AI training for non-technical employees
No code. No jargon.Just their own work, done better.
Short modules on the work people already do: the Monday inbox, the meeting notes, the contract, the deck, the spreadsheet. Each one ends in a check, so you know the skill stuck.
Priced per seat, per year.
The short answer
How do you train non-technical employees to use AI?
Use their own tasks, inside the tool they already have, and check the result rather than the watch time. Start with what may go into which tool and how to spot a wrong answer, then move to the weekly work: email, meetings, documents and data.
Train Space starts everyone on 14 short essentials modules, then sets the practice in each team's own work.
- Coding
- None
- Each module
- Watch, read, try on real work, check
- Pass mark
- 80%, scored on the server
- Department lenses
- HR, legal and GRC
- Live tool course
- Microsoft Copilot
What each team practises
Real modules,
set in real work.
A few of the modules each team meets first, with what the person can do afterwards.
| Team | Module | What they can do after it |
|---|---|---|
| Sales and account teams | How can AI prepare you for a supplier negotiation? | Prepare for a supplier renewal: build a pack, have the assistant play the supplier, map the trades, price your alternative, check numbers with finance, and set the walk-away yourself. |
| How do you answer a request for proposal fast, without inventing answers? | Answer an RFP only from your approved answer library, date-check every draft, route each gap to a named expert, and feed the answers back. | |
| What changes when AI can read your email, drive and CRM? | Connect a work app with the least access the job needs, keep reading apart from acting, spot a risky chat setup, and keep every send your own. | |
| Marketing and communications | How do you make AI drafts sound like your organisation? | Build a shared house-voice skill from varied real examples and banned phrases with replacements, test it blind with bad news, and keep fact-checking separate. |
| How do you adapt content for another market, not just translate it? | Brief an assistant with each market's glossary, house rules and restricted claims, check its options with independent back-translations, and get a native reviewer's approval. | |
| How do you get a deck that's on-message, not just pretty? | Agree one headline per slide before anything is built, build in the company template, and check every figure against the approved source. | |
| HR and people teams | How can AI help build a fair, structured interview without deciding who gets hired? | A department version of this module. |
| How do you practise a difficult conversation before it happens? | Rehearse a hard conversation against a tough made-up persona, out loud, then score yourself on three goals with your own quoted words. | |
| How do you turn "watch me do it" into a written procedure? | Get a job out of one person's head: record a real run, have AI draft it with guesses marked, check it against the transcript, and test it on a newcomer. | |
| Finance and operations | How can AI draft variance commentary without inventing the reasons? | Write variance commentary where every reason cites an owner's note, split mixed lines into rate and volume, and check every citation and figure. |
| How do you get AI to analyse a spreadsheet properly? | Get an assistant to describe your data, agree the method, log its cleaning with row counts, test other explanations, and rebuild one number yourself. | |
| How do you turn forty PDFs into one table you can trust? | Pull the same fields from a batch of documents into one table you can check: fixed columns, an example row, a quote per cell, and NOT FOUND when the document is silent. | |
| Legal and compliance | How do you get a first pass on a contract without missing what isn't there? | A department version of this module. |
| How do you catch what changed between two versions of a contract? | Get every change between two versions listed clause by clause, deletions included, then check the list against your word processor's compare. | |
| Which AI uses at work carry legal obligations? | Spot AI uses that decide people's jobs, money or services, and take them to legal with the right questions before launch. | |
| Everyone | How do you get through a 300-email Monday without letting AI reply for you? | Get a read-only briefing of what your inbox wants from you, check items at source, count what it missed, and reply yourself. |
| How do you turn meeting AI into action, not just notes? | Check an AI-drafted meeting follow-up against the transcript, restore the promises it missed, and send it with a line inviting corrections. | |
| What may be pasted into which tool? | Tier what you're about to paste in under ten seconds, send it only where that tier may go, and cut it down so a lower tier applies. |
The objections we hear
“Training isn't IT's job.”
Fair. So it shouldn't need IT.
No office hours to staff.
People work through short modules when the task comes up. Managers see progress without chasing.
Data rules come first.
What may be pasted into which tool, and which account to use, are among the first modules everyone takes.
The version on their screen.
Lessons are rechecked against vendor sources on a schedule, so menus and features match what people see this week.
A few good questions
Training people who aren't technical?
Start with their work.
Still wondering about something? Ask us and we’ll answer it here.
Ask your questionWhat AI training do non-technical employees need?
Four things: what the tools are and where they go wrong, what company data may go into which tool, how to ask for a usable result and check it, and how to use AI on their own weekly tasks, such as email, meetings, documents, decks and spreadsheets. None of it needs code.
Is there any coding in the training?
No. The general AI programs are written for people who use Word, Outlook, Teams, Excel and a chat assistant. Developers who use AI coding tools have a separate program, Secure AI coding.
How is it different for each department?
Department lenses rewrite each module's scenario and examples for HR, legal and GRC teams, and the library has modules set in sales, marketing, finance and operations work. A starting-point check places each person at the right level and in their department's version.
Which AI tools does it use?
The general programs teach skills that carry across tools. The Microsoft Copilot course is live and dated; courses for Claude, ChatGPT and Codex, and Google Gemini are in preparation.
How do we know it worked?
Each lesson ends with a check of at least eight questions, scored on the server, with 80% to pass, and use-case modules are completed with a record of the work the person did. Mastery fades, so a short refresh check follows a few weeks later. Managers see who is current as of any date.
Put the learning to work