This case study highlights how we at Vertex Expert Network supported a qualitative research study focused on understanding enterprise demand for GPU-as-a-Service (GPUaaS). The objective was to explore how organizations are approaching high-performance computing, AI infrastructure, and third-party GPU solutions across key European markets.
We at Vertex Expert Network supported a multi-market study across Germany, Portugal, and Ireland, targeting mid-sized to large enterprises actively involved in IT and AI infrastructure decision-making.
The research focused on organizations with:
- 500 to 5000 employees
- Active involvement in cloud, AI, and high-performance computing environments
- Ongoing or planned use of GPU-based workloads
The study aimed to understand how businesses evaluate GPU solutions, their expectations from third-party providers, and the drivers behind adoption.
Specialist-Led Recruitment:
We at Vertex recruited senior IT and AI decision-makers with direct involvement in infrastructure strategy and technology selection.
Participants included:
- Heads of IT and Infrastructure
- AI and Machine Learning Leaders
Digital Transformation and Cloud Strategy Leads
In-Depth 1:1 Interviews:
A total of 15 one-hour qualitative interviews were conducted with senior stakeholders.
Multi-Market Coverage:
We ensured geographic representation across:
- Germany
- Portugal
- Ireland
With balanced quotas across company size and industry sectors, including public sector, manufacturing, transport, energy, and healthcare.
Strict Qualification Criteria:
All participants met key requirements, including:
- Active involvement in IT and/or AI decision-making
- Significant influence or final authority on technology purchasing
- Familiarity with GPU technologies and use cases
- Current or planned usage of third-party GPU services
- Engagement in workloads requiring high-performance computing
Core Research Areas Explored:
Discussions focused on:
- Current infrastructure setup (private, public, or hybrid cloud)
- Awareness and usage of GPU technologies
- Adoption drivers for GPU-as-a-Service
- Workloads requiring GPU computing (AI/ML, simulation, rendering, analytics)
- Key considerations such as cost, scalability, energy usage, and data security
The study provided a clear view of how enterprises are approaching GPU infrastructure and third-party computing solutions.
Key insights included:
- Growing demand for scalable, on-demand GPU capacity driven by AI and data-intensive workloads
- Strong preference for flexible, hybrid infrastructure models
- Cost optimization and burst capacity identified as major adoption drivers
- Increasing importance of data security, compliance, and energy efficiency in decision-making
These insights enabled the client to better understand enterprise expectations, refine its GPUaaS value proposition, and align its offering with real-world business needs across different markets and sectors.
- Senior IT leaders including Heads of IT, Infrastructure, and Cloud Strategy
- AI and machine learning leaders responsible for AI adoption and governance
Digital transformation and technology decision-makers with direct influence on infrastructure investments
Seeking answers to similar business questions? Vertex combines human expertise with AI-enabled research to deliver actionable intelligence.
