AI for Teachers: A Staff Presentation Outline With Activities

A staff presentation on AI for teachers works best when it shows rather than tells. Explaining what AI can do is less useful than demonstrating it with actual teaching tasks, discussing the results honestly, and giving teachers time to form their own judgments. This outline gives you a structure that can be adapted for a one-hour or two-hour session, with activities at each stage.

The goal is not to convince everyone to use AI, but to give the team enough shared knowledge to make informed decisions. Tools like fenbs help by keeping the prompts that worked, the allowed-use decisions the team agrees on, and any follow-up questions in a shared project that every teacher can read and add to.

Opening: frame the session honestly

Start by naming what the session is and is not. It is a practical introduction to what AI can and cannot do for teachers and students. It is not a mandate to use AI, not a policy announcement, and not a replacement for the professional judgment that teaching requires. This framing reduces defensiveness and opens the room to genuine exploration.

Useful opening questions to surface: What have you already tried? What concerns do you have? What would be most useful to understand by the end of the session? Note these on a shared board. Come back to them at the end.

Time: 10 minutes. Materials: whiteboard or shared digital board for capturing responses.

Section 1: What AI can do in teaching contexts

Walk through the concrete use cases: lesson planning, generating activity ideas, drafting feedback comments, creating rubric templates, differentiating material for different reading levels, and writing routine communications. For each one, give a real example from the context your school or department works in.

Activity: Live demonstration. Choose one task the group works on regularly, such as writing a discussion question or generating three examples of a concept at different levels. Run the task live with an AI assistant so participants can see the process and the result. Discuss: what did it get right, what did it miss, what would you change before using it?

Time: 15 minutes. Key message: AI produces a useful first draft, not a finished product.

Section 2: Limits and review steps

Cover the areas where AI is unreliable: factual accuracy, cultural sensitivity, age-appropriateness, and alignment with what the course actually taught. Give one example of an AI output that looks good but has a problem teachers would catch. Ask the group what the review step would be.

Activity: Spot the problem. Give pairs a short AI-generated activity or rubric and ask them to find issues before they would use it in class. Share findings. The point is not that AI always fails; it is that every piece of AI output needs a person to check it before it reaches students.

Time: 15 minutes. Key message: the review step is not extra work; it is how you use AI responsibly.

Section 3: Student use and academic integrity

This section needs honesty about the complexity. Students are already using AI. The question is whether your policies are clear, consistently applied, and actually teach students to use it well rather than to hide their use. Walk through the spectrum from full prohibition to disclosure-based permission.

Activity: Policy discussion. Give groups a set of assignment scenarios and ask them to decide: permitted, not permitted, or permitted with disclosure? Compare responses across groups. The discussion itself is valuable because it surfaces where the team agrees and where more clarity is needed.

Time: 15 minutes. Key message: policy clarity protects students and teachers equally.

Section 4: Hands-on practice

Give participants time to try AI with their own tasks. Ask each person to choose one thing they actually need to prepare in the next two weeks: a lesson plan, a set of feedback comments, a parent communication, a differentiated activity. Give them fifteen minutes to work with an AI assistant on it and note what was useful, what needed changing, and what they would do differently next time.

Brief sharing at the end: two or three people share what they tried and what they found. Keep this practical, not evaluative. The goal is to end the session with teachers who have used AI for something real, not just watched a demonstration.

Time: 20 minutes.

Closing and follow-up

Return to the opening questions and check which ones the session answered. Note any that are still open and identify who will follow up on them. Give participants a way to continue the conversation: a shared note-taking space, a follow-up session date, or a channel where questions can be posted.

End with one concrete next step each person can take: try one AI-assisted task before the next meeting, share what they learned, and bring one question or example back to the group. Small, specific actions sustain engagement better than big commitments.

How to do this with fenbs

Set up a fenbs project for the AI in education initiative and record the team's decisions and prompts as the work develops.

1. Create a free account and add a project for the AI in education initiative at your school or department.
2. After the session, record the allowed-use decisions and review steps the team agreed on as Decisions and rules.
3. Add the prompts that worked well in the demonstration to the Skills and prompts library so every teacher can reuse them.
4. Connect your AI tools from Integrations so sessions start with the current team decisions and prompts available.
5. Before each follow-up meeting, save progress notes on what teachers have tried and what questions have come up.

For a broader look at AI use cases in education, see AI use cases in education. The how to use AI at work guide covers general practices that apply to teaching work.