Extend AI through measurable business outcomes
Christine Sarros, Senior Vice President, Oracle
Christine Sarros is a senior vice president in Oracle’s Enterprise Engineering organization, responsible for delivering cutting-edge IT services to more than 170,000 employees worldwide. Christine has 25 years of experience as a leader in Fortune 500 technology organizations and currently leads a team of 1,500 global staff within the Oracle Cloud Infrastructure organization. Currently, Christine is leading efforts to find AI solutions for enterprise search and support, and companion assistants for secure development and operations functions. She is an active member of the Oracle Women’s Leadership community, whose mission is to develop, engage, and empower current and future generations of women leaders.
Focus on big results
New technologies are emerging all the time. How do you separate actual value from hype?
Any new technology can be oversold, and AI is no exception. I start by developing clear and desired business outcomes. If you think about engineering and automation since the Industrial Revolution, the goal has been to establish a baseline for end-to-end processes and align them with the outcomes you want to achieve. Then ask if there is already a process that provides some of that, or if you need to build it from scratch. From there, I identify high-impact use cases and prioritize those with volume and clear ROI that drive customer success. Value can be efficiency, simplification, innovation, etc., but it needs to be measurable.
Then look at where the data resides, how it can be accessed and distributed, and how process and technology components work together to produce results. Security and governance are essential, and a secure, unified data core is a key enabler.
This approach allows you to see how much work already exists in the process and how much work needs to be introduced. Also clarify which technologies will be combined, whether that means using existing systems in new ways or tweaking new systems that include standalone AI components.
Any new technology can be oversold, and AI is no exception.
Scaling technology across large organizations is a difficult task. How does Oracle approach this?
We build for scale and flexibility. Data center options consider data residency and offer both commercial and sovereign platforms. Customers can also keep their data on-premises. Internally, we set minimum and maximum thresholds and plan for multiple years. My basic principle is to assume that everything I build needs to run at maximum capacity. I consider availability and resiliency requirements, and consider whether the service is Tier-0 or a lighter service, such as a biweekly reporting service. Set the investment level according to the nature of the service.
Running on the cloud allows you to scale up and down quickly so you don’t have to reinvent the wheel. You can plug and play many Oracle services. If some of your applications or business data is on Azure or GCP, you can connect using multicloud options. Easily deploy new Oracle databases by adding new AI-integrated Oracle databases and tying them into those environments.
We build for scale and flexibility.
AI behavior:
How are you using AI in your internal operations at Oracle?
We started with low complexity use cases. As an example, at our AI service desk, an intelligent chatbot is integrated into our direct messaging system for employees to use when they experience issues such as not being able to connect or their laptop freezing. Achieved 48% ticket deflection with very high monthly volume.
Most interesting is the reasoning ability of generative AI. [Gen AI]. We use the resulting data to identify faults in the system. AI recommends what to prioritize and suggests potential root cause fixes, so you don’t just avoid tickets, you aim to avoid or permanently resolve issues. This improves process efficiency over time and allows engineering teams to focus on innovation rather than extensive manual analysis and basic root cause corrective actions.
The goal is to be proactive. By proactively recognizing patterns in your data, you can proactively prevent customer impact. AI can also help uncover these patterns from an analytical perspective and generate code to solve the problem. That’s what I’m most excited about.
Our AI service desk achieved 48% ticket deflection at extremely high monthly volumes.
Where do you see the greatest business value from AI?
We see clear value in our SaaS [Software-as-a-Service] fusion platform.
- supply chain: In Fusion Cloud SCM, AI capabilities combine internal and external signals, historical patterns, real-time market changes, and simulations to help predict demand. Reduced some supply chain planning cycles by 70%.
- finance: In ERP [enterprise resource planning]Close the books and announce earnings within 10 days. That’s nearly 60% faster than most organizations our size.
- human resources: With faster onboarding, new employees are more productive from day one. Full system access now takes approximately 24 hours from offer
These results come from orchestrating systems with AI that drives CTA activities. The reasoning element of automation identifies what should happen next across backend systems. As the model learns, the process becomes more efficient.
In ERP [enterprise resource planning]Close the books and announce earnings within 10 days. That’s nearly 60% faster than most organizations our size.
With so many AI use cases gaining traction, how do you decide where to invest and how to deploy?
