---
title: "Oracle AI World 2026 Shows AI Shifting From Insight to Action in Enterprise Workflows"
slug: "oracle-ai-world-2026-shows-ai-shifting-from-insight-to-action-in-enter"
date: "2026-11-11"
category: "Business & Society"
author: "Helena Ross"
correspondent: "Helena Ross"
correspondentRole: "Strategic Think-Tank Curator"
readingTimeMinutes: 3
tags: ["News"]
originalSourceUrl: "https://www.forrester.com/blogs/oracle-ai-world-2026-ai-moves-from-insight-to-action/"
canonicalUrl: "https://aurav.ae/oracle-ai-world-2026-shows-ai-shifting-from-insight-to-action-in-enter"
publisher: "Aura-V Intelligence (aurav.ae)"
---

# Oracle AI World 2026 Shows AI Shifting From Insight to Action in Enterprise Workflows

> Oracle presented Fusion as a governed layer for AI agents that act on business context and execute work across systems.

## Key Takeaways (TL;DR)

- Fusion is positioned as the authority layer that gives agents context, identity, permissions and guardrails.
- OCI’s accelerator lineup now spans NVIDIA, Google, Cerebras, AMD and SambaNova, with some chips slated for 2027.
- Customer pilots highlight sub-5-second response needs, the move from fraud detection to payment blocking, and faster name-check runtimes.

Oracle AI World 2026 highlighted a strategic shift from AI-driven insight to AI-driven action, with CEO Mike Sicilia stating the goal is “making your business capable of doing more” [Forrester](https://www.forrester.com/blogs/oracle-ai-world-2026-ai-moves-from-insight-to-action/). The company showcased Fusion as a governed authority layer that supplies agents with business context, identity, permissions and guardrails, enabling autonomous tasks such as field-service truck rolls and nurse scheduling while keeping finance processes under human approval.

### Oracle Fills Out The Agentic Stack
Oracle is tackling a fundamental problem with enterprise agents: they need more than an LLM to do real work. Fusion Claw provides a governed runtime for agents to execute tasks; Fusion Companion gives employees a natural-language interface for getting work done; and enterprise ontologies map the relationships, policies, processes and actions that agents need to understand the business. Agents receive task-limited identities and human verification for sensitive actions, rather than inheriting a user’s credentials. Autonomy is matched to risk: the truck-roll and nurse-scheduling demos ran fully autonomously, whereas finance scenarios still required human sign-off.

### AI Infrastructure Gets More Diverse
Oracle expanded Oracle Cloud Infrastructure’s AI compute roadmap with a growing range of accelerators aimed at different AI workloads:

- **NVIDIA Vera Rubin NVL72** – frontier-model training, high-throughput inference and agentic AI systems
- **Google TPUs** – an alternative to GPUs for large-scale training and production inference (expected on OCI in 2027)
- **Cerebras CS-3** – extremely low-latency inference and reasoning workloads (expected on OCI in 2027)
- **AMD Instinct MI455X GPUs and EPYC CPUs** – rack-scale AI infrastructure for performance- and cost-sensitive workloads
- **SambaNova SN50** – inference-focused specialized architecture

The broader point is that no single accelerator will suit every workload; training, reasoning, real-time inference and agentic workloads have distinct requirements. Oracle’s advantage is expected to come from offering diverse compute architectures tied together by a high-performance network fabric.

### Customers Put The Technology In Context
External presenters provided concrete reality checks:

- Fabio Fazzino and Sophie Buresi of QSRP, whose platform includes Burger King Italia, described agents that identify product shortages, unusual transactions and delivery problems. Their lesson was practical: “The hard part is not AI.” The challenge is turning an AI-generated insight into something an operations employee can understand and act on in **5 seconds**, while building enough trust for adoption.
- At the Centers for Medicare & Medicaid Services, Jeneen Iwugo explained that roughly **300 AI models** are used to find patterns and identify potential fraud in Medicare. The ambition is to move from flagging suspicious activity to **recommending action and eventually stopping questionable payments before the money goes out**.
- Hetal Doshi of the U.S. Department of State illustrated scale: the agency processes roughly **100,000 passports daily** across more than 270 locations. Modernization efforts have helped **some name checks return 50–60 % faster** and have cut **some runtimes roughly in half**.

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*Original Think-Tank Source: [Oracle AI World 2026: AI Moves From Insight To Action](https://www.forrester.com/blogs/oracle-ai-world-2026-ai-moves-from-insight-to-action/)*