Page 155 - Red Hat PR REPORT - OCTOBER 2025

10/7/25, 1:53 PM Latest News
Real-World Applications: Regional Case Studies
Two very different sectors point to the same conclusion: open, private AI is delivering hard business wins.

At DenizBank, Intertech standardized a private, container-based AI stack and gave 120+ data scientists self-serve workbenches. Time-to-market for new models dropped from about a
week to ~10 minutes, while GPU “slicing” curbed accelerator waste. Crucially, teams now push core banking models—credit-risk scoring and fraud-anomaly detection—into production
fast enough to influence real-time decisions.

In energy, Aramco’s Upstream Digital Center built a GenAI foundation running inside its own environment to centralize resources and streamline upstream workflows. Drill and plant
engineers complete routine analysis up to 10× faster, saving roughly two hours per person per day, and new models are onboarded in under an hour—time that goes back into
subsurface modeling, drilling optimization, production monitoring, and other high-value tasks. The firm also applies AI to operational risks such as flaring prediction and component-
failure detection to keep output efficient and equipment online.

Across banking and oil & gas, the pattern is consistent: open tooling plus private deployment = faster model delivery, tighter governance, and measurable productivity gains.

In Saudi Arabia, Aramco is another important government entity that is utilising AI for complex geological surveys.

A Glimpse into the Future: Agentic AI

Perhaps the most exciting frontier is agentic AI, a paradigm shift from today’s prompt-response models to autonomous agents capable of interacting with enterprise applications to
complete full workflows. Imagine an AI agent that not only answers queries but automatically updates Salesforce entries, reconciles invoices in SAP, or schedules meetings based on
real-time availability. Unlike external SaaS-based assistants, agentic AI built in-house can be tightly integrated with internal systems, enforcing strict access controls, data privacy, and
auditability.

Companies are already investing in this future through open frameworks like MCP (Model Context Protocol) and the Llama Stack, designed to empower enterprises to develop fully
autonomous, auditable AI agents.

A Call for Strategic Ownership

For enterprises and governments in the Middle East, the AI opportunity is immense but only if pursued with a long-term vision. Building AI in-house by utilizing open source is no longer
a luxury, it’s a strategic necessity as it ensures control, fosters innovation, and safeguards data, which is the foundation of the digital economy.

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