Agentic AI Industry & Department Adoption Patterns:
Organizations across industries such as Finance, Manufacturing, Logistics, Healthcare, and Retail are adopting Agentic AI to automate decisions, improve operational efficiency, and enhance customer experiences. The strongest use cases focus on monitoring, document processing, workflow automation, and intelligent decision support.
Departments including Finance, HR, Procurement, IT, Supply Chain, and Customer Service use Agentic AI to automate repetitive tasks, accelerate workflows, and improve productivity. Oracle Integration provides the governance, connectivity, and orchestration needed to safely connect AI agents to enterprise systems and business processes.
Key takeaway: Industry adoption focuses on solving sector-specific business challenges, while department adoption targets functional processes that exist across nearly every organization. Together, they provide a practical roadmap for scaling Agentic AI from individual use cases to enterprise-wide transformation.
Get the pattern papers by department here and by industry here.
Rapid Prototype workshop Agentic AI Oracle Integration
Discover how Agentic AI can transform your business with Oracle Integration in this interactive three-day workshop. Working alongside Oracle AI and integration experts, you'll explore real-world use cases, learn proven design patterns, and gain hands-on experience building intelligent AI agents.
Together, we'll validate your business use case, develop an initial proof of concept, and provide practical guidance on architecture, best practices, and next steps. By the end of the workshop, you'll have a clear roadmap and a working prototype to accelerate your Agentic AI adoption and deliver business value faster. The workshop kit is available here.
As part of the workshop, Oracle can support your go-to-market strategy by:
• Providing Oracle experts as speakers for customer and industry events.
• Collaborating on joint promotion activities to showcase your Agentic AI innovation.
• Aligning Oracle and customer sales teams to identify opportunities and accelerate customer engagements.
• Developing customer success stories, webinarse and executive briefings to help drive adoption and business value.
Interested to offer this workshop to your customers please contact myself.
What’s New in Oracle Integration 26.07 by Niall Commiskey
Introduction
Building on the power of AI that we already have in OIC is still a big focus for this release.
Disclaimer: This is a working document, please revisit this page closer to the actual 26.07 release for possible updates.
AI Features Released in 26.07
AI Assistant
This release brings several meaningful improvements to the AI Assistant, focused on simplifying integration development, improving performance, and expanding availability.
The features released include the following:
Leveraging OIC Design Best Practices
With the 26.07 release, developers can use the assistant to validate whether they are adhering to OIC design best practices. If they are not, the assistant will deliver the relevant guidelines. In some cases, the assistant will offer the option to directly apply its recommendation(s).
New Adapters and Connectivity Enhancements in Oracle Integration 26.07 by Madhav Poosarla
Oracle Integration continues to advance intelligent automation and enterprise connectivity with this release, delivering enhancements across adapters, native actions, AI workflows, security, and cloud connectivity. This update focuses on helping customers build integrations that are more flexible at runtime, easier to move across environments, and better aligned with modern authentication, private connectivity, and cloud interoperability requirements.
With this release, Oracle Integration improves several common integration patterns, including event-driven processing, schema-based messaging, temporary data reuse, dynamic payload handling, intelligent search, document-processing workflows, and API resilience. These enhancements help reduce custom logic, minimize design-time reconfiguration, and make integrations easier to maintain as business applications, payload structures, and deployment environments change.
New Adapters
• OCI Cache Adapter – New adapter providing connectivity to OCI Cache clusters with support for string and list operations, TTL-based caching, key existence checks, private endpoint connectivity, and key prefix strategies.
• Azure Synapse Database – Microsoft SQL Server Adapter-certified to integrate with Azure Synapse.
Processing Comma-Separated Lookup Values in Oracle Integration Cloud Using the Functions Library by Devkiran Tomar and Madhav Poosarla
Abstract
In Oracle Integration (OIC), lookup values are usually treated as single values, even when a lookup field contains multiple comma-separated entries.
This article shows a practical way to split and process those values individually by using oraext:create-nodeset-from-delimited-string() XSLT. With this approach, you can convert a comma-separated string into iterable XML nodes and process each value sequentially in a For-Each loop.
Key Takeaways
• Process multiple values stored in a single lookup column.
• Convert a comma-separated string into iterable XML nodes.
• Use oraext:create-nodeset-from-delimited-string() in OIC mappings.
• Implement dynamic For-Each processing in OIC.
• Reduce hardcoding and improve reusability in integrations.
Introduction
OIC lookups are commonly used to externalize configuration and avoid hardcoding values inside integrations. However, a challenge arises when a single lookup field contains multiple values that need to be processed one by one. For example, a lookup may store the following value:
Abstract
In Oracle Integration (OIC), lookup values are usually treated as single values, even when a lookup field contains multiple comma-separated entries.
