--- "title": "What should a hands-on AI workshop for executives cover?" "description": "What a useful hands-on AI workshop for executives and senior leaders should cover, how to run it, the formats that work for busy leaders, and how to tell a good session from a vendor demo." "section": "AI Training" "sidebarTitle": "AI workshop for executives" "published": "2026-10-27T13:11:59.251Z" "updated": "2026-10-27T13:11:59.251Z" --- ## What should a hands-on AI workshop for executives cover? It depends on what you need leaders to do afterward. If the goal is for executives to use AI themselves, the workshop should be mostly hands-on, built on their own real tasks like board prep, client emails and reviewing reports. If the goal is to make decisions about AI for the company, add time on risks, data rules, costs and where AI fits in the business. Most leadership teams need both, in that order: personal use first, because leaders who use AI make better decisions about it. ## Who this is for CEOs, managing partners, COOs and heads of people planning AI training for a senior team, and executives who want to know what a good session looks like before booking one. ## The short version - Executives learn AI fastest by using it on their own work, not by watching slides. - A good workshop covers personal use, judgment about outputs, risks and data rules, and company decisions. - Keep it short, private and practical. Senior people rarely want to practice in front of a large group. - The test of success is what leaders do in the following weeks, not how the session felt. ## Why executives need their own workshop Leaders set the tone. When senior people use AI openly, others follow. When they do not, staff read that as a sign AI is optional or risky. See [how to get partners to use AI](/docs/get-partners-to-use-ai). Executives also have different work from the rest of the team. They read more than they write, make decisions under time pressure and handle the most sensitive information. A general training built for analysts or coordinators will not match their day. ## What the workshop should cover **1. Their own real tasks.** Before the session, ask each leader for two or three tasks from the past month. Typical examples: preparing for a board or client meeting, summarizing a long report, drafting a hard email, comparing proposals or reviewing a contract summary. Most of the session should be spent doing these tasks with AI. **2. How to give AI good context.** The biggest jump in quality comes from explaining the situation, the audience and the desired output, and from attaching the right documents. Leaders should leave with a few reusable prompts. See [how to create prompting standards](/docs/create-prompting-standards). **3. Judging outputs.** Executives need to know where AI tends to be wrong: invented facts, confident errors, outdated information and missing context. Practice checking a summary against its source and asking AI to show where each claim came from. **4. Risks and data rules.** What can go into which tool, why personal accounts are a problem and what client or board material needs extra care. If you do not have a written policy yet, this is a good moment to agree its main points. See [how to write an AI acceptable use policy](/docs/write-an-ai-acceptable-use-policy). **5. What AI means for the company.** Once leaders have used AI themselves, spend time on bigger questions: which workflows matter most, what to measure, how to talk to staff about jobs and who owns AI going forward. See [where to start with AI](/docs/where-to-start-with-ai) and [what to do if employees are afraid AI will replace them](/docs/employees-afraid-ai-will-replace-them). ## Formats that work for busy leaders - **A half-day hands-on session** for the leadership team, followed by one or two short follow-ups. This suits most teams. - **One-to-one sessions** for leaders who are less comfortable learning in a group, or whose work is especially sensitive. - **A short session before a leadership offsite,** so the strategic discussion is grounded in real experience. Whatever the format, keep the group small, use the tools your company has actually approved and make sure everyone has access before the session starts. See [one-off AI workshop vs ongoing coaching](/docs/ai-workshop-vs-ongoing-coaching) for how follow-up fits in. ## A simple agenda 1. Short framing: what AI is good and bad at today, in plain terms. 2. Hands-on round one: each leader works through one of their own tasks with a facilitator nearby. 3. Share what worked and what did not. 4. Hands-on round two: a harder task, with practice checking the output. 5. Risks and data rules: what is allowed and what needs care. 6. Company discussion: top workflows, ownership and next steps. 7. Each leader commits to one task they will use AI for every week. ## How to tell a good workshop from a vendor demo - **Who is typing.** In a good workshop, leaders type. In a demo, the presenter does. - **Whose examples.** Good sessions use your work. Demos use polished generic examples. - **Which tools.** Good sessions use the tools you already have. Demos often push a product. - **What happens after.** A good workshop ends with specific commitments and a follow-up plan. ## How to measure whether it worked Check a few weeks later. Are leaders still using AI on the tasks they chose? Have they shared prompts or examples with their teams? Has the leadership team made the decisions it discussed, such as approving a policy or naming an owner? Our guide on [how to measure whether AI training worked](/docs/measure-ai-training-results) covers more measures. ## Common mistakes - **Mixing executives into a large general session.** Many will stay quiet and learn little. - **Spending the time on strategy slides.** Without hands-on use, the strategy talk stays abstract. - **Using tools the company has not approved.** Leaders learn habits they cannot use the next day. - **No follow-up.** Without a check-in, most new habits fade. ## When you do not need us If someone inside your company already uses AI well, understands your data rules and can facilitate senior people comfortably, you can run this workshop yourself using the agenda above. Outside help is more useful when leaders want a neutral facilitator or when you want the workshop tied to a wider AI plan. ## How Ruby helps - **AI training:** hands-on workshops for leadership teams, built around each leader's real tasks, plus one-to-one sessions. - **AI strategy:** turning the leadership discussion into a policy, an owner and a short list of workflows. - **AI engineering:** building assistants and agents once leaders know where AI should help most. If you are planning AI training for your leadership team, [book a call with Ruby](https://rubyadvisory.com/book-a-call). ## Related pages - [How do I get partners at my firm to actually use AI?](/docs/get-partners-to-use-ai) - [One-off AI workshop vs ongoing coaching](/docs/ai-workshop-vs-ongoing-coaching) - [How long does it take to train a team on AI?](/docs/how-long-to-train-a-team-on-ai) - [How do I measure whether AI training worked?](/docs/measure-ai-training-results)