AI Strategy Basics for Executives
A clear, hype free grounding in what AI means for your organisation and how to lead the first steps
A taste of a lesson
Should we wait a year until AI settles down before doing anything?
Waiting on big commitments can be sensible, but waiting on learning is costly. Your staff are probably already using public AI tools, with or without rules. A middle path: publish a short usage policy now, let a few teams try low risk tasks, and measure what happens. That builds judgement cheaply and keeps big spending decisions open. Small exercise: list two tasks in your organisation where a wrong AI answer would be harmless and easy to catch. Those are good places to start learning.
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 in plain terms what today's AI does well and where it fails
- Identify where AI typically creates value inside an organisation
- Recognise the common reasons early AI efforts stall
- Draft a short AI stance and a first quarter plan for your team
Lesson plan
- 1 What AI is, in business terms Build a simple, accurate mental model of generative AI's strengths and limits. Start
- 2 Try it yourself Use an assistant on real non sensitive tasks and judge the results first hand. Start
- 3 Where value tends to appear Recognise the kinds of work where AI commonly helps organisations. Start
- 4 Why efforts stall Learn the common failure patterns so you can avoid them. Start
- 5 The leader's first moves Draft your AI stance and a simple first quarter plan. Start
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About this tutor
For executives and senior managers who need a sound mental model of AI to lead well, without becoming technical. You will learn what today's AI systems do well and badly in plain terms, where they tend to create value inside organisations, why many early efforts stall, and what a leader's job is in the first year: setting direction, picking a few use cases, putting basic guardrails in place, building skills and measuring honestly. Lessons are short conversations built around your own organisation. You leave able to explain your AI stance to your team in a few sentences, with a starter plan for the next quarter that you can adapt as you learn.
Reviews
4.7
3 ratingsSample
- Gerhard W.Sample
Short, direct and free of buzzwords. The three sentence stance exercise was what I needed before my leadership offsite.
- Aisha N.Sample
Useful grounding. The push to try tools myself for a week was the best advice. It covered the basics well, so experienced users may want more depth.
- Pablo R.Sample
I came in sceptical and left with a sensible plan for the quarter and better questions for my CTO.
About the teacher
Helps leaders choose AI work that pays for itself and drop the projects that do not
9 tutors 353 lessons taught Sample
I teach managers and executives how to make sound decisions about AI without needing to become engineers. My background is in strategy and operations work inside companies, where I spent a lot of time turning vague ambitions into projects with a budget, an owner and a way to tell if they worked. I teach with real decisions: a use case...
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