This article shows a practical way to split and process those values individually by using oraext:create-nodeset-from-delimited-string() XSLT. With this approach, you can convert a comma-separated string into iterable XML nodes and process each value sequentially in a For-Each loop.
From Headset to ATP: How OIC Turns Support Calls into Searchable Knowledge by Biman Sarkar
Introduction
Every support call your team handles is a small goldmine. A customer describes a real-world problem in plain language, an agent troubleshoots it live, and a resolution emerges. Then the call ends, and most of that knowledge evaporates. At best it survives as a few terse lines in a ticket; at worst, it is gone the moment the headset comes off. What if every call automatically became a clean, timestamped, speaker-separated transcript, written straight into Oracle Autonomous Database (ATP), ready to power semantic search or ground an OCI Generative AI Agent for Retrieval-Augmented Generation (RAG)?.
This is where Oracle Integration (OIC) earns its keep. OIC is the engine that makes the whole thing effortless: it takes a recording sitting in object storage, hands it to OCI AI Speech to convert speech into text, waits for the transcription to finish, retrieves and decodes the result, and lands a clean transcript in ATP, end to end, in one low-code flow. No functions to deploy, no servers to manage, no glue code to maintain. You build it once, visually, in the OIC canvas, and every call from then on transcribes and stores itself.
That is the Voice-to-Service pattern: OIC orchestrates the entire flow using its embedded actions for OCI AI Speech and OCI Object Storage, alongside adapters such as the ATP Database Adapter. Building on the same agentic foundations described in the Agentic AI in Oracle Integration and OIC Knowledge Base blogs, Voice-to-Service shows how a single OIC integration turns raw audio into a living, self-updating knowledge layer for your support organization.
Connecting Oracle AI Data Platform Agent Flows to OIC MCP Tools for Enterprise Automation by Sandhya Lakshmi Gopalan
Oracle AIDP enables agent flows that reason over governed enterprise data. Oracle Integration Cloud extends those flows by exposing integrations as governed, callable MCP tools, allowing agents to take controlled, policy-aware, and auditable actions across Oracle and non-Oracle enterprise applications and systems.
What Is Oracle AIDP?
Oracle AIDP provides the foundation for building enterprise agent flows that are grounded in trusted data and governed business context. Rather than treating AI agents as standalone assistants, AIDP enables them to reason over enterprise data, apply business rules, make policy-aware decisions, and invoke tools to complete business workflows.
AIDP is built around a governed data foundation. Using a medallion-style architecture, data can be organized across Bronze, Silver, and Gold layers. Bronze preserves raw, source-aligned data, Silver applies cleansing and standardization, and Gold exposes curated, business-ready data products for consumption by analytics, applications, and agent flows.
This is where Master Catalog plays an important role. Master Catalog helps agents and users discover trusted enterprise context across structured and unstructured sources without requiring unnecessary data replication. Structured data such as purchase orders, suppliers, invoices, and finance records can be cataloged alongside unstructured content such as policies, contracts, SOPs, and documents. The data can remain where it lives, while Master Catalog provides the governed discovery, metadata, lineage, and access context needed to use it responsibly.
Together, the medallion architecture and Master Catalog help AIDP give agents access to trusted data products and contextual knowledge. Instead of every agent flow building direct integrations into raw systems, agents can reason over governed, reusable enterprise context before taking action.
This makes AIDP more than an agent orchestration layer. It becomes a governed data and agent platform: one that connects trusted enterprise knowledge with policy-aware agent flows and controlled tool execution.
Why OIC MCP Tools Matter
AIDP agent flows can reason over enterprise data and decide what should happen next. But for agents to create real business value, they also need a governed way to take action in enterprise systems.
This is where Oracle Integration Cloud plays an important role. OIC acts as the action layer for AIDP agent flows. The agent flow can evaluate context, apply decision logic, and determine the next step, while OIC executes the actual enterprise action through integrations.
SOA Suite on Docker, Part 1: Now Certified, Even Without Kubernetes by Johannes Michler
A while back I wrote a blog series on running Oracle SOA Suite in Docker, starting with a high-level overview and working through setting up a host, a database, a SOA environment, and finally patching. Later I followed up with the 14c edition (SOA Suite 14c on Windows with WSL2 in ten minutes), an Apple Silicon edition, and a post on Docker Compose for SOA Suite.
This new mini-series is the production payoff of all of that. I recently moved a customer from SOA Suite 12c to 14.1.2, not as an in-place upgrade but as a fresh, fully containerized 14c deployment that we cut over composite by composite. Everything runs in plain containers on a single host per environment, with no Kubernetes anywhere in the picture.
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