Identify & realize AI projects Seminar – From the idea to the successful AI use case

Because AI investments without clear use cases, data basis and structure often fail or fizzle out. Managers are under pressure to make AI usable quickly and responsibly, but often do not know how to get from the idea to realistic implementation. The seminar provides exactly this orientation – practical, methodically sound and immediately implementable.

You have a prioritized list of relevant AI use cases, a realistic feasibility assessment, a resilient target image, an initial storyboard/canvas and a clear implementation plan (roadmap, KPIs, risks). You will also know how to convince stakeholders and how to pilot and scale AI projects methodically and safely.

No. The seminar is deliberately designed so that all roles – business, IT, project management, controlling, transformation or specialist departments – can participate. Technical backgrounds are explained in an understandable way and all methods are structured in such a way that they can be used without programming knowledge.

Very different ones: Automation of back-office processes, ChatGPT-based assistance systems, intelligent analyses, predictive models, service automation, sales enablement, HR optimization or Industry 4.0 scenarios. The methods work regardless of industry, system landscape or company size.

Very. You don’t work with abstract examples, but with your own real project ideas. We guide you through analysis, problem definition, feasibility, prioritization, canvas creation and prototyping. All exercises are directly adaptable to your company situation.

The seminar will show you how to identify and evaluate use cases even if the data situation or system landscape is still unclear. You will learn how to realistically assess data requirements, which alternatives are possible (e.g. pilot data, synthetic data) and how to start projects with minimal risk despite gaps.

We use a structured evaluation model based on business value, risks, effort, data availability, regulatory requirements and complexity. This results in a comprehensible, fact-based ranking – ideal for decision-makers and budget decisions.

Through clear use case definition, clean data connection, methodical piloting, governance rules, role models, KPIs and realistic expectation management. The seminar teaches you specifically how to implement these success factors in practice and how to avoid typical mistakes.

Yes – as an in-house workshop, content, examples, frameworks and exercises can be tailored precisely to your company, your industry and your system landscape. Teams benefit from a common understanding, a common language and a common AI roadmap.

In many cases within 2-4 weeks. The seminar provides all the necessary preliminary work: prioritized use case, feasibility, canvas/storyboard, initial prototype ideas and clear next steps. This means there are no long lead times and projects can be initiated immediately.

The focus is not on technology alone, but on real projects, a clear approach, risk reduction, decision-making ability and results that are convincing internally. Instead of theory, there is methodical security, structure, examples from real AI implementations and concrete tools that can be used immediately.