What GDCC 2026 Taught Us About AI Infrastructure

Our First Conversation Challenged the Case for Buying More Hardware

Interestingly, one of the first presentations we encountered questioned why organizations should continue purchasing additional infrastructure when existing data centre resources aren't always being used to their full potential. It was an interesting perspective to walk into... 

Much of the AI infrastructure conversation focuses on expanding capacity. Things like more GPUs, larger facilities, greater power requirements, and new data centres. But there's another equally important question.

Of course, unused storage capacity doesn't necessarily mean an organization has enough available GPU compute. Different workloads place very different demands on processors, memory, storage, networking, and facilities.

Still, the broader point was worth considering. Before purchasing more hardware, organizations should understand what they already operate, where the bottlenecks exist, and whether additional capacity will solve the actual problem.

That principle applies whether a business is planning one AI workstation or an entire GPU server deployment. And it connected to a familiar conversation we had encountered at Elevate Festival 2026.

Cloud vs. Dedicated AI Hardware: The Right Answer Depends on the Workload

At Elevate, many of our conversations with startup founders involved businesses using AWS or other cloud platforms.

At GDCC, the conversations felt noticeably different. Most of the companies we spoke with worked directly with physical infrastructure or specialized hardware. That difference wasn't necessarily evidence of a wider market shift; the two events simply attracted different types of professionals.

But it reinforced how differently businesses approach AI infrastructure depending on their stage of development and technical requirements. One particularly interesting conversation involved a team developing an AI software platform. They were using cloud infrastructure but were also interested in exploring dedicated local hardware.

We discussed a previous Alpha PC project involving Castle Ridge Asset Management's WALLACE AI supercomputer. The company had previously operated its proprietary AI workload using cloud infrastructure. As its computing requirements grew, continuing to rent capacity became increasingly expensive.

But it does illustrate a practical question for CTOs, AI founders, and infrastructure teams:

The answer depends on utilization, hardware cost, power, maintenance, software, performance requirements, data handling, and expected growth.

The important part is making that decision based on real operating requirements rather than assuming one model is always better.

What Actually Goes Into a Data Centre Project?

One of our biggest realizations came from spending time on the exhibition floor.

We spoke with companies specializing in electrical infrastructure, networking, cabling, cooling, engineering, hardware, and data centre operations. Each company approached infrastructure from a different direction.

At first, it was sometimes difficult to understand how Alpha PC's capabilities connected with a particular exhibitor's services. A company specializing in fibre connectivity, for example, isn't necessarily interested in purchasing a custom AI workstation. But the more conversations we had, the more clearly we understood how these specialties fit together.

A Data Centre Is More Than a Room Full of Servers

A computing deployment doesn't exist independently of its operating environment.

Depending on the project, delivering a data centre can involve:

And while our experience already includes custom liquid-cooled computing systems, seeing cooling discussed at the scale of entire facilities introduced another level of complexity. The underlying principle was familiar: demanding hardware requires an appropriate thermal environment. The scale of the engineering was very different.

Large Infrastructure Projects Often Depend on Multiple Specialist Companies

Across our conversations, we noticed how frequently companies worked with other suppliers, contractors, or technology providers to deliver a larger solution. Not every company operated this way. Some maintained a very narrow specialization, while others coordinated broader projects through established partner networks. But the collaborative nature of the industry was difficult to miss.

A data centre operator may work with engineering consultants, electrical contractors, cooling specialists, networking integrators, and computing hardware suppliers. Each is responsible for a defined portion of the outcome. For a business preparing a large infrastructure RFQ, this matters.

Successful procurement depends on identifying those responsibilities early, confirming technical compatibility, and ensuring the overall project has accountable delivery ownership. It was a reassuring realization for us, as our expertise is in the computing hardware. The opportunity is to understand how that hardware fits into the broader project and collaborate with qualified specialists when the requirement extends beyond our scope.

A Conversation That Stayed With Us

Some of the most valuable moments at GDCC had little to do with formal presentations.

At a particular booth, we initially spoke with a representative about data centre equipment and hardware lifecycle services. As the conversation became more technical, we were introduced to the company's Director of Managed Services, Stephan Hales. What followed was one of our favourite interactions of the day.

Stephen and Dillon, Alpha PC's founder and system builder, discovered they had a shared background in building and tuning computers. They exchanged stories about gaming PCs, overclocking, and the technical curiosity that comes from spending years learning how hardware behaves beyond the specifications on a product page.

Outside of the average business talk, it was refreshing to meet someone with extensive industry experience who remained so enthusiastic about the fundamentals. For us, the conversation reinforced the value of remaining adaptable.

Technology changes quickly, but curiosity, practical problem-solving, and a willingness to keep learning remain useful regardless of what the next hardware generation brings. We left that conversation with both technical ideas and a genuine appreciation for how willing experienced professionals can be to share their knowledge.

