AI for Decision Makers.
Cut through the noise: make AI decisions with clarity and confidence — based on evidence, not buzzwords. For leadership teams deciding on AI budgets.
Build, buy or wait — with criteria instead of gut feel
Every AI investment comes down to one of three decisions. The workshop gives you the frame for each — with the signals that point to it.
Build your own AI capabilities — where your codebase and your data are the difference.
- Your software is core to your differentiation
- Data ownership and data residency are business-critical
- You have engineering capacity that can carry it
Buy tools that know your context — instead of building something generic yourself.
- The process is standard, the problem isn't unique
- Time-to-value matters more than building in-house
- Jira, Confluence and GitHub are already your backbone
Waiting deliberately is a decision — with criteria and a review date, not procrastination.
- The data situation is unclear or scattered
- Regulatory questions are open
- No lever that pays for itself within 12 months
Questions you'll answer yourself afterwards
Where does our organisation stand on AI readiness — and how do we measure it?
Which AI investment pays for itself within 12 months?
Build, buy or wait — and with what reasoning?
Which risks do we accept deliberately: data residency, vendor lock-in, shadow AI?
What do we measure after 90 days — and who owns it?
Anchored in research and product
The workshop builds on the AI Monitor — the research project Teklens publishes with ETH Zurich and the University of St.Gallen. You decide based on six validated readiness dimensions, not slides. And where a tool is the right answer, we show honestly what Teklens can do — and what it can't.
Frequently asked questions
Not sure which package fits?
30 minutes with the founder team. We'll tell you if none of them fits, too. No sales.