How Will My Team Use It, How Are Rules Written?
Until AI usage rules are written, one of two things happens: either nobody uses it, or everyone uses it their own way. The second is more common and more risky. 👥
Short answer: not a ban but rules. Three lines suffice — what may be entered, what never may be, who approves the output. In a business that bans it, usage goes underground and control disappears entirely.
Below: the rule set, how training should run, resistance, and how to track usage. 🔒
How is the rule set written?
AI usage rules shouldn’t exceed one page.
The three-line core
1) May be entered: general product information, publicly available content, drafts you wrote. 2) Never entered: customer identity data, contract details, personnel records, payment data. 3) Approval: every output going to a customer or an official body passes human checking. With those three written, the risk becomes manageable. 📜
Why don’t bans work?
Because these tools are on phones too. A ban makes usage invisible; a rule makes it visible and auditable.
How should training run?
A one-off presentation is the least effective method.
Real work, short and repeated
Instead of a three-hour session, short rounds the team does with their own work. People learn while producing their own quote, not while watching a presentation. Someone sitting beside them in the first days beats ten videos. 🎓
Where does resistance come from?
And how is it resolved?
Two real fears
The first: “will I lose my job”. The second is quieter: “if I use it, will they think I’m not doing my own work”. Both hide behind “it doesn’t suit me” unless spoken. Stating the aim plainly — shortening the repetitions nobody enjoys — halves the resistance. 🗣️
How is usage tracked?
Not to police but to see where it jams.
Three monthly questions
Which job was it used for, which output had to be corrected, did anything fall outside the rules? These three get asked monthly and the template gets updated accordingly. Non-use is usually a sign that the template is incomplete — causes sit in the why-it-failed article. 🔍
How is shared memory built?
Rules and templates shouldn’t live in one person’s head.
A one-page company guide
Keep three things on one page: the rule set, templates by job, good and bad output examples. A new hire spends their first day with that page; knowledge doesn’t leave with a departing employee. That page is the lasting part of the setup. All questions on the business AI consulting page. 📄
📝 Field Notes
At one business management had banned it. When we asked, most staff were still using it from their own phones — and nobody knew what information was being entered. The ban was lifted, a three-line rule was written, a corporate account opened. The risk had been larger under the ban. Invisible usage is unmanageable risk. 🔒
📖 Quick Glossary
Rule set: the written statement of what may be entered. Corporate account: manageable access opened in the company’s name. Template: a reusable instruction skeleton. Human approval: checking output before use.
⚡ Quick Summary
Rules, not bans: three lines suffice. 👥 The corporate account is the first item. Training should be short and on real work. The template is half the training. Put the most resistant person on the pilot. Track with three monthly questions.
🎯 Next Step
Let’s write your rule set and first template together; it fits on one page: the quote page. Scope on the consulting page. 📄
Frequently Asked Questions
Sık Sorulan Sorular
The corporate one. When company information is processed on personal accounts, nobody knows what was entered, and access leaves with the departing employee. This should be the first line of the rule set — setup decisions sit in the ready-tool article. 🔑
Because everyone asking differently produces different results. A good template — what’s wanted, which information gets supplied, in what tone — makes output repeatable and shortens training. A team with a template doesn’t need to master the tool. 🧩
On the pilot team. Asking them to make the rule and template decisions turns resistance into ownership. It’s a method that has worked repeatedly in the field. 🔑
Identity and contact data shouldn’t be entered; but working with anonymised information is possible — “the customer” instead of a name, a range instead of an amount. That keeps the gain and removes the risk. Write that distinction into the rule set with examples.
The business. That’s why the rule that every outgoing output passes human approval gets written, making responsibility clear. The approval rule protects both the customer and the employee.
Both together. Management knows the boundary, the team knows the practice; a rule written by management alone doesn’t survive on the floor. One page written jointly holds better than a long manual.
Source: GDPR — data protection