Making AI Projects a Success
Launching and Managing AI Projects and Effectively Integrating Them into Day-to-Day Business Operations
Fundamentals and Framework Conditions for Sustainable AI Projects
- A Refresher on the Basics of AI: Potential, Limitations, and Typical Applications.
- Understand the unique characteristics of AI projects compared to traditional IT projects.
- Assessing AI Readiness: Culture, Process Maturity, System Landscape, Data Management.
- Process and system inventory, capability map, identifying media breaks.
- Identify scope creep early and take action to prevent it.
Project Launch and AI Project Architecture
- Building an AI Project Team: Roles, Responsibilities, Change Agents.
- The 4-Phase Model in Practice: Discover, Design, Develop, Deploy.
- Record requirements, prioritize them, and continuously refine the scope.
- Define two success metrics: engagement and quality.
- Business Case and Budget: Realistically Calculate License and Token Costs and TCO.
AI Project Management and Stakeholder Management
- Identify typical pitfalls in AI projects early on.
- Analyze stakeholders and engage them in a targeted manner.
- Systematically identify and assess risks.
- Measure progress, identify deviations, and take effective corrective action.
Rollout, Adoption, and Sustainable Implementation
- From a pilot project to a productive system using the traffic-light system as a rollout canvas.
- Testing and Hypercare: Ensuring quality, security, and reliable results in production.
- Optimize change management and actively foster acceptance.
- Establish feedback loops and improvement cycles.
- Building data network effects: Every interaction makes the system better.
Your Digital Add-On: To complement the training, you’ll receive free access to additional digital learning resources afterward. These include an e-learning course on initial applications of AI in project management, as well as a guide on how to use AI as your personal learning companion or coach to help you apply what you’ve learned in your day-to-day work.
In your online learning environment, you will find useful information, downloads and extra services for this training course once you have registered.
- You build on your project management knowledge and specialize in a targeted manner.
- You understand the unique aspects of AI projects and know what matters most when it comes to planning, management, and adoption.
- You assess the current state of your organization in a structured manner as the basis for every AI decision.
- You set up AI pilot projects using the 4-phase model and know when to scale up and when to make adjustments.
- You actively manage stakeholders, change, and risks, and ensure that your project doesn't fizzle out after the pilot phase.
- You'll walk away with methods, checklists, and templates that you can put to use right away in your next AI project.
- You will establish the use of AI systems within the company on a long-term basis and continuously improve them.
Technical insights with case studies from real AI projects. Hands-on individual and group exercises based on participants’ own projects. Proven methods and templates to take home: Capability Map, 4-Phase Model, Traffic Light System as a Rollout Canvas, Business Case Calculator, Adoption Dashboard, Risk Matrix. Group discussion and sharing of experiences. The workshop actively incorporates participants’ real-world examples and projects.
Please bring your own laptop (including the charging cable, etc.) to training.
Technical insights with case studies from real AI projects. Hands-on individual and group exercises based on participants’ own projects. Proven methods and templates to take home: Capability Map, 4-Phase Model, Traffic Light System as a Rollout Canvas, Business Case Calculator, Adoption Dashboard, Risk Matrix. Group discussion and sharing of experiences. The workshop actively incorporates participants’ real-world examples and projects.
project managers, project managers owners process managers owners are responsible for the day-to-day management and implementation of AI projects within their companies. This course is particularly well-suited when the strategic direction of the AI initiative has already been established and implementation is now set to get underway in a structured manner.
Eligibility requirements:
Operational experience and basic knowledge of project management (comparable to the content of the “Project Management Basics” seminar), as well as a basic understanding of how to work with AI and the relevant terminology.
42812
- Customized training courses
- Direct application in practice
- Efficient use of time and resources
Start dates and details
Monday, 14.12.2026
09:00 am - 5:00 pm
Tuesday, 15.12.2026
09:00 am - 5:00 pm
Thursday, 14.01.2027
09:00 am - 5:00 pm
Friday, 15.01.2027
09:00 am - 5:00 pm
Monday, 01.02.2027
09:00 am - 5:00 pm
Tuesday, 02.02.2027
09:00 am - 5:00 pm
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
Thursday, 22.04.2027
09:00 am - 5:00 pm
Friday, 23.04.2027
09:00 am - 5:00 pm
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
Thursday, June 17, 2027
09:00 am - 5:00 pm
Friday, June 18, 2027
09:00 am - 5:00 pm
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
Monday, August 16, 2027
09:00 am - 5:00 pm
Tuesday, August 17, 2027
09:00 am - 5:00 pm
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
Thursday, September 9, 2027
09:00 am - 5:00 pm
Friday, September 10, 2027
09:00 am - 5:00 pm
Training is guaranteed to take place- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
FAQ
Successful AI project management requires clear goals, appropriate responsibilities, and a structured process. At the same time, requirements must be prioritized, the project scope continuously refined, and potential pitfalls identified early on. In the “ training ,” you’ll learn how to systematically set up and manage AI projects. This will enable you to turn a strategic AI initiative into a concrete and viable project.
AI readiness describes how well a company is prepared—in terms of organization, technology, and processes—for the implementation of AI. This includes, among other things, process maturity, data management, the system landscape, and corporate culture. In the “ training ,” you’ll learn how to analyze these prerequisites in a structured way and identify potential gaps early on. This will help you better assess which foundations need to be laid for the successful implementation of an AI project.
AI projects often involve collaboration between business units, IT, and other stakeholders. Differing requirements and responsibilities can complicate implementation if they are not clearly coordinated. In the “ training ,” you’ll learn how to analyze relevant stakeholders, engage them in a targeted manner, and clarify roles within the project team. You’ll also learn how change management and actively building acceptance help to sustainably embed AI solutions within the company.
A successful AI pilot is an important step, but the solution must then be reliably transitioned into production. In the " training ," you’ll learn how to prepare for the rollout in a structured way and ensure quality and security through testing and hypercare. Feedback loops and continuous improvement cycles will help you permanently embed the AI solution into your company’s day-to-day operations.
The success of an AI project does not depend solely on its technical implementation. Usage, quality, costs, and economic benefits also play an important role. In the " training ," you’ll learn how to define appropriate success metrics, realistically assess the business case and budget, and systematically evaluate risks. This will enable you to measure progress, identify deviations, and steer your AI project in the right direction.
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