Insights ·
Corporate AI Training: What to Check Before Day One
Whether corporate AI training sticks is largely decided before the first session. Check four points in time. Two weeks out, pick the roles, two or three real tasks per role, and the attendee list. One week out, prepare anonymised practice material and confirm the tool used in class is allowed and accounts are ready. On the day, explain the rules for using company material first, then have each person work on their own task. Two weeks after, check who is still using it and on what, then decide the next step.
A common pattern after corporate AI training: a lively session, then business as usual. The cause is rarely the teaching itself. More often, things that should have been ready before class were not: no agreed practice tasks, unusable material, tools that would not open, and no one checking in afterwards.
So rather than fixing things after the fact, move the checks before the first session. Split them across four points in time: two weeks out, settle roles and tasks; one week out, prepare material and tools; on the day, set the rules; two weeks after, review how it is being used. Check a few items at each point and fix any gaps before moving on.
1. Four checkpoints in one table
| When | What to check | What tends to happen if it is missing |
|---|---|---|
| Two weeks before | Roles, two or three real tasks per role, attendee list and timing | Only generic examples in class; people do not know how to apply it |
| One week before | Practice material anonymised, rules for company material written, tools and accounts ready | Half the session goes on sign-ups and hunting for files |
| On the day | Rules explained first, everyone brings a task, someone logs sticking points | People are afraid to use it or use it carelessly; problems are never collected |
| Two weeks after | Who is still using it, on which tasks, where they get stuck | No way to judge whether it was worth it or what to do next |
2. Two weeks before: roles, tasks and people
Pick roles first; do not aim for everyone. Starting with two or three roles that have plenty of repetitive, fairly rule-based work makes change easier to see than a company-wide lecture.
Set two or three real tasks per role. For example, compiling a weekly report, drafting standard replies, or checking that a document set is complete. Define each task down to what goes in and what the finished output looks like, so it can be practised in class.
Fix the list and the timing. Put people from the same role in the same session so they can compare notes, and bring the manager who makes decisions into the closing part; the sticking points they hear will shape what comes next.
3. One week before: material, rules and accounts
Make practice material usable as is. Take it from real work in the role, replace client names, amounts and account numbers, and keep the original format and difficulty.
Write the rules for company material on one page. Which material may go into the tool, which may not, and who answers the unclear cases. Send the page before class and go over it again at the start.
Test tools and accounts in advance. Which tool is used in class, whether the company allows it, whether accounts are set up, and whether the office network can reach it: ask the coordinator to run through it on an ordinary office computer beforehand. If people get stuck at login, the rest of the practice suffers.
4. On the day: rules first, then hands-on
Spend the first ten minutes or so on the rules for company material and on which outputs must be confirmed by a person; this matters more than a tour of features. Then each person works on the task they brought, with the trainer and a colleague who knows the work walking the room.
Have one person log sticking points: where people could not continue, and which material they were unsure about using. That log is the starting point for the follow-up.
5. Two weeks after: review, then decide
About two weeks after the session, ask three questions: who is still using it, on which tasks, and where they get stuck. If the sticking points are about material rules, add a one-page clarification; if they are about usage, add a short practice session.
If a role wants AI to query business data or connect to internal systems, that goes beyond training and needs its own plan. The systems then need to be built so AI can connect to them; see AI Integration, and for custom business systems, Systems. If you want AI assistants and search engines to understand your company website, see How to make your website easier for search engines and AI to cite.
FAQ
Do we need to pick roles before the training?We recommend it. Once roles are set, tasks and material can be prepared properly; a single session for everyone rarely fits each role's actual work.
Should practice material be real or made up?Take it from real work and replace the sensitive details. Entirely invented material is hard for people to map back to their own jobs.
When should the follow-up happen?About two weeks after works well: earlier, habits have not formed; later, the sticking points have been shelved.
Does FIM offer corporate AI training?Beijing FIM Network Technology Co., Ltd. offers corporate AI training, taught by the day and not tied to any purchase, for management, business and technical teams, covering what AI can and cannot do and working through real workflows.
Summary
Before corporate AI training, check four points: two weeks out, roles, tasks and people; one week out, material, rules and accounts; on the day, rules first, then hands-on; two weeks after, review usage and decide the next step. Fix any gaps at each point before moving on.