Coming soon

Upcoming masterclass: Data × AI initiative steering

From AI ambition to
everyday practice

Putting AI on the agenda

Making sense of AI before committing to platforms or programs.

Starting from the right end

Pinpointing business friction before choosing Data-AI solutions.

Scaling adoption

Moving from pilots to everyday operations — unlocking value from data & AI investments.

Designed interventions — choose the format that fits where you are right now

For the individual

Open camps & clinics

Seminars and Master Classes

Sessions for individuals who want to see beyond their role and build a common framing for data & AI.

Tailored For companies

Tailored interventions

Kick-off, courses, internal events & camps

Focused interventions designed for one organisation, one moment, one mandate.

Partnership

Longer engagements

Enterprise Data-AI reform design

Partnering over time to sequence the interventions that enable data & AI to scale in operations.

“Most data & AI initiatives don’t fail because the technology is wrong. They fail because everyday ways of working don’t change.”

What we have seen

Most organisations don’t struggle with data & AI because they lack ideas or skills. They struggle because new technology is added, while everyday practices stay the same.

The real issue; how work is organised, how decisions are made, and how teams collaborate. When we don’t change together in a cohesive way. When new practices move at different speeds in different parts of the organisation, even good initiatives slow down or stall.

AI Camp

What makes AI work

Progress comes from changing how work is done, step by step, as organisations move forward. Early on, it’s about exploring real problems in everyday work. Later, it’s about making what works easier to repeat and scale.

Data AI Camp is built around designed interventions. These interventions help organisations see what actually changes things, and adjust how work, teams, data, and technology fit together as they scale.

Our network of experts

We work with some of the greatest minds behind the scenes of AI, each experts in their own field, with years of documented experience.

Henrik Göthberg

CEO & founder Dairdux

Founder of Dairdux, Chairman of Data Innovation Summit and co-host of the AI AW Podcast.

Mikael Klingvall

Mikael Klingvall

Head of research Dairdux

Paolo

Paolo Platter

CTO - Co-founder at Agile Lab | Product Manager on Witboost

Alberto

Alberto Firpo

CEO - Co-founder at Agile Lab

Alagan

Alagan Mahalingam

Founder & CEO of Rootcode

The driving force behind Rootcode, which consists of Rootcode Labs, Rootcode AI, and Rootcode Studio.

Nicholas

Nicolas Averseng

Chief Product Officer | DataGalaxy

Founder of Dairdux, Chairman of Data Innovation Summit and co-host of the AI AW Podcast.

Our partners

The Dairdux Consortium

Rootcode
Agilelab
Datagalaxy
Scaleout
Scling

Frequently asked questions

What is Data AI Camp?

Data AI Camp is an immersive learning experience designed to help organizations move from experimentation to real, scaled adoption of Data & AI.
It combines hands-on work, strategic framing, and real-world application in a focused, offsite environment.

Who is it for?

The camp is designed for decision-makers and practitioners responsible for driving Data & AI initiatives, including:

  • CDO and data leadership functions
  • Transformation and L&D leaders
  • Business unit leaders working with AI adoption

What problem does Data AI Camp solve?

Many organizations are stuck between pilots and real impact.
Data AI Camp helps you:

  • Turn fragmented initiatives into coherent systems
  • Move from “AI hype” to everyday practice
  • Build the capability to scale safely and effectively

What makes Data AI Camp different?

Unlike traditional training or conferences, the camp:

  • Focuses on your real context, not generic cases
  • Combines strategy + execution
  • Uses a high-intensity, distraction-free setting
  • Emphasizes flow and continuity, not one-off inspiration

What will participants actually do?

Participants will:

  • Work on their own real use cases and challenges
  • Translate strategy into concrete actions and structures
  • Learn frameworks for scaling Data & AI adoption
  • Collaborate with peers facing similar challenges