Your Data and AI: What to Paste and What Not To
"Do not paste sensitive data into AI tools." Advice you hear everywhere, and nobody follows — because it does not say where the line is.
Why “Do Not Paste” Fails as Advice — and What Actually Happens
By the end of this lesson you will be able to:
- Understand why “do not paste data” fails in practice, and what replaces it
- Know the five things that actually happen to what you paste
- Treat an AI tool as a third party rather than a special case
- Identify the three behavioural differences that make it riskier than any supplier
The scene that repeats in every office every day:
An eight-page contract arrives. You open an AI tool, paste it in, and type: "summarise this and tell me
which clauses are risky."
And within two seconds, a contract containing names, amounts and terms has left your control.
And nobody will blame you — because the tool gave you in a minute what would have taken an hour. **And that
is precisely why the problem is hard: the benefit is real.**
Why "do not paste data" fails as advice
The prevailing advice is "do not put sensitive data into AI tools." It fails for two reasons:
1. Nobody follows it. Because the work has to get done, and the tool gets it done.
2. It does not say where the line is. What counts as "sensitive"? A customer name? An invoice number?
A contract? With no definition, everyone decides by instinct.
And a ban that is not followed is worse than none, because it pushes the use into hiding: the employee
uses the tool from their phone rather than asking you, and you lose both the ban and the visibility.
**This course does not ask you to ban it. It asks you to know what you paste, and for your team to know it
by a rule they can apply in three seconds.**
What actually happens to what you paste
Without alarm and without minimising — the structural reality:
1. It leaves your device. It is sent to another company's servers to be processed. That is not a flaw in
the tool — it is how it works.
2. It is stored for some period. Most services retain conversations for a time, for operational reasons
and to handle misuse.
3. It may be used for improvement. Some services use what you write to develop their models and some do
not — and the difference is often between a personal account and a business account.
4. Humans may see it. Sampling for quality control or misuse review is a normal practice in this
industry.
5. It falls under the laws of wherever the servers are, which may be outside your country.
And not one of those five means "the tool is bad." All of them apply to your email and your cloud
storage too. The difference is that with email you know you are sending something, and with the tool it
feels like you are "asking a question."
The idea the course rests on
**An AI tool is not a special case. It is a third party — like your accountant, your system vendor and
your marketing agency.**
And you already know how to deal with a third party: give them the least they need, know **where your
data goes**, and sign something in writing.
So the question is not "is AI safe?" — a question with no useful answer. The question is:
Does this particular piece of information leave me, and to whom?
And the real difference from any third party
Three differences make it more dangerous in practice, and all three are **behavioural rather than
technical**:
1. There is no friction. Sending a file to your accountant is an act you decide on. Pasting is a passing
gesture that does not feel like sending.
2. There is no record. You know what you sent your accountant. **Nobody knows what your team pasted
yesterday.**
3. Every employee can do it. Engaging a supplier is a management decision. Opening an AI tool needs
nobody's permission.
And the third is the hardest: you do not have one gate to guard — you have the number of employees ×
the number of devices.
What you will leave with
- A classification list for your data: what may be pasted, what may be pasted after redaction, and what
never
- A one-page policy your team signs and can actually apply
- An approved tools list and the questions to assess any new tool
- An incident procedure: what to do when someone pastes something they should not have
What is not in this course
- No walkthrough of buttons or particular settings. Interfaces and policies change every few months, and
any course describing them becomes a source of error. You will learn what to ask of any tool.
- No comparison of models or which is smarter. Not our subject, and it changes faster than it can be
written.
- No opinion on AI itself. I use it daily. This course is about what leaves your side, not about the
tool.
And the legal question
Some sectors carry specific obligations around the confidentiality of client, patient and case data, and
some contracts contain confidentiality clauses forbidding sharing information with any third party — **and
an AI tool is a third party**.
Consult your lawyer, your syndicate, or the competent body about what applies to you specifically.
This is a course of practice, not of law.
Action steps
- Write honestly: what are the last three things you pasted into an AI tool?
- For each: would you have sent it to your accountant without thinking? And if not, why did you paste it?
- Ask yourself: do you know what your team pastes? And how would you know?
- Review your contracts: do they contain a confidentiality clause forbidding sharing with a third party?
- Write in one line: what are you most afraid of leaving your side?
That was the full sample — here is the rest
What you just read is one part. The full edition includes:
- All 8 lessons: what actually happens, the three-second rule, tools, your team, third parties, the output, the incident, and the capstone
- The hands-on task and quiz that close every lesson — neither is included in this sample
- The twelve questions for vetting any tool, four documents you leave with, and a 32-question audit
- A completion certificate in your name, in Arabic and English