Where Custom Workstations and GPU Servers Fit Into Larger Projects

Not every organization attending GDCC needs the same kind of computing system.

An AI startup developing a proprietary model has different priorities from a research laboratory running scientific simulations.

A systems integrator delivering twelve workstations to a customer has different procurement responsibilities from a CTO evaluating a shared GPU server for an internal team.

And a data centre deployment introduces additional facility, networking, serviceability, and operational requirements.

The right computing architecture depends on what the hardware is expected to accomplish.

Common Enterprise Compute Requirements

Scroll horizontally to compare all three columns on smaller screens.

These are common planning considerations, not fixed configurations. The actual design should follow the workload and site requirements.

Workstation, GPU Server, or Multi-System Deployment?

For larger projects, one incorrect component choice or an unexpected supply delay can affect far more than a single computer.

That's why we believe the hardware supplier should be involved early enough to understand the full requirements rather than simply receive a list of parts at the end.

What Alpha PC Has Already Delivered

The discussions at GDCC also gave us an opportunity to reflect on the kinds of projects Alpha PC has already supported.

One example was a 12-workstation deployment for an international communications systems integrator.

The project required twelve custom enterprise workstations, each configured with professional graphics hardware and 1 TB of ECC memory. The challenge wasn't just assembling powerful systems; it was coordinating sourcing, configuration, testing, and delivery against one project specification. That kind of work is especially relevant to technology integrators delivering solutions for their own customers.

Other Alpha PC projects include a scientific computing workstation for Rutgers University and the purpose-built WALLACE system for Castle Ridge Asset Management.

Each project had different technical requirements. But the underlying approach was consistent: understand the workload, identify the appropriate architecture, and build around the client's actual operating needs.

These experiences don't automatically qualify Alpha PC to undertake every large infrastructure contract. However, they do demonstrate the specialized computing expertise we can bring to projects where hardware is one important part of a larger solution.

What GDCC Changed About Our Perspective

Before attending GDCC, much of our exploration of the data centre industry involved online research: understanding suppliers, identifying prospective partners, and learning how larger infrastructure projects are structured. Those resources were useful, but there's a limit to what you can learn from a company's website.

Speaking directly with people who work on these projects gave us a clearer understanding of how opportunities actually move forward. We learned more about supplier relationships, specialist contractors, procurement processes, and the practical responsibilities involved in larger deployments.

We also discovered that established companies were often open to speaking with a smaller specialized builder when there was a relevant capability to discuss. After eleven meaningful conversations on our first day, the industry felt considerably more accessible than it had before we arrived.

That doesn't mean the path to becoming an approved supplier is automatic. Technical qualifications, pricing, references, financing, support arrangements, and contractual responsibilities still matter. But it reinforced that:

It needs to be exceptionally clear about the problems it solves and reliable in delivering its part. For Alpha PC, that means continuing to strengthen the relationships and processes surrounding the hardware we already know how to build.

Have an RFQ That Goes Beyond a Standard Workstation Build?

One thing we want potential customers to understand is that you don't need to determine whether your project fits neatly into Alpha PC's catalogue before contacting us.

Some requirements involve a single high-performance AI workstation. Others require custom GPU servers, multi-unit deployments, specialized engineering configurations, or computing hardware within a much larger infrastructure project.

Alpha PC works with businesses, startups, universities, research teams, professional firms, enterprise IT departments, and systems integrators that need custom computing solutions.

When a requirement extends beyond our own technical scope, we can review the wider project and determine whether collaboration with qualified infrastructure specialists would be appropriate. We won't assume every requirement is feasible. But we are open to evaluating the opportunity.

What to Include in Your Compute or Infrastructure RFQ

To help us understand your project, share whatever information is currently available:

1. Workload or intended applicationWhat the hardware needs to run.
2. Technical requirementsExisting specifications, preferred platforms, or a bill of materials.
3. Quantity and scaleNumber of workstations, servers, or anticipated phases.
4. Deployment environmentOffice, research laboratory, customer facility, or data centre.
5. Timeline and procurement requirementsTarget delivery date, purchasing process, and any mandatory support conditions.

Our first step is to understand the requirement, establish what Alpha PC can support, and identify any dependencies that need further review.

Frequently Asked Questions

The Bigger Picture

Our biggest takeaway from GDCC 2026 wasn't that every business needs more computing hardware. It was how much expertise, collaboration, and planning sit behind the infrastructure that makes modern computing possible.

For us, the most valuable part of the event was meeting the people doing that work and seeing where our own capabilities could contribute.

We're still learning. We're still building relationships. And we're continuing to understand how Alpha PC can support increasingly complex projects without losing the specialized, hands-on approach that got us here.

Because whether a project requires one workstation, twelve coordinated systems, or compute hardware within a larger data centre deployment, the most important question remains the same: