In my last blog post, I explored how OCI Dedicated Region helps enterprises retrofit AI workloads into their existing data centers. We discussed how bringing Oracle’s cloud infrastructure on-premises addresses challenges such as GPU availability, latency, and data sovereignty, thereby removing many barriers to AI adoption.

Today, I want to take this further and explore the next wave of AI evolution, agentic AI, which not only responds to prompts but also takes autonomous actions. This isn’t just about having powerful models, it’s about embedding intelligence where it counts most: right next to your critical legacy systems.

The Rise of Agentic AI and Why It’s Different

Agentic AI represents a shift from passive AI tools to systems that can observe, decide, and act independently. Imagine AI agents that don’t just answer questions but manage workflows, orchestrate cloud resources, or automate incident response. This means giving AI the ability to interact with APIs, monitor real-time data streams, and adjust systems dynamically without human intervention.

The challenge? Most organizations’ critical data and applications still live in legacy platforms or tightly controlled environments. These environments were never built with autonomous AI in mind. Simply putting agentic AI in the public cloud and hoping it will integrate smoothly is not realistic. The physical and architectural distance creates latency, security risks, and compliance headaches that slow down adoption.

Legacy Systems and the Limits of Retrofitting

In my previous article, I described how OCI Dedicated Region helps organizations retrofit their existing infrastructure to support AI workloads by providing cloud-native GPU compute and AI services on-premises. While this approach is a game changer for many pilot projects and inference jobs, agentic AI demands something more foundational.

Agentic AI needs to be deeply integrated into the operational fabric of an enterprise. It requires direct, low-latency connections to databases, enterprise resource planning systems, and mission-critical applications that govern day-to-day business. Integrating AI compute into existing traditional infrastructure is a good first step, but it frequently results in complicated networks and security setups that raise operational risks.

Beyond Retrofit – OCI Dedicated Region as a Fully-Integrated AI Platform

OCI Dedicated Region is not just an add-on for AI, it’s a cloud region deployed inside your data center, delivering the same cloud services and infrastructure as Oracle’s public cloud, but physically under your control. This means you get a fully operational cloud region with high-performance computing, GPU acceleration, storage, networking, and AI services—all seamlessly integrated and ready to connect with your existing systems.

This is a fundamental shift. Instead of adapting your legacy environment to AI, you now place a full cloud region right next to your workloads. The AI agents you deploy can access real-time data, interact with legacy applications through native APIs, and operate within your strict security and compliance boundaries.

This close proximity eliminates latency and trust issues that come with remote public cloud AI deployments. It also reduces the need for complex VPNs or data synchronization layers, making agentic AI not just possible but practical.

Why Proximity Matters for Autonomous AI

Agentic AI thrives on context and immediacy. The closer it is to the systems it manages, the better decisions it can make and the faster it can act. For instance, if an AI agent detects a fault in a manufacturing control system or a spike in financial transaction anomalies, it must respond quickly to minimize disruption.

Running these AI systems in a public cloud region thousands of miles away adds delays and potential security risks, which can be unacceptable in regulated industries or mission-critical environments. OCI Dedicated Region removes those barriers by bringing the cloud to you.

By combining cloud agility with on-premises control, you get a hybrid environment where agentic AI can operate with the speed, reliability, and security enterprises demand.

The Strategic Advantage of OCI Dedicated Region

Most organizations aren’t looking for AI experiments, they want to operationalize AI at scale and embed it within their core processes. OCI Dedicated Region provides the infrastructure foundation to do just that.

It offers enterprise-ready cloud services inside your data center, enabling agentic AI to interact naturally with legacy systems without requiring costly or risky migrations. This means AI-powered automation, orchestration, and decision-making become achievable realities instead of distant goals.

If you want to move beyond retrofitting and truly modernize your AI journey, keeping the cloud close to your data, and your data close to the cloud, is essential. OCI Dedicated Region delivers exactly that.

As AI adoption becomes a strategic priority across nearly every industry, enterprises are discovering that scaling these workloads isn’t as simple as adding more GPUs to their cloud bill. Public cloud platforms like AWS and Azure offer extensive AI infrastructure, but many organizations are now facing steep costs, unpredictable pricing models, and growing concerns about data sovereignty, compliance, long-term scalability, and operational complexity. There are also physical challenges: most enterprise data centers were never designed for the high power, cooling, and interconnect demands of AI infrastructure.

A typical GPU rack can draw between 40 and 100 kW, far beyond the 5-10 kW that traditional racks can handle. Retrofitting a legacy data center to support such density requires high-density power delivery, advanced cooling, reinforced flooring, low-latency networking, and highly parallel storage systems. The investment often ranges from $4-8M per megawatt for retrofits and up to $15M for greenfield builds. Even with this capital outlay, organizations still face integration complexity, deployment delays, and fragmented operations.

This creates a challenging question: how can enterprises gain the agility, scale, and services of the public cloud for AI, without incurring its spiraling costs or rebuilding their entire infrastructure?

Oracle Cloud Infrastructure (OCI) Dedicated Region presents a compelling answer. It delivers the full OCI public cloud experience, including GPU compute, AI services, and cloud-native tooling, within your own data center. Oracle operates and manages the region, while you maintain full control. The result: public cloud performance and capabilities, delivered on-premises, without the compromises.

