AI Learning Networks
Scale your organization’s AI adoption though peer learning and change networks.
A 6-month program that turns individual AI expertise into shared organizational capability — through peer learning, not another training program.
Problem 1: Training is too general to be relevant
Most AI training and groups of mixed participants (like ambassadors or champions) are too general for content to be relevant for participants in their everyday work.
People get frustrated with abstract presentations and too general use cases that do not solve their acute needs in their job.
Problem 2: Current AI knowledge is not shared
In each organization there are hundreds of excited people experimenting with AI on a daily basis.
The problem is, they're learning on their own, and the learning is not shared with others.
Without a way to systematically share what's being learned, your organizaion keeps buying more training instead of activating the expertise you already have.
What is an AI Learning Network?
Experts from the same professional domain develop their AI use in practice and share what they learn with others.
A network of experts of the same profession eager to learn and develop AI use in the organization
Monthly meeting rhythm with practical demonstrations, experimentation and learning
Channels for sharing and use-cases, learning and insights with rest of the organization
A system for accumulating knowledge about valuable use-cases and learnings in the organization
There's no external trainer telling people what AI can do for them. Participants show each other what has been useful in their work — and commit to teaching it forward.
“Villiam has been the driving force behind making our AI program a success. What stood out most was his ability to create engagement and urgency around a complex topic like AI—without overhyping it.”
Learning network design
-
Practical use case demos
Paricipants present and demonstrate real AI use cases from their own work. A core principle is “Show, don’t tell”.
-
Shared prioritization
The network continuously prioritizes use cases together and chooses which ones will be featured during upcoming sessions.
-
Apply and teach forward
Participants take the most valuable use cases and apply them in practice and teach them forward. Learning and impact is systematically assessed.
-
Continuously improve
The network improves constantly through retrospectives, quantitative assessment, and a culture of shared ownership.
How the program is run
AI Learning Networks
-
We co-design the network concept with your core team. We find motivated participants for the netowk. We validate the concept with participants, and get the first sessions on the calendar. By the end of this phase, the network is ready to run.
-
1-2 hour sessions organized every 2-4 weeks. Participants surface AI use cases from their own work, we prioritize them together, and take turns demoing and practicing. Between sessions, participants teach what they've learned to their teams. We facilitate, iterate, and continuously improve the format
-
We gather the pilot's learnings, document what worked, and help you decide whether — and how — to scale the model across the organization.
Why it works
AI Learning Networks
Focus is chosen by participants
Experts with similar roles choose use cases relevant specifically to their work. This makes sessions immediately applicable and useful.
Hands-on Demos,
not lectures
Sessions are built around live demonstrations by participants — no long slide decks. Theory is added only when it serves learning.
Built-in knowledge
transfer
Participants are expected and supported to teach forward what they learn. This expectation is set from day one, which selects for people who want to share.
Psychological safety
by design
The facilitator creates conditions where people feel safe to ask, experiment, and admit what they don't yet know.
Ready to pilot your network with a proven design?
What you get from the pilot
A working peer-learning model you can replicate across teams and units
A system for collecting and accumulating AI knowledge in the organization
The model is handed over to your own facilitators (train-the-trainer)
A documented summary of AI use cases, learnings, and practical recommendations
A clear framework for deciding whether and how to scale the model to other teams
Investment and pricing
You will get a systematic network model that makes AI learning and sharing continuous and scalable across the organization.
The 6-month program includes co-design, facilitation of 4–6 sessions, continuous improvement, and hand-over to your facilitators. If you're running multiple networks concurrently, ask about volume pricing.
€22,400 + VAT
Who is this for?
The AI Learning Network Pilot works best for organizations that have already done some AI training — people are experimenting but that knowledge isn't spreading.
Typical group size: 8–20 participants from the same professional area. The model has been proven with legal teams, educators, and technology specialists.
You're a good fit if:
You want a practical model, not a heavy program or another vendor relationship
You're ready to pilot something and evaluate it honestly before scaling
You have a group of people who are curious about AI and willing to share what they learn