Modern project management for AI projects – methods, tools & practical knowledge

Rethinking project management – for data-driven, experimental AI initiatives

Artificial intelligence is changing not only products and processes – it also poses new challenges for classic project management. AI projects rarely run linearly, are often highly data-dependent, and their results can hardly be predicted exactly at the beginning. What does this mean for the planning, control and leadership of such initiatives?

This training gives project managers, product owners and team leaders the tools they need to manage AI projects realistically, purposefully and successfully – with a clear view of practice, pitfalls and the necessary adaptations of classic methods.

What we offer:

In this one-day seminar you learn which special features AI projects have compared with classic IT or digital projects – and which methodological consequences result from them. You get a sound overview of agile and classic project approaches, of roles and tools that are especially relevant in the AI context, and of proven methods for steering data-driven developments.

The content is based on real project experience from industry, public administration and services – honest, nuanced and with many concrete examples.

What to expect:

• You learn the basics of agile methods such as Scrum and Kanban compared with the waterfall model – specifically with regard to AI projects
• You understand why AI projects are often iterative, experimental and data-driven – and how to reflect this organizationally
• You find out which project management approaches suit which situation: agile, hybrid or classic – depending on maturity, objectives and team structure
• You gain insights into roles that are becoming increasingly important in the AI environment: e.g. product owner for AI, data science leads, MLOps managers
• You analyze real experience reports: What worked in AI projects – and what did not?
• You get tips for developing a viable project culture for dealing with uncertainty, learning loops and changing requirements

Plus:

• Practical checklists for project kick-off
• Methods for realistic progress assessment in exploratory processes
• Discussion: How can responsibility be sensibly distributed in data-driven teams?

Why take part?

This training is aimed at everyone who structures, supports or is responsible for AI projects – and needs more than standard methods. You gain clarity about which approaches and tools work when it comes to successfully leading projects with high uncertainty, a strong data focus and interdisciplinary teams.

👉 One-day AI training that makes your project management fit for the particularities of AI – with practical knowledge, methodological confidence and realistic tools.

Register now – and prepare your project management for the future of artificial intelligence in companies.