom application to identify customers who will churn, but if it’s not something they can understand or use, if it’s not integrated in a way that’s familiar to them, then it will sit on the shelf and be of no value.  Oracle is #1 in business applications and is uniquely positioned to address this challenge- by building AI capabilities into our SaaS applications which business teams are using every day, whether that’s ERP, EPM, HCM, CX, or SCM. This approach enables business teams to reap the benefits of AI in a way they can use, and that’s familiar to them, without having to rely on scarce data science talent build solutions from scratch.

The second area of opportunity is with data and platform teams. Building AI-powered solutions is a team sport, and the tools and workflows and processes for building AI-powered solutions are simply not efficient. We’re not just talking about inefficiencies in the data science and the modeling workflow, but across the lifecycle- getting access to the right data, managing that data, deploying models into production, etc. Oracle takes a holistic view here- we view the opportunity as making it easier and more efficient for everyone involved in building AI-powered solutions- not just data scientists, but also data engineers, IT, and application developers.

The final area of opportunity is with Oracle’s own cloud services. Oracle is continually striving to set a new standard for performance, security, and innovation in our cloud services and to provide the best possible products for our customers. We view our opportunity here to embed machine learning in different services to provide our customers with new capabilities that help them do their jobs more effectively, while automating and optimizing underlying operations so they can save time and money while reducing risk.

So how are we addressing these three areas to help our customers accelerate AI adoption?

 

Oracle AI is ready-to-go, ready-to-build, ready-to-work.

 

Oracle AI Strategy

 

Ready-to-go refers to the AI capabilities we’re building into our SaaS applications. This is AI that’s business focused and designed to help business teams get value from AI without relying on data scientists and developers to build custom solutions from scratch. For example, our CX suite uses AI to guide sales reps to opportunities with the highest win probabilities and our HCM suite uses AI to identify the best-fit candidates for roles. These solutions help our customers save development resources while giving business teams AI they can use and get value from on day 1 in the tools they’re already using.

Ready-to-build refers to our AI Platform- a collection of services to rapidly build, deploy, and manage AI-powered solutions. The platform consists of best in class services for every step in the AI development lifecycle, from data integration to data science, to application development. The platform leverages Oracle Cloud Infrastructure which provides a range of high performance compute shapes, fast networking speeds, scalable independent storage, modern architecture, and competitive pricing, making it an ideal infrastructure platform for AI workloads in the cloud.

Ready-to-work refers to our strategy of embedding ML in our cloud services, most notably our Autonomous Database- which sets a new standard in the category as the world’s first fully autonomous database. The database uses machine learning in three key areas of the database: diagnostics, recovery, and optimizations for each layer of the deployment stack.

Oracle’s approach to AI is unique in the market in that its geared towards both business users and those building AI. By providing robust pre-built AI solutions for business teams, a unified platform for AI solution development, and fully autonomous cloud services, organizations can overcome traditional barriers to getting value form AI, no matter where they are in their AI journey.

Register for our webinar to learn more about Oracle’s AI strategy and product offerings and why Oracle is the right partner to guide your journey with AI.

Click here to learn more about Oracle’s AI products and services.

 

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