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AI at the company: from pilot to production

Ten steps from “we tried it and it fizzled out” to specific processes running on AI, with an owner for each of them.

Who it is forFor managers and team leads who are not rolling out AI for the sake of AI.

Total time
3 h 2 min
Steps
10

Progress

0 of 10 done

About 3 h 2 min left

  1. AI in the company: the complete rollout guide — from data to measurable resultsTip · 35 min

    You have a map of the whole rollout and know which phase you are in.

  2. Five levels of working with AI: from chat to agentChapter · 12 min

    You name how far you want to go — and how far you do not.

  3. MCP connectors: USB-C for AITip · 15 min

    You understand how AI connects to company data without copying it anywhere.

  4. Which tools have an MCP connector, and what you can actually do with themTip · 20 min

    You have the first system connected that the team genuinely reads from.

  5. The meeting that doesn't eat your day: a complete system with AITip · 20 min

    Meetings have an agenda, notes and tasks that someone actually receives.

  6. Meetings that write themselves up — down to the tasks in your task listTip · 15 min

    Notes write themselves and nobody types them up any more.

  7. Delegate the outcome, not the processTip · 12 min

    An assignment carries its context, so the work does not bounce back.

  8. Your first no-code AI automation: trigger, AI step, draft for approvalTip · 25 min

    The first process runs without you, holidays included.

  9. Processes: what to automate and what to leave to peopleChapter · 14 min

    You know what is worth automating and what is just mess in a nicer wrapper.

  10. Introducing change: why most improvements die at the pilotChapter · 14 min

    The change survives its first month, because it has an owner and a measure.

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What next

The path that follows

Data without spreadsheet hell

Open the path →All the paths

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