AI for non technical managers
Understand AI well enough to lead your team, ask good questions and avoid expensive mistakes
A taste of a lesson
A vendor says their AI tool will save my team 30% of their time. How do I check that?
Treat it as a hypothesis to test, not a fact. Ask the vendor where the figure comes from: which customers, which tasks, measured how, and whether it includes time spent checking outputs. Then run your own small trial: pick one task, measure how long it takes now and its error rate, give the tool to a few people for a few weeks, and compare, including review time. Decide in advance what result justifies buying. Which task in your team would you pick for the trial?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Explain current AI strengths and weaknesses in business terms
- Distinguish using, configuring and building AI and their costs and risks
- Ask the questions that test an AI proposal from a colleague or vendor
- Run a small, measured trial with a baseline and honest comparison
Lesson plan
- 1 What AI does well and badly Build a decision relevant picture of current AI. Start
- 2 Use, configure or build Understand the three ways to adopt AI and their costs. Start
- 3 Data, privacy and risk Know the risks a manager must address before rollout. Start
- 4 Questions that test a proposal Probe AI proposals and vendor claims effectively. Start
- 5 Running a fair trial Measure whether AI actually helps on a specific task. Start
- 6 Leading your team through it Support people while keeping accountability clear. Start
Try asking
About this tutor
For team leads and managers without a technical background who are expected to make decisions about AI. You learn the essential concepts in business language: what current AI does well and badly, the difference between using a general assistant and building a system, why output quality varies, where data and privacy risks lie, and how to judge a proposal from a colleague or vendor. You practise asking the questions that expose weak plans, setting sensible expectations with your team, and running small, measurable trials. No coding and no jargon without explanation.
Reviews
4.5
4 ratingsSample
- Sarah K.Sample
Practical and clear. The use, configure, build framing helped me explain to my director why our 'quick project' was not quick.
- Wei L.Sample
Good grounding for managers. Leading the team lesson was a bit short, I would have liked more on handling job anxiety.
- Gillian M.Sample
The question list for proposals is now in my notebook. I used it in a vendor meeting and their answers were very revealing.
- Rashid A.Sample
No jargon, straight to decisions. The trial with a baseline showed a smaller gain than the vendor claimed, but a real one.
About the teacher
I help managers and teams use AI at work safely, with clear oversight and sensible rules
9 tutors 337 lessons taught Sample
I teach AI for the workplace from the angle of people who have to make decisions and answer for them. My learners are managers, team leads and staff who want to use AI without leaking data, misleading customers or handing judgment to a machine. We cover safe everyday use, oversight that works, regulation in broad terms, data protection principles and...
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