I always start with step 1. That means defining measurable business outcomes. AI-generated meeting notes and email drafts are interesting, but they become even more valuable when connected to real-world workflows. For example, you can associate your inbox with relevant documents, automatically update tickets, send action items, and trigger code changes.
Then match that complexity to your goals. If the process is mature, low-complexity improvements can be made quickly. If the goal is to do something new, we discuss the relevant data and systems and iteratively build towards that goal. It doesn’t have to be a “big bang”. Starting with Service Desk ticket changes, you can associate device history and enable automatic remediation. Inferential analysis can reveal where efficiency and innovation have the highest returns.
This is basic agile. Act quickly, iterate, and demonstrate incremental value in small scales rather than long waterfalls that can miss the mark. Most large companies have vast amounts of data, so just organizing the data is a worthwhile exercise to test and improve. Oracle products have built-in database and AI components, as well as optional add-on AI services, so you don’t need to be an AI expert to design your solution. We offer options based on the outcomes you are trying to achieve.
Sovereign cloud and multicloud:
How do you manage data sovereignty? What should organizations consider?
Our strategy is to maximize flexibility for our customers. This means running in a specific country, in your own data center, in a sovereign or dedicated model, or in a multi-cloud setup. Dedicated regions allow you to operate the complete Oracle Cloud platform within your data center with a small, scalable footprint starting from 3 racks, which is useful if you need a small deployment. If you want just what you need, products like Exadata Cloud at Customer provide certain cloud database capabilities on-premises.
As regulations evolve, we also support government cloud options and air-gapped isolated regions. It’s not one-size-fits-all. Many organizations use multiple models simultaneously. Some workloads run well in commercial regions. Others require sovereign or dedicated deployment. Some must satisfy FedRAMP type isolation. The goal is that our products run consistently across platforms, so you don’t need special builds when choosing the right model for each workload. Start with regulatory, residential, and operational requirements to choose the best combination for each application. As rules change globally, we continue to invest in keeping these options up to date.
Multicloud can be powerful, but it can also be complex. What does your approach actually mean for your clients?
Our goal is to make multicloud as simple as possible. Our database services run on OCI and are available directly in our partner data centers. If a customer already has an Oracle database on OCI, they can tie it to a backend service on AWS, Azure, or Google Cloud. If you want to move something from these clouds to an Oracle database, you can do that too. Simplified management through the console allows cloud operators to manage resources across their environments without worrying about the complexity of the underlying architecture.
Looking forward to:
What do you think a CXO should focus on?
AI is changing the way every industry and job operates, but the data behind it is at the heart of economic growth. Today’s organizations must adapt to the volume and velocity of data so that businesses can make informed, data-driven decisions, create new products and services, sustain innovation, and gain real-time insights into customer behavior, market trends, and operational efficiency.
For us at Oracle, our top priority is getting the most out of our cloud platform. We run Oracle on top of Oracle whenever possible. Additionally, we partner with strategic providers. For example, we use Zoom alongside our contact center so we can combine our own CX. [customer experience] Best practices for the contact center component of the Zoom system. The common theme is connecting secure data across platforms to truly understand your customers, provide them with the services they need, and help them grow their own businesses.
AI is changing the way every industry and job operates.
AI is changing the power of software engineering and CIOs. How do you think the role of the CIO will evolve over the next few years?
I’ll summarize it in two basics. First, understand the data. This means core business data and required external data, where that data resides, and the governance and security around it. Then make that data accessible in an extensible environment. The cloud is ideal for this, with options to meet your regulatory and security needs, including sovereign and isolated models.
From an AI perspective, decide how much to consume now and how much to add as a standalone AI component. When AI first appeared, it ran on several platforms. Many products now have AI built into their platforms, and additional AI can be configured as needed. Oracle supports that choice with strategic partnerships including NVIDIA, offering a large selection of language models. [LLMs].
By integrating with the cloud and modernizing your operating model, you can turn cost savings from traditional on-premises sprawl into agile innovation. That innovation could be new AI or new capabilities for a specific business segment. The question for every CIO is whether the way they have operated over the past decade can keep up with the evolution of the industry. The flexibility of the cloud, combined with clear, business-driven, and measurable AI outcomes, helps customers move forward.
The question for every CIO is whether the way they have operated over the past decade can keep up with the evolution of the industry.
