By Jordi Daniels, founder of AI Board · ·
As a manager you need four AI skills. You ask the right question, trace the answer back to its source, know what must stay out and know what you keep doing yourself. A course is not required. The fastest way to learn is one recurring task, done with AI for four weeks.
Search for AI for managers and you mostly find courses. The assumption underneath is that you must learn before you may act. A course does not have to come first.
The job changes faster than a curriculum can be written. What works is the reverse order. You start with the work already on your desk, and the skill grows along the way.
This article is for the employed manager: team lead, head of department, member of the management team. You answer to a board or a director.
Below: the four skills, when a course helps, your work week with AI, the tools you may use and a page per management role.
The four AI skills of a manager
None of the four is coding, and none is memorising clever phrasing. It is judgement, applied through a new instrument. Run through the checklist and see which you already have.
- You ask the right question. A vague question gets a vague answer. "How is my department doing" is not a question. "Which three deliveries are about to miss their date this week, and why?" is one.
- You trace the answer to its source. An answer without a traceable source is an opinion with confidence. Keep asking until you see the underlying line, booking or ticket.
- You know what stays out. Personal data, medical information, an employee file, a contract under confidentiality. This is where the biggest risk sits.
- You know what you keep doing yourself. Judging, delivering bad news, persuading someone, taking a decision whose consequences land with you. You do not delegate that to a model.
All four are best practised on your own data. In a classroom without your numbers, it stays theory.
AI course for managers: when it helps, and what it costs
A course makes sense when you want the basics and the risks clear quickly. Or when your employer offers training and makes time for it. Pick one where you practise on your own work.
A course is not mandatory. For organisations in the EU, the European Commission states that no certificate is needed. An internal record of trainings and other initiatives is enough.
We only list courses whose price and duration we could check on the provider's own page. For English-language courses we have not done that check, so there is no comparison table here.
The Dutch version of this page compares six Dutch open trainings.
What a course does not solve: your own questions, your own data and the habit of asking them every week. A course is a starting gun. The skill only forms afterwards, in your work week.
Your work week with AI: what you do yourself
The change is not a new agenda item. It sits in the digging that precedes your existing agenda items.
| Task | The question you ask | What AI gives back |
|---|---|---|
| Monday status round | "Which three deliveries are about to miss their date this week, and why?" | A list with the cause and the source per delivery |
| Preparing the management meeting | "What deviated from plan this month, and why?" | The deviation, the cause and a draft of your proposal |
| Meeting a customer or supplier | "What actually happened with this customer over the last six months?" | A timeline from mail, tickets and notes |
| A new policy or contract | "What changes for my team, and in which clause?" | A summary that points to the passage |
| Friday wrap-up | "What moved in my department, and what needs a decision next week?" | A short list of decision points |
You no longer ask four people where things stand. You pull the status from the systems your team already works in, and use the round for what stands out.
What you do yourself stays the same: choose the question, check the source and make the call. AI does the digging in between.
Which AI tools may you use as a manager?
As a manager you handle data that is not yours. Employee files, customer data, numbers that may not go public yet. So the question is not which tool is smartest, but which one you may use.
In practice you meet three kinds.
- AI inside software you already have. Think of Copilot in Microsoft 365 or an assistant in your CRM. Its safety depends mostly on the permissions in your own environment.
- A general chat assistant on a business account. Business accounts fall under different terms than free personal ones. For work, use only the account your employer contracted.
- A personal assistant on your own files. It works with the documents and numbers you already have access to. Here too: only with your organisation's approval.
A personal account belongs in none of the three. One wrong paste is then an incident with your name on it.
Ask every tool the same three questions. Where is the data stored? Is it used to train models? Can you have it deleted? If there is a policy, follow it. If there is none, ask your manager or security officer.
Full disclosure: our own product sits in that third kind.
AI Board is your personal AI assistant that makes you AI-native: it runs on your own laptop, grounded in your company's data, and gets sharper as your knowledge grows.
AI per management role
How AI fits your work differs per discipline. Every role below has its own page with the questions you ask your own data. The overview with research per role is on AI for management.
