As enterprises across Saudi Arabia and the wider GCC accelerate their digital transformation journeys, the conversation around cloud adoption has shifted decisively from if to how fast, and how intelligently. According to Rajan Krishnan, Group Vice President, Oracle Product Development, the drivers behind Oracle Fusion Cloud Applications adoption in the region are pragmatic, business-led, and increasingly AI-centric.
Cloud first, because business comes first
For many organisations in the Middle East, the starting point remains the same: the growing burden of on-premise environments. Maintaining legacy systems, managing upgrades, patching infrastructure, and operating private data centres have become distractions from core business priorities.
“Customers don’t want to be in the business of running data centres anymore,” says Krishnan. “They want to run banks, hotels, retailers, telcos, not infrastructure.”
Cost predictability is another major driver. On-premise systems come with unpredictable capital and operational expenses, while cloud platforms allow enterprises to move to more transparent, consumption-based models. Competitive pressure also plays a role. As organisations see peers and competitors modernising, cloud migration becomes less of an IT decision and more of a strategic necessity.
But beyond cost and maintenance, AI has emerged as a decisive accelerator. Oracle Fusion’s architecture allows customers to combine clean, unified enterprise data with AI-driven processes—enabling entirely new ways of operating, not just incremental automation.
A full-stack advantage that resonates in the region
Krishnan points to Oracle’s full-stack ownership as a key differentiator in Saudi Arabia and across the GCC. Oracle Fusion Applications are built on Oracle Cloud Infrastructure (OCI), the same platform that runs large-scale workloads such as OpenAI, Zoom, and Uber.
“OCI is one of the fastest-growing hyperscalers globally,” he explains. “And we use that same infrastructure to build Fusion Applications across ERP, HCM, supply chain, and CX.”
This architectural consistency extends into AI. Oracle leverages OCI’s AI services to embed intelligence directly into business workflows, rather than bolting AI on as an afterthought. When combined with Oracle’s industry applications, spanning financial services, telecom, retail, hospitality, healthcare, utilities, and more, the result is a depth and breadth of capability that few competitors can match.
“You either see application vendors without infrastructure, or infrastructure providers without applications,” Krishnan says. “Oracle is one of the few that delivers both, deeply integrated.”
From GenAI to agentic enterprise AI
Over the past 15 months, Oracle has rapidly expanded its AI footprint within Fusion. What began with generative AI for content creation, such as job descriptions, performance reviews, and product descriptions, has evolved into a sophisticated, agent-based AI ecosystem.
Oracle initially set out to deliver 100 AI agents. Today, that number stands at more than 600.
These agents now span:
- Task-based agents for specific functions
- Workflow agents that orchestrate processes across ERP, HCM, and supply chain
- Cross-enterprise agents that ingest both Oracle and third-party data in multiple formats, including documents, images, and media
To manage this complexity, Oracle introduced an integrated AI development environment within Fusion. This includes agent libraries, lifecycle management, prompt management, traceability, performance analytics, and security controls.
“What the market needed was enterprise-grade AI hygiene,” says Krishnan. “You can’t scale AI without governance, traceability, and trust.”
The latest evolution is the AI Agent Marketplace, where Oracle partners publish certified agents directly within Fusion Applications. These agents undergo a rigorous 21-point validation process before being made available to customers as part of their existing subscriptions.
Sovereignty and trust are non-negotiable
In Saudi Arabia and the UAE, sovereignty requirements are central to cloud and AI adoption. Oracle addresses this through multiple deployment options, including public cloud, private cloud, and Dedicated Region Cloud@Customer—running the same software and hardware stack, managed by Oracle.
“For public sector and regulated industries, sovereignty is table stakes,” Krishnan notes.
Equally important are AI-specific guardrails. Oracle ensures that AI agents only access data users are authorised to see, maintaining strict role-based controls. Customer data is never used to train public models. Instead, Oracle applies retrieval-augmented generation (RAG), bringing AI intelligence to enterprise data at inference time—without exposing that data to external LLM training.
AI that delivers measurable business outcomes
Oracle’s philosophy is clear: AI must be business-led. Successful deployments begin with operational objectives, not experimentation.
Krishnan points to real-world examples where AI adoption has delivered tangible KPIs, such as significant reductions in time-to-hire and expanded talent reach in recruiting use cases.
“AI succeeds when it’s tied to a business process and a business outcome,” he says. “Not when it’s deployed just because it sounds impressive.”
The next phase: industrial-grade enterprise AI
Looking ahead, Krishnan believes the era of standalone AI pilots is coming to an end. Enterprises are moving toward secure, governed, and increasingly autonomous AI—while retaining human oversight.
“We’re moving from deterministic systems to probabilistic, agent-based models,” he explains. “But with humans in the loop at every stage, especially for mission-critical workflows.”
Adoption speed will vary by industry and geography, with digital-native organisations leading the way. What is clear, however, is the direction of travel: enterprise AI that is embedded, auditable, and scalable.
“In 2026 and beyond, AI won’t be a side project,” Krishnan concludes. “It will be industrial-grade, enterprise-grade, and deeply woven into how organisations operate.”
