From projects to practices:make AI normal
A breakfast seminar for people shifting AI projects into practices
AI-enabling one workflow is improvement. Learning to AI-enable at scale is capability. AIs aren’t miracle-workers. Design them to enable, so teams can employ them to get jobs done.
+ Q&A and networking session
Location in Stockholm:
Sturegatan 15 Möten och Event by Hantverket
2026-03-30:
08:00-10:00 + Q&A, sharing and networking
From projects to practices: make AI normal
A breakfast seminar for people shifting AI projects into practices
AI-enabling one workflow is improvement. Learning to AI-enable at scale is capability. AIs aren’t miracle-workers. Design them to enable, so teams can employ them to get jobs done.
+ Q&A and networking session
Location in Stockholm:
Sturegatan 15 Möten och Event by Hantverket
2026-03-30:
08:00-10:00 + Q&A, sharing and networking
Making your Data×AI initiatives stick
AIs become the new normal by offering people a smoother Workflow Experience (WFX). Your WFX Engineering, then, must navigate common AI initiative failure modes.
Projects withoutpractices
People don’t adopt new tech. They adopt new practices. But only if the practice reduces everyday work friction.
Practices without product ownership
People employ products in their practices. But only if the product offers smoother WFX (job-doing). WFX Engineering requires effective product ownership and governance.
Point-solution spaghetti that blocks scaling
When more people adopt a practice, products must scale with demand. This requires investment in refactoring products into reusable and composable components.
Practices that don't spread beyond pockets of pioneers
Pioneer enthusiasm is critical. However, the majority can only adopt practices that are supported by policies, processes, and platforms.
What we will cover
The Seminar topics are a response to better understand the failure modes and how to adress them.
The path from new to normal
Why this transition is where Data & AI initiatives most often stall — and what has to change for adoption to move beyond pilots.
Where AI adoption breaks: common failure modes
How invention, early adoption, and scaling pull in different directions, creating blind spots that are easy to miss.
What must be designed for adoption to become repeatable
The key conditions that allow teams to move fast while staying coherent, safe, and value-generating.
What this means for the decisions you make next
The shared language and perspective to help participants see where to focus — and where deeper work is usually required.
How the breakfast seminar works
Breakfast & arrival (08.00–08.30)
Informal arrival, breakfast, and light networking.
Guided discussion (08.30–10.00)
Each topic covered start with setting context. Followed by guided discussion to engage, validate and challange persepctives.
+ Q&A, sharing & networking (after 10.00)
The official session ends at 10.00. If you need to leave, this is a natural stopping point.
For those who stay, we open up for questions and participant scenarios and networking, using the shared language and tools from the first 90 minutes.
Who this is for
For people starting or already working with Data & AI and navigating the shift from pilots into normal operations.
Where progress depends on alignment between tech, transformation, and business
Who want a clearer picture of whatthe work actually involves
Sign up for free
From projects to practices: make AI normal
A breakfast seminar for people shifting AI projects into practices.
Location in Stockholm:
Sturegatan 15 Möten och Event by Hantverket – Ateljén
Date:
2026-03-30
Time:
08:00-10:00 + Q&A, sharing and networking
Includes:
Small Breakfast Buffé and Seminar + Q&A, sharing and networking
Limited seats
Upon sign up, you will be contacted by Katarina Liard to confirm your seat.
Contact
Katarina Liard
katarina.liard@dairdux.com
Fill in your details to get your FREE spot!
About the host
Henrik Göthberg is the founder of Dairdux, a Data & AI industrialisation company focused on systemic adoption — helping organisations move new capabilities from ambition into everyday practice.
Since founding Dairdux in 2019, Henrik has combined hands-on responsibility in large industrial organisations with research into systemic adoption — how organisations design work, governance, teams, and platforms so data and AI capabilities actually become normal. Since 2020, this work has been supported by a dedicated research track together with Mikael Klingvall, PhD in Computational Organisational Sociology, integrating insights from organisational research, complex systems, computer science, and Data & AI.
Alongside his work at Dairdux, Henrik has held leadership roles in large industrial organisations, owning responsibility for moving data and AI from experimentation into real operations. He is also Chairman of Data Innovation Summit and co-host of the AI AW Podcast.