Leadership and strategy
- AI for CEOs: walk into the MT with numbers you can defend.
- AI for general managers: the P&L is yours, the staff functions aren't.
- AI for strategy managers: know whether the plan is landing, before the MT asks.
Finance
- AI for finance leaders: ask your own numbers, get the answer before the meeting.
- AI for controllers: answers you can re-check, grounded in your own numbers.
Operations, procurement and service
- AI for COOs: one ops number that reconciles.
- AI for operations managers: delivery and capacity, with the orders about to run late.
- AI for procurement managers: OTIF, price increases and contract renewals, answered from your own files.
- AI for customer service managers: the AI that answers to you, not to your customers.
HR
- AI for HR directors: workforce cost, attrition and succession, grounded in your own files.
- AI for HR managers: absence, retention and headcount, answered from your own files.
IT and engineering
- AI for CTOs: ship dates, cloud cost, pentest triage and tech debt, answered from your own files.
- AI for CIOs: your application landscape, security posture and shadow IT, answered from your own files.
- AI for IT managers: your own IT data, answered before the CFO, the auditor, or the renewal deadline forces it.
- AI for engineering managers: walk in with the cause named, not the apology.
Product
- AI for product leaders: portfolio decisions grounded in your own product data.
- AI for product managers: stop guessing whether anyone uses what you shipped.
Marketing and sales
- AI for CMOs: the marketing number that survives the CFO opening the model.
- AI for marketing managers: prove pipeline contribution and where every euro went.
- AI for sales managers: pipeline truth, forecast honesty, and the deals about to slip.
Legal and compliance
- AI for in-house counsel: know what is true in your own registers.
Is your role missing? Pick the one closest to your data. The questions differ per discipline, the four skills do not.
Your team and AI: what you ask of your people
Your team is not waiting for you. Many employees already use their own AI tools at work, often out of sight. How big that is, with sources, is in the shadow AI economy.
A ban does not fix it. It pushes the use further into the shadows, onto personal phones and home laptops. So ask four things of your people.
- Openness. Whoever uses AI says what for and with which data. No blame afterwards.
- A source for every number. The rule that applies to you applies to your team.
- One example a week. Show in the team meeting what worked and what went wrong.
- A short record. Note who learned what. In the EU, that counts towards evidence of AI literacy.
Go first yourself. A manager who shows their own questions and sources makes it safe for the team to do the same.
Will AI replace the manager?
Not the leader, the relay layer. Gartner predicted that through 2026, 20% of organizations will use AI to flatten their structure. That would eliminate more than half of current middle-management positions.
What goes is coordination: collecting status, summarising, passing it up. Judgement, coaching and decisions stay with people. The full answer is in will AI replace managers.
Your first week
Five working days, one task. You need no budget and no project.
- Monday: pick one recurring task, ideally your status round or your management-meeting prep.
- Monday: check which AI tools your employer allows. If nothing is arranged, ask.
- Tuesday: ask three questions of data you are already allowed to see.
- Wednesday: check every answer down to the source and note where it went wrong.
- Thursday: use one answer in your real work, with the source attached.
- Friday: write down in five lines what it delivered. That is your first piece of evidence.
Repeat this for four weeks with the same task. Then you know whether you need a course, and if so which one. To take it wider across the company, read how to implement AI in your business.
Frequently asked questions
Do I need an AI course as a manager?
No, a course is not required. It helps to get the basics and the risks clear quickly. The skill itself only forms when you use AI in your own work, on your own data.
Which AI course for managers should I pick?
We do not rate course quality. Look for three things. Do you practise on your own work? Does it cover risks with company data? Can you carry on with it the week after?
What does a manager need to know about AI?
Four things: which question to ask, where the answer comes from, what must stay out and what you keep doing yourself. Coding is not on the list. Memorising prompt tricks is not either.
Is AI literacy mandatory?
In the EU, yes, for organisations that use AI professionally. Since 2 February 2025, Article 4 of the AI Act requires them to take measures that support the AI literacy of their people. No certificate is needed for that.