PM is a good starting point for AI in a company. Cases are structured, hand-overs repeat, much of the work is documented. We work with your PM team on status, risks, stakeholder briefings and documentation.
Project teams spend a lot of time on recurring work: writing status reports, tracking risks, briefing stakeholders, maintaining documentation. This work follows fixed patterns and relies on existing documents. That makes it a good entry point for AI.
We work with PM teams on their real cases, not on textbook examples. The approach is compatible with PMI, IPMA and agile ways of working. Simon Micheler holds a teaching role at WIFI Vienna.
One to two days with your PM team. We work on cases from live operations: status, risks, stakeholder briefings, documentation. The result is three working prototypes and a plan for the next 30 days.
For teams that want to keep going after the workshop, or are looking for longer support straight away. We come in regularly, work on real cases alongside you and build independent solutions with your people, step by step.
Beforehand we agree with you which cases to work on, for example status reports, risk registers or stakeholder briefings.
The team assesses possible use cases on these real cases: where AI saves time and where human judgement is still needed.
By the end of the workshop there are three working prototypes the team can try out straight away.
The team leaves the workshop with a plan for the next 30 days, so the prototypes make it into everyday project work. Teams that want to keep going continue with the multi-week support.
Status reporting and risk tracking are core tasks in project controlling. An AI agent can bring together information from minutes, reports and emails and prepare a draft status report or an updated risk register. Whether that pays off for your team is something we assess in the workshop on your real cases.
The workshop is led by Simon Micheler. He brings over ten years of product work and team leadership and describes in his book "Digital Translator" (Linde Verlag, 2025) why AI projects mostly fail on the translation between business logic and model. If a prototype is to become a permanent solution, Nikolay Krastev takes over the technical delivery.
Above all with recurring, documented work: status reports, risks, stakeholder briefings and project documentation. Because cases are structured and hand-overs repeat, AI runs reliably here today.
Yes, for example by bringing together information from minutes and reports and preparing a draft status report or an updated risk register. Whether an agent makes sense for your cases is something we check in the workshop.
The in-house workshop takes one to two days. The follow-on support runs over 6 to 12 weeks, with a clearly defined scope and a weekly check-in with the team.
Yes. The workshop is compatible with PMI, IPMA and agile ways of working, because we work on your own cases.
A use-case assessment on its own cases, three working prototypes and a 30-day plan for the team.