A survey
Asks people how often they use AI.
A snapshot of what people remember, and next quarter you have to send it out again.
AI usage monitoring
AI usage monitoring: measure AI use without tracking people.
Is AI being used in your organisation, and by how many people? AI usage monitoring answers that: how many people, how often, with which tools and for what. That question is about the organisation, not about a person, and the answer should be too. BeeSensible counts anonymously, without a user ID. An administrator sees that three people use AI daily, never who. Anyone searching for AI adoption software ends up with the same question: are the licences being used, and what else is going on?
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app.beesensible.eu/insights/usage
AI tools in use
7
Newly discovered
2
The problem
You bought licences. Are they being used?
A board wants to know whether AI has arrived in the organisation and where the work is changing. The figures that exist come from one vendor's admin centre or from a survey. What is missing is a view of the whole organisation, without a profile of every employee.
The admin centre counts licences, not work
The Microsoft admin centre shows who has activated Copilot. It says nothing about ChatGPT, DeepSeek or the AI feature inside a tool the team already had.
The survey measures what people remember
If you asked in spring which AI tools are in use, you have an answer about spring. New tools have arrived since.
Measuring starts to look like tracking
Many tools that measure AI use do so per person. That turns the measurement into a monitoring facility, which brings in the GDPR and the works council. You need none of that to know whether AI is being used.
Features
Which features AI usage monitoring needs, and what BeeSensible covers.
The term covers everything from a licence counter to employee monitoring. These are the features that belong to measuring AI use, and for each one, whether BeeSensible covers it fully, partly or not at all.
| Feature | What it does | BeeSensible |
|---|---|---|
| Share of employees using AI | How many people use AI, set against the number of seats. | Yes The Usage screen. Reported as an anonymous count, with no user ID. |
| Frequency of use | How many people use AI daily, weekly or occasionally. | Yes Without a user ID. The organisation sees "three people use AI daily", never who. |
| Prompts over time | How the number of prompts changes from week to week. | Yes Counts, no content. |
| Which tools | Which AI tools are in use, including the ones nobody requested. | Yes Only the tool's domain, counted anonymously. |
| What AI is used for | The split across seven kinds of work: writing communication, marketing and content, summarising, rewriting and editing, translating, coding and technical, analysis and knowledge. | Yes The first prompt of a conversation is classified and discarded straight away; only the label is counted. |
| Share of use through allowed tools | How much of the AI use runs through tools the organisation has allowed, with its trend. | Yes On the Compliance screen. The figure that shows whether the policy is taking hold. |
| Per-employee view | See who uses which tool and how often. | No Deliberately not. The usage figures carry no user ID, so it cannot be reconstructed later either. |
| Productivity score per person | A number per employee for how much AI someone uses or produces. | No Deliberately not. The figures describe the organisation, never a person. |
| Exports and API | Export the figures as CSV or PDF, or fetch them through an API. | Partly The AI register exports as CSV and as a PDF report over a period, with usage per tool, and Accountability as PDF. The Insights screens themselves have no export, and there is no public API. |
What it does not do
Where measuring stops and tracking would begin.
The line between measuring AI use and tracking employees lies in the design, not in a setting. This is where BeeSensible stops.
- No user ID and no content. Nothing records who did what, and the only thing counted about the purpose of use is a category label.
- No per-person view and no productivity score. Department figures only appear for groups of at least 5 people, over at least 7 days.
- No public API. Exports exist for the AI register (CSV and PDF) and for Accountability (PDF).
The approach
From a measurement to a decision you can back up.
Measuring AI use is the first of four steps. The figure only becomes useful once a decision, a notice and evidence follow.
1 See
Measure what happens across the organisation
How many people use AI, how often, with which tools and for what. Counted anonymously, reported without a user ID.
2 Decide
A decision per tool
What you see calls for a choice: allowed, limited use, not allowed, or deliberately no decision yet. The organisation chooses.
3 Help
The decision, when someone opens the tool
Anyone who opens a tool the organisation has decided on sees that decision in the browser, with the alternative first. People can still continue, unless the organisation has chosen otherwise.
4 Substantiate
The trend after the decision
The share of AI use through allowed tools, with its trend, and how often a notice was followed. That is the figure a board can use.
and again How the cycle works
Why this approach
Why a survey or the admin centre does not give the whole picture.
Three ways organisations currently try to get AI use into view, and what each misses.
Licence use from the Microsoft admin centre
Counts who has activated Copilot.
Sees one tool. The others stay out of view, and those are exactly the tools nobody has made a decision on yet.
Employee monitoring
Records which tools each person opens.
Delivers more than the question needs, and runs into the GDPR and the works council.
Frequently asked questions
What people ask before they choose.
What is AI usage monitoring?
Software that shows whether and how AI is used in an organisation: how many people, how often, with which tools and for what. The term is also used for tools that record what each employee does. BeeSensible does the first and deliberately not the second.
How does BeeSensible measure how often people use AI?
Each device keeps track of whether an AI tool was opened daily, weekly or occasionally this month, and reports only that category as an anonymous count, with no user ID. The organisation sees the distribution, never who is in it.
Can an administrator see who uses ChatGPT?
No. The figures on tool use and frequency reach the servers without a user ID, and the dashboard has no drill-down per person. An administrator sees that a tool is in use and how much, not by whom.
How does BeeSensible know what AI is used for?
The first prompt of a conversation in a major AI tool is classified into one of seven categories, such as summarising, translating or coding. The text is used only for that classification and discarded straight away; only the label is counted. The organisation decides whether this measurement is on.
Is an employer allowed to measure AI use?
Yes, with conditions. The GDPR asks for a purpose, proportionality and transparency. A works council has a say over facilities suited to monitoring. Measuring without a user ID and without content makes that conversation a lot shorter. The article on what an employer may check goes into more detail.
Further reading
More on measuring without tracking people.
See which AI tools are in use, and how.
Every module is included, with no user ID in the figures from day one.
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