Putting AI Roadmaps into Action – A Data Leader’s Guide to Successful AI Implementation

Course details

Suddenly in charge of “doing something with AI”? In this course, AI expert Tobias Zwingmann helps data leaders move from uncertainty to execution by translating AI roadmaps into scalable, business-aligned action. Learn to focus on high-value use cases, prototype effectively without overbuilding, and scale solutions without derailing your data strategy. Explore systematic ways to identify business pain points, evaluate potential AI use cases, and differentiate between viable AI opportunities and common implementation traps. Find out how to produce professional-grade documentation packages for organizational review. Complete a decision matrix comparing potential solutions. Develop a scaling plan for one AI pilot that includes performance monitoring metrics. Plus, learn how to position yourself as a credible AI leader. Packed with practical frameworks, tool walkthroughs, and real-world scenarios, this course shows you how to lead AI like a pro (even when you didn’t ask for the job).

Learning objectives
Analyze business pain points to identify high-impact AI opportunities.
Create comprehensive use case documentation and prototype charters.
Evaluate build vs. buy decisions and select appropriate AI tooling layers.
Apply the five enablers framework to design scalable AI systems.
Synthesize an AI leadership strategy and organizational narrative.

Concepts

Introduction

AI roadmaps - the solution to humankind's problems

Wait I m in Charge of AI Now

The hand-off - Why this happened to you
From dashboards to AI - The expanded role
Which AI game are you playing
Roadmap for action
Repositioning yourself as an AI enabler

Building Use Cases That Actually Matter

Why you should stop looking for AI use cases
How to spot real business problems AI can solve
Remove bad ideas early with an impact filter
Understanding the (misunderstood) role of data in AI
Document and communicate an AI opportunity effectively
Use cases - Good, bad, and unclear

Effective Prototyping without Wasting Time or Budget

From idea to prototype without overdoing it
The 20 20 rule for AI prototypes
Build, buy, or both
Pick the right solution type
Write a prototype brief
Your starter AI tool stack - Prototyping tools that actually work
Demo - Building a pilot with n8n + Azure

Scaling AI without Losing Your Mind

What scaling AI really means
The five enablers of scalable AI
Monitoring beyond accuracy
Scaling profitable AI systems
Evaluating your AI scaling maturity
Your AI ops stack and how to choose it
AI strategy vs. data strategy - How to keep both aligned

Becoming the AI Anchor in Your Organization

The job no one defined but you re doing it
How to talk about AI without talking about AI
Creating your AI narrative
The AI center of enablement (lite)
Your next move as an AI leader

Continuing Your AI Roadmaps Planning Learning Journey

Next steps and additional resources