An Episode and Article in the EPM Intelligence Oracle AI World Series featuring Chris Muli (GVP, Presales at Oracle) and Kaci Coble (GVP, Sales at Oracle).
Key Takeaways
- Predictive, generative, and agentic AI unlock unique use cases across planning, reconciliation, narrative reporting, and cross-department automation.
- Oracle’s competitive advantage: activate AI in minutes, not months. AI built directly into Oracle Cloud EPM allowing customers to scale capabilities quickly, and Oracle’s extreme attention to detail when it comes data security.
- AI will redefine finance roles. By automating manual tasks, AI enables finance teams to spend more time on strategic conversations, decision support, and partnering with the business.
AI’s Real Impact: Transforming EPM Implementations
Many organizations still feel pressure to implement quickly, which often results in simple lift and shift deployments. Kaci explains that AI can change this dynamic entirely. By using internal chatbots to consolidate requirements, highlight priorities, and spot gaps, teams can align more efficiently and design solutions that accelerate the entire implementation lifecycle.
“I think what AI is going to do for implementations is going to be really exciting… especially from a speed and efficiency perspective.”
— Kaci
Teams can now focus on the advanced analytics they’ve always wanted to deliver, but never had time for.
Understanding the Three Types of AI in Finance
To frame the role of AI in finance, it helps to distinguish between deterministic AI, which focuses on numerical accuracy, and generative AI, which produces text-based insights.
Chris and Kaci build on this foundation by exploring three types of AI that give finance teams a clear understanding of where to start and how to scale.
You do not need to adopt all three at once. Beginning with one clear use case specific to your business is far more effective than attempting to deploy every capability at once.
1. Predictive AI
Machine learning algorithms that identify patterns, trends, and forecasts.
Use cases include:
- Auto Predict forecasting
- Rolling forecasts
- Back-testing accuracy
2. Generative AI
Text-driven insights and narrative explanation:
- Narrative reporting
- Variance explanations
- Automated commentary
3. Agentic AI
Systems that act on behalf of users, not just answer questions:
- Workflow actions
- Cross-department orchestration
- Multi-step analytics execution
Oracle’s AI Advantage: ‘Built-In, Not Bolted-On’
Oracle’s approach to AI stands out because, rather than relying on an external integration, Oracle includes AI capabilities directly inside its EPM and ERP platforms.
Built-In AI Means:
- No external data movement
- No third-party model hosting
- No bolt-on connectors
- No new security risk
Chris and Kaci explain that Oracle leverages leading models such as Cohere and OpenAI, but delivers them through Oracle Cloud Infrastructure.
Turning on Oracle AI in Minutes: No Implementation Required
One of the most striking moments from the conversation is the example of a customer who enabled Oracle’s generative AI and saw results in 47 minutes!
Since the data, metadata, and security already exist within Oracle Cloud EPM, AI is able to deliver immediate value without any new implementations.
Asking Better Questions: How Finance Leaders Unlock AI Insight
Chris and Kaci highlights an important shift in how finance teams should think about AI. Many people already use AI at home for simple questions, yet struggle to translate that into the workplace. The quality of insight depends on the quality of the question.
Examples of strong finance prompts:
- “Explain the variance in OPEX at a freshman-college level and show the top 3 drivers.”
- “Identify anomalies in revenue by region and provide both sides of the trend with supporting data.”
- “Summarize insights and recommend corrective actions.”
Finance is shifting from creating analysis to shaping the insights AI produces.
AI Security: How Oracle Protects Your Data
Data privacy remains one of the most common concerns among finance leaders. Oracle addresses this with a design that keeps all customer data inside the secure cloud environment. The models do not train on customer data, and no information is shared outside the Oracle boundary.
“We do not mix your data with any public data.”
— Chris
This approach provides confidence for highly regulated industries and supports the governance standards that finance teams expect.
AI and the Future of Finance: A Shift Toward Strategic Work
Instead of spending time on reconciliations, variance analysis, or the creation of narrative reports, finance teams will be able to redirect their energy toward strategic conversations and business collaboration.
AI automates the tasks that have historically taken hours, which opens time for deeper collaboration and faster decision making.
“Six hours of work becomes six seconds. The value becomes the conversations that follow.”
— Chris
The result is businesses that are more proactive, more engaged with operations, and more connected.
EPMI’s Key Insights
AI, ERP, and EPM are reshaping enterprise performance by moving intelligence directly into the systems where decisions are made. The challenge is not the technology. The challenge is knowing where to start. AI is not replacing finance teams. It is enabling them to contribute at a higher level than ever before.
At EPMI, we help organizations start with clear goals, unify their data, and empower leaders to make better business decisions using Oracle’s built-in AI and enterprise solutions.
FAQs
1. Does Oracle AI require a new implementation?
No. Most features activate directly inside Oracle Cloud EPM, often within minutes.
2. Will Oracle AI train on customer data?
No. Customer data stays within a secure cloud environment and is never used to train public models.
3. How do predictive, generative, and agentic AI differ?
Predictive identifies patterns and supports forecasting. Generative produces narratives and insights. Agentic takes action and orchestrates processes across different functions.
4. Where should finance teams begin with AI?
Start with a clear outcome and a manageable use case such as predictive forecasting or anomaly detection. Small wins create momentum for broader adoption.
5. Will AI replace finance roles?
No. AI automates manual tasks so finance teams can focus on analysis, decision support, and stronger collaboration with the business.
Watch the AI World Series on YouTube!