The Infrastructure Challenge of AI at Scale

AI workloads are no longer experimental, they are driving real business impact. Whether it’s training foundation models, deploying LLMs, or powering advanced search capabilities, these workloads require specialized infrastructure.

Unlike traditional enterprise IT, AI workloads place massive demands on power density, cooling, networking, and storage. GPU racks housing Nvidia H100 or A100 units can exceed 100 kW. Air cooling becomes ineffective, and liquid or hybrid cooling systems become essential. High-throughput, low-latency networks like 100/400 Gbps Ethernet or InfiniBand, are needed to connect compute clusters efficiently. AI workloads also rely heavily on large datasets and require high-bandwidth storage located close to compute.

In many enterprise data centers, this level of performance is simply out of reach. The facilities can’t provide the power or cooling, the racks can’t carry the weight, and the legacy networks can’t keep up.

The High Cost of Retrofitting for AI

For organizations considering bringing AI workloads back on-premises to manage costs, retrofitting is often seen as the obvious next step. But it rarely delivers the value expected.

Upgrading power infrastructure alone demands new transformers, PDUs, backup systems, and complex energy management. Cooling must shift from traditional air-based systems to liquid-based cooling loops or immersion techniques, requiring structural and spatial changes. Enterprise-grade racks are often too lightweight or densely packed for GPU servers, which can weigh over a ton each. Existing data center floors may need reinforcement.

Meanwhile, storage and networking systems must evolve to support I/O-intensive workloads. Parallel file systems, NVMe arrays, and tightly coupled fabrics are all essential, but rarely available in legacy environments. On top of that, most traditional data centers lack the cloud-native software stack needed for orchestration, security, observability, and automation.

Retrofits cost between $4-8M per megawatt. A greenfield build costs $11-15M per megawatt. These figures exclude operational overhead, integration timelines, training, and change management. For many, this is a non-starter.

OCI Dedicated Region – A True Public Cloud in Your Data Center

OCI Dedicated Region sidesteps these challenges. Oracle delivers a complete public cloud region, fully managed and operated by Oracle, inside your own facility. You get all the same infrastructure, services, and APIs as OCI’s public regions, with no loss of capability.

This includes GPU-accelerated compute (think of any Nvidia GPU), AI Services (like Data Science, Generative AI, and Vector Search), high-performance block and object storage, Oracle Autonomous Database, Exadata, analytics, low-latency networking, and full DevOps toolchains.

You also benefit from service mesh, load balancing, Kubernetes (OKE), serverless, observability, and zero-trust security services. From a developer perspective, it’s the same OCI experience – tools, SDKs, Terraform modules, and management consoles all work identically.

Importantly, data locality and sovereignty remain fully under your control. You manage access policies, audit trails, physical security, and compliance workflows.

Shifting from Capital Investment to Operational Efficiency

OCI Dedicated Region transforms infrastructure investment into an operating model. Rather than pouring capital into facilities, power systems, and integration, enterprises consume cloud resources on a predictable subscription basis. This eliminates hidden costs. No GPU spot market pricing, no surprise egress fees, no peak-hour surcharges.

Deployment is significantly faster compared to building or retrofitting infrastructure. Oracle delivers the region as a turnkey service, with pre-integrated compute, storage, AI, networking, and security. This minimizes integration complexity and accelerates time to value.

Operations are also simplified. OCI Dedicated Region maintains service parity with public OCI, which means your teams don’t need to adapt to different environments for hybrid or multi-cloud strategies. Everything runs on a consistent stack, which reduces friction and operational risk.

This model is particularly well-suited to highly regulated industries that require absolute control over data and infrastructure without losing access to modern AI tools.

Built for the Future of AI

OCI Dedicated Region supports a broad range of next-generation AI architectures and operational models. It enables federated AI, edge inference, and hybrid deployment strategies, allowing enterprises to place workloads where they make the most sense, without sacrificing consistency.

For instance, organizations can run real-time inference close to data sources at the edge (for example with Oracle Compute Cloud@Customer connected to your OCI Dedicated Region), while managing training and orchestration centrally. Workloads can burst into the public cloud when needed, leveraging OCI’s public regions without migrating entire stacks. Container-based scaling through Kubernetes ensures policy-driven elasticity and workload portability.

As power and cooling demands continue to rise, most enterprise data centers will be unable to keep the pace. OCI Dedicated Region is designed to absorb these demands, both technically and operationally.

Conclusion – Cloud Economics and Control Without Compromise

AI is quickly becoming a core part of enterprise infrastructure, and it’s exposing the limitations of both traditional data centers and conventional cloud models. Public cloud offers scale and agility, but often at unsustainable cost. On-prem retrofits are slow, expensive, and hard to manage.

OCI Dedicated Region offers a balanced alternative. It provides a complete cloud experience, GPU-ready and AI-optimized, within your own facility. You get the innovation, scale, and flexibility of public cloud, without losing control over data, compliance, or budget.

If your cloud bills are climbing and your infrastructure can’t keep up with the pace of AI innovation, OCI Dedicated Region is worth a serious look.