Agentic AI has the potential to fundamentally transform how organizations operate, creating groundbreaking opportunities and complex challenges. We invite you to join our exclusive roundtable on integrating Agentic AI within your business. Together with thought leaders and industry peers, we will explore the practical steps and strategic decisions that will define the AI-ready tech team for 2027.

The 2027 tech team

Defining the ai-ready tech team for 2027

Statement: your best software architect will soon be less valuable than your best 'ai psychologist'.

• Does your team have the right ai skills for 2027?
• What new roles do you see emerging, and which existing roles will need to fundamentally change?
• How do we up skill our current workforce in the Netherlands to fill these roles?
• Does the leadership structure (of technology departments) need to change to manage these new hybrid teams?

Build vs. Buy

The platform dilemma: cloud convenience vs. independent control.

Statement: for any serious european enterprise, relying on us cloud platforms for core ai is an unacceptable long-term risk.

• Cloud AI or your own models: what’s the right bet?
• What is your current strategy regarding the large cloud providers for AI?
• What are the specific triggers (e.g., cost, privacy, control) that would make you choose self-hosting?
• What frameworks and tools are you experimenting with, and are they mature enough for enterprise maintenance?

The ‘Red Button’ and runaway costs

Taming the agent: governing risk, cost, and the 'red button'.

Statement: a manual 'red button' is a comforting illusion; by the time you press it, an autonomous agent has already done the damage.

• How do you currently model and control the costs of your AI experiments?
• Who pushes the red button on a rogue AI agent?
• Who in the organization should have the authority to approve, deploy, and terminate agents?

Architecture: designing the central context platform

Architecting context: building your company's AI brain.

Statement: everyone is focused on the LLM, but the model is a commodity. your only real competitive advantage is a superior data and context platform.

• How do you build your company's AI 'brain'?
• Do you need to embed all of your unstructured data?
• Large context windows vs. retrieval optimization
• Who defines the business rules? Do we let the stakeholders create the agents?
• When to implement MCP?

From pilot to production

From hype to high-value: deploying your first production agent.

Statement: the smartest first move isn't a flashy, customer-facing agent. it's automating a 'boring' internal process where it can fail safely.

• Beyond the chatbot: what will your first real agent do?
• Share one high-potential use case from your company.
• Measuring ROI.
• What is the most immediate, practical step your organization could take to start building this?