AI is Here. But Your Infrastructure Might Not Be.
Leveraging IT Asset Management (ITAM)
AI is no longer a side project. It’s in production—helping businesses detect fraud, streamline design, simulate outcomes, personalize experiences, and uncover insights at scale. The challenge now isn’t whether to use AI. It’s how to support it.
That’s the problem many IT teams are running into: AI is pushing their infrastructure in ways they didn’t expect. And while cloud platforms are still part of the answer, they’re no longer the whole story.
High-performance HP AI workstations, powered by NVIDIA RTX™, are giving organizations a new path forward—one that’s faster, more flexible, and more cost-effective for a growing number of real-world AI workloads.
MCPC partners with organizations to make this path actionable. We help design and deploy AI-ready infrastructures that incorporate HP workstations for edge and local compute while supporting hybrid models that balance performance, security, and scalability.
What’s Changed?
AI adoption has exploded. But most organizations have found that scaling AI requires more than just spinning up another cloud instance. Here’s what they’re up against:
- Long cloud provisioning times for GPU resources
- Data privacy and regulatory barriers
- Soaring cloud costs for compute-heavy workloads
- Delays caused by network latency or bandwidth limits
- A growing need for control, security, and speed—especially at the edge
That’s why more IT leaders are adding AI workstations to their infrastructure mix.
At MCPC, we understand these pressures firsthand. Our Lifecycle Management, IT Asset Management (ITAM), and Infrastructure Consulting teams ensure you’re not only adopting the right hardware—but doing so strategically. We help you deploy and scale workstations efficiently, reduce operational risk, and stay compliant with evolving regulations.
Why Workstations Are Back in Focus
Modern AI workstations have little in common with the desktops of years past. Today’s systems deliver the kind of performance once limited to data centers—right at the desktop.
Take HP’s Z8 Fury and Z8 G5 workstations. These machines can be configured with:
- Up to four NVIDIA RTX 6000 Ada Generation GPUs
- 192GB of GPU memory
- Up to 5.8 petaflops of AI compute performance
They’re built to:
- Train, test, and iterate on complex models
- Run GPU-heavy applications in parallel
- Perform real-time analytics at the edge
- Accelerate deep learning, computer vision, and data science workflows
- Support local development before scaling to the cloud
And with built-in support for the Z by HP Data Science Stack Manager, they’re ready to go—no complex setup required.
MCPC helps operationalize that power. From procurement to configuration to deployment, our team ensures your AI workstation investment delivers results quickly. We also support remote access, security hardening, and integration into broader hybrid or cloud infrastructure.
When Local Compute Makes the Most Sense
Workstations make sense for more than just performance. They’re often the better choice for workflows that require speed, privacy, or precision. Consider:
Manufacturing teams running simulations to optimize factory layout in real time
Architects and engineers generating AI-assisted designs and running performance modeling onsite
Creative professionals rendering high-res 3D content while using generative tools for effects and motion
Data scientists building and fine-tuning models on proprietary datasets that can’t leave the firewall
In these cases, local performance isn’t just a nice-to-have. It’s the difference between real-time iteration and waiting for the cloud to catch up.
MCPC specializes in deploying AI workstations for exactly these scenarios. Our professional services ensure secure local environments, whether for manufacturing, healthcare, creative, or research-intensive applications—without compromising on compliance or performance.
More Control. Lower Cost. Faster Time to Value.
Cloud platforms are essential—but they come with trade-offs. High demand for GPU resources means longer wait times and unpredictable pricing. Sending sensitive data offsite raises compliance concerns. And for edge workflows, network latency is an ongoing constraint.
Workstations offer an alternative:
- Predictable cost and local control
- Instant access to performance—no provisioning delays
- Better security posture for sensitive workloads
- Reduced data movement and associated risk
- Seamless remote access via HP Anyware for distributed teams
And when the time comes to scale up or share results across the organization, workstations integrate easily with cloud platforms—making them a perfect fit for hybrid environments.
That’s where MCPC adds long-term value. We not only help you implement high-performance workstations—we manage them across their lifecycle. From imaging and deployment to device security, user support, and eventual ITAD (IT Asset Disposition), we provide complete support for your hybrid AI environment.
The Bottom Line for IT Leaders
Your teams are using AI now—or they will be soon. But infrastructure built for yesterday’s applications isn’t optimized for today’s AI-driven workflows.
Z by HP AI workstations, powered by NVIDIA RTX, give your teams the power they need—at the speed and scale that makes sense. They don’t replace the cloud, but they reduce your reliance on it. And they give you the control, performance, and flexibility to move faster without compromising your security or budget.
AI is moving fast. Your infrastructure should be able to keep up.
Explore how AI workstations can help you support real-world workloads—without waiting on the cloud. Get in touch with us. We can help.
MCPC brings it all together. We align your infrastructure strategy with your AI roadmap, deploying the right tools—workstations, cloud, or edge—while providing the services and security needed to succeed.
AI is moving fast. Your infrastructure should be able to keep up.
Explore how AI workstations can help you support real-world workloads—without waiting on the cloud.
Get in touch with MCPC. We can help.