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Your AI, Your Way
In this podcast, we examine AI infrastructure from an enterprise perspective. Guests with backgrounds in enterprise IT, cloud architecture, security, finance, and education join MDCS.ai in the Cisco podcast studio to share practical experience and informed viewpoints.
Each episode addresses the questions that arise once AI initiatives move beyond experimentation and into production.
How do you design infrastructure that truly scales?
What happens to cost, performance, and control as AI workloads grow?
How do organizations balance speed, security, data sovereignty, and long-term ownership?
Rather than focusing on trends or product promotion, the discussions are grounded in real-world challenges—covering architectural choices, operating models, governance, accountability, and the trade-offs organizations must navigate when building or scaling AI environments.
Your AI, Your Way is intended for AI leaders and practitioners responsible for delivering AI in practice, not just in theory.
Your AI, Your Way
AI Center of Excellence
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
Giving people AI tools is not the same as AI adoption.
Most employees are driven by their inbox. Add a strategic AI project on top, and enthusiasm alone will not create capacity. Without structure, AI becomes a side project for one eager person while leadership has no visibility into the risks underneath.
At TU Eindhoven, the Supercomputing Center grew its AI team from one engineer to five in eighteen months. Demand keeps rising. Researchers, educators, and now industry partners all want access to compute, but raw compute power is only half the story.
Every platform is a race track. You need the right car for it. And someone who knows how to drive. When specialists work alongside researchers, efficiency gains of six times are common. Without that support, teams burn time learning what others already know.
The question for any organization is not whether to build AI capability, but how. Centralized through a Center of Excellence? Distributed through a hub and spoke model? The answer depends on risk appetite, maturity, and speed.
In this 39-minute discussion recorded at the Cisco Studio in Amsterdam, Nick Brummans (TU Eindhoven) and Vera Schut (NXT Minds) share what they have learned about building AI competencies that actually stick.
Key topics include:
- Why giving employees AI tools without structure leads to invisible risk and wasted effort.
- The difference between a Center of Excellence, a hub and spoke model, and letting the business figure it out.
- How TU Eindhoven onboards researchers onto advanced AI platforms, and what trips them up.
- Why knowledge is a muscle that requires consistent training, not a one-time workshop.
- What smaller companies can do faster than enterprises stuck on legacy systems.
