The Copilot rollout with PromptingBirds
What we’ve learned from more than 100 projects – and why the rollouts that do everything right on paper still fail.
Most companies fail at AI adoption because they try to bring 100% of their employees along.
A fixed team, clear roles. Why for you this is the difference between a “project that works” and a “project that fizzles out.”
Real numbers from ongoing client projects. Which KPIs we use, which ones we deliberately don’t, and why “adoption rate” alone tells you nothing.
What you’ll learn in this video
- Why the freelancer model creates structural quality problems in AI consulting
- Which concrete roles exist within the PromptingBirds team — from strategy and product development to AI development
- How a fixed team ensures that methodology and quality stay consistent across all client projects
- What happens when the primary point of contact is suddenly unavailable
- Why scaling on large rollouts works through train-the-trainer concepts rather than armies of external trainers
- Which commitment to projects applies beyond the signing of the contract
Who is this relevant for?
This page is for everyone currently in the process of evaluating an AI consulting partner — in particular decision-makers at mid-sized companies who have already had bad experiences with a rotating cast of external consultants, or who, during a longer-term AI rollout, depend on stable points of contact and a consistently applied methodology.
The next step
Anyone who wants to see what a concrete project with this team looks like — with real numbers from real projects — will find it in the final part of this video series. Or directly: get in touch and clarify which setup fits your own company size.