All Use Cases

Measure your team's AI progress

Licenses bought, no idea what happened

You can see who on your team is set up, who is building things and who has not started.

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The Challenge

  • You pay for AI tools every month and cannot say who is really using them
  • Usage numbers tell you somebody opened the app, not whether they got anything out of it
  • You can name the two people who are good at AI. You cannot name the ones who gave up in week two
  • You announce a rollout, and three months later nobody can say how far it got
  • Training goes to everybody at once, because there is no way to tell who needs which part

The Runwork Solution

  • Each person gets a score across 4 dimensions: setup, usage, building and knowledge
  • The dashboard keeps setup, usage, building and knowledge on separate views, so they stay separate instead of blending into one number
  • You see who is set up, which AI tools they have installed, and who has not started yet
  • Weekly nudges reach each person about their own next step, so training is aimed rather than announced
  • The signals come from work people already do, so nobody has to file a report about their AI use

What your team gets

Who is set up, and who only said they were

The dashboard shows which AI tools each person actually has installed and connected, rather than who was sent an invitation two months ago.

The person who stopped in week two

Somebody started well and has done nothing since. That shows as a score that stopped moving, while there is still time to do something about it.

Where the gap really is

A team can be fully set up and still building nothing. Four separate dimensions keep those two problems apart, because they need different fixes.

Training aimed at one person

Each person gets a weekly nudge about their own next step, so the people who are already ahead are not sent beginner material.

The AI tools your team really uses

The list you pay for and the list installed on people's machines are rarely the same list. This shows you the second one, tool by tool.

Something to open before the rollout meeting

Where the team stands, in one place, so the meeting is about what to do next instead of about who has started.

A Day in the Life

9:00 AM. Monday, before the standup. You open the team dashboard and read the team as a list of people rather than a headcount. Who is set up, which AI tools are installed on their machine, who has built something, who has not started.

9:20 AM. One score stopped moving. Somebody who started well in June has not saved anything since. Nothing dramatic happened; they went back to doing it the old way. You can see that now, in June, rather than in December.

11:30 AM. The tools you pay for. Two people have never installed the AI tool the company bought for everyone, and one has been using a different one all along and getting good results with it. Both of those are useful, and neither was in the invoice.

2:00 PM. Set up, but not building. The setup numbers look healthy and the building numbers do not. Those are two different problems with two different answers, which is why the score is kept in four parts rather than averaged into one.

4:00 PM. The nudges already went out. Each person got a note about their own next step during the week, aimed at where they actually are. You did not have to write it, and nobody sat through training for a thing they already do.

5:30 PM. You know who to put together. One person is building things nobody else knows about. Two others are stuck at the same step. You pair them this week, and you can check next Monday whether it moved.

Frequently Asked Questions

Does this show me individual people or just team totals?
Individual people, by name. The team dashboard lists each member with their role, which AI tools are installed on their machine, and their score. That is deliberate: a team average hides the person who stopped in week two, and that person is the whole reason to look.
Can someone opt out of being counted?
Not individually. Telemetry is a workspace-level setting, decided once for the workspace rather than person by person, so if your workspace has it on, it is on for the team. What is measured is progress and activity, not the content of anybody's conversations.
How does Runwork know who is using AI?
From work people already do. Skills saved, AI tools connected, integrations set up, things built and run in the workspace. Nobody fills in a form and nobody reports their own usage, which matters because self-reported adoption numbers are the ones that look best and mean least.
What do the four dimensions mean?
Setup is whether their AI tools are connected and working. Usage is whether they are actually using them. Building is whether they have made anything that runs in the workspace. Knowledge is what the team has saved and can reach. They are scored separately because a team can be strong on one and flat on another, and the fix is different each time (4 dimensions, each with its own view on the dashboard).
What do I do once I can see it?
Two things the dashboard is built for. Weekly training nudges go to each person about their own next step, so you are not running the same session for people at five different stages. And you can pair the person who is stuck with the person already doing that kind of work, which usually beats any training you could book.

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