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AI Adoption Lead

The course moves from understanding AI to identifying where it creates value, testing it in practice, and driving adoption across an organisation. Across three phases — Self, Systems, and Others — you will combine new knowledge with fieldwork in your own professional context. 

Phase 1 — Self: Understanding enough to lead (Weeks 1–4)

In the first weeks, the learning journey starts with a self-assessment of your AI Literacy and skill level. You will gain core knowledge of LLM:s, AI systems, mapping your personal leadership skills, and how to do an inventory of your organisation. You will be up to date with the latest models and prompting techniques, as well as frameworks for change. 

You will define a real problem/process/change and assess the impact and resources needed. You will work with AI tools to frame problems, brief collaborators, compare options, and surface assumptions. Define the opportunity, map the stakeholders, identify the risks, and name the permission you need to proceed. You'll end with a personal AI mandate brief, having built your capacity to interact with and use AI tools. 

Phase 2 — Systems: Seeing where AI creates value (Weeks 5–10)

This section explores AI's role in a larger context. You will work on your own project while adding new knowledge, perspectives, and technical skills. Step by step,  you will build the foundation for AI adoption by mapping workflows, identifying technical guardrails, and applying ethical and legal considerations. Look at AI implementation using a systemic approach, create roadmaps and develop strategies. 

Test your idea/project in the field, meet real experts, prototype and iterate on your ideas.In the fieldweek, you will present what you learned from the field. What worked, what failed, what stakeholders said, what risks appeared. Structured peer review, honest feedback, and a clear decision: stop, continue, or redesign.

Phase 3 — Others: Bringing people with you (Weeks 11–15)

With a clear brief and your idea ready to be challenged, you move to the third module where you will focus on communication and leadership. You will practice communicating with stakeholders, from CFO to CTO and board members. Practice the real conversations using the Manager's AI Conversation Pack. 

Learn to bring stabilisers and explorers into the same room and design the adoption conditions that make change stick. Revise the case, sharpen the story, prepare the roadmap, and rehearse the conversations. The work becomes something you could bring to a real decision-making meeting this week.

Present your AI Leadership Case — pilot, roadmap, or prototype — to the full cohort and invited industry guests from the Berghs network. Receive structured feedback from peers and practitioners. The AI Adoption Field Kit is complete. Certificate awarded.

What you'll leave with:

• A real AI adoption case, built in your organisation
• A clear 90-day roadmap for AI adoption
• Practical methods for engaging stakeholders and navigating resistance
• Working knowledge of LLMs, prompting, agents, automation, ethics & governance
• Methods for identifying, testing, and prioritising AI opportunities
• A professional peer network across sectors and organisations

This course is for people who have already used AI properly and suspect the problem is not the tool. Communication leads, managers, strategists, consultants, operations people and founders. This course is suited to anyone who is expected to answer for how AI gets used in their organisation.

This course is deliberately tool-agnostic. If your organisation uses Microsoft Copilot, that can be your starting point. If you are free to explore, you might work with tools such as Claude, Lovable, or n8n. We will map the current tool landscape, share recommendations, and encourage you to experiment while focusing on the tools that move your project forward.

Tools explored across the course may include a selection of tools such as Claude, ChatGPT, Gemini, Microsoft Copilot, Lovable, n8n, LangChain, Copilot Studio, NotebookLM and Perplexity. Subscriptions for these tools are not included in the course fee.

Do I need any prior knowledge?

We require at least 3 years of experience in a leadership or management role and a working level of English. You should have practical experience with and an understanding of the AI tools relevant to your profession. You also need a real context: an organisation, team, process, or challenge to work on during the course.

Course fee

Fee excl. VAT
39 000 SEK

Fee incl. VAT
48 750 SEK

Additional Information

By clicking "REGISTER" on this page, you take your first step towards enrolling in the course. At this point, there are no financial commitments. Only after registering for the course will you be asked to complete payment to secure your spot. Once you have completed payment, your registration for the course is complete.