Power Platform en AI: wat vibe-coding wel en niet voor je oplost

Where individual AI automation hits a wall

A colleague builds a flow that saves their team three hours a week. Besides that, an analyst sets up a Copilot agent for recurring product questions. It works, nobody hears about it, fine. However, the moment that solution gets picked up by other teams, or business data starts flowing through it that turns out to be more sensitive than anyone realized, things change.

Then the questions stack up: who maintains it, who is allowed to change it, what happens when the builder moves to a different department, and how do you know the output is reliable enough for decisions that matter.

Not every step needs AI

AI makes things possible that were previously out of reach. At the same time, it brings cost and uncertainty. First, every call to a large language model costs tokens, and that bill rises surprisingly fast once an automation is widely used. In addition, every LLM response carries inherent unpredictability, which sits poorly with steps where you expect the same result for the same input.

Therefore, builders of mature automations make conscious choices. Some steps stay deterministic, others benefit from AI, for example when interpretation or classification is needed. Vibe-coding mostly belongs in the prototype phase, where putting an idea on the table fast matters more than durability.

Power Platform and AI as the foundation under your automation

This is where Microsoft Power Platform comes in. After all, Power Platform and AI complement each other: AI accelerates the build, while the platform makes sure what gets built fits within your organization’s boundaries. In practice, that means version control, monitoring, separate environments, data loss prevention, role-based access, and visibility into which connectors are used where.

Furthermore, we look at two angles for the build itself. First, Claude with the Power Platform MCP server lets you adapt existing solutions and stand up new canvas or code apps through a prompt. In addition, Copilot Studio works as a central intelligence layer for automations that need interpretation, with the option to pick OpenAI or Anthropic models under the governance of your own tenant. As a result, Power Platform and AI stay workable together as the number of automations grows.

What you take away

• When an automation is ready to be used across the organization.
• Where AI does or does not add value inside an automation, and what that means for cost and reliability.
• How Copilot Studio works as a central intelligence layer under governance.
• Examples of Power Platform and AI in combination, including Claude through the Power Platform MCP server.

Who this is for

Managers, data leads, IT decision-makers and analysts actively working with AI and automation. Especially relevant if you are responsible for the scalability or governance of automations, or if you build them yourself and want to know how your work can be handed over later, once it starts to matter.

Practical info

• • Date: May 28, 2026
  • Time: 10:00 (CEST)
  • Duration: 30 minutes
  • Location: Online
  • Language: English