Workforce Training

Everyone who uses AI should know when not to trust it: a practical AI literacy baseline for your whole workforce, no engineering background needed.

Everyone who uses AI should know when not to trust it.

AI literacy is a baseline for your entire workforce. People across operations, finance, sales, HR and other functions need to understand what AI can help with, where it can fail and what remains their responsibility. No engineering background is required.

Start with a real task. What problem are you trying to solve? What information does AI need, and what should you withhold? How will you check the result before someone relies on it? Those questions give people a practical basis for using AI in their own work.

What people take into their work

A shared language for discussing AI, practice giving it useful context, and a habit of checking output before acting on it. Build on that baseline with guidance for the systems, information and decisions each role handles.

Choose the right starting point

AI Literacy & Foundations is the workforce baseline: one live online session of about two and a half hours covering how AI works, the Seven Principles of AI Leadership (seven plain rules for using AI well at work), how to give AI useful context, and a short written description of each participant’s role that AI can work from. It is delivered the same way for a team of fifteen or a cohort of several hundred.

AI Assistant Training is the next step for teams who want to put that role description to work: a half-day, hands-on session building an assistant on your approved platform from your objectives, terminology, roles, problems and rules.

If leaders have not yet agreed purpose, information boundaries and responsibility, start with leadership alignment; our Kendall partnership page sets out the starting sequence. If you already have a specific problem, go straight to AI Opportunity Discovery; training is not a prerequisite. If the EU AI Act brought you here, Article 4 and AI literacy covers what it asks of you.

Put the learning to work

Participants leave with a starting point, not an assistant ready for operational use. Applying it to an organisational workflow needs an owner, agreed information boundaries and checks before anyone relies on the result.

Choose one task and define what acceptable work looks like. Use information you are permitted to share, check the output against its sources and follow what happens after it leaves the person who created it. Count the time spent reviewing and correcting it when deciding whether the change helped.

Assign someone to keep the supporting information current, review failures and decide when use should stop. An assistant that helps you prepare work and an agent authorised to act on a system need different controls; engineering support is available when permissions, integration or recovery need technical work.

If AI work is already creating rework, or its use is unclear, start with the problem you can see.

The courses

Fixed price, agreed before work starts. Each card takes you to the full curriculum and booking details.

Give everyone the habit of checking before they rely on AI

Tell us who needs the baseline and what they use AI for today. We can scope the appropriate course and cohort, with a fixed price agreed before work starts.

Scope it for your organisation