Teach · Executives
How to run an AI workshop for leadership
An AI workshop for leadership is a facilitated session where executives learn what current AI can and cannot do, try AI tools on company-relevant tasks, and agree on next decisions. A productive leadership workshop uses the company's own processes as examples and ends with named owners, a short priority list, and a date for follow-up.
- Reading time
- 8 min
- Chapters
- 6
- Last reviewed
- November 10, 2026
- Author
- Lingows AI Team
- Difficulty
- Beginner
Before you start
- An executive sponsor who will chair the session
- Approved AI tool accounts for every participant
- Two or three real processes the company could improve
The steps at a glance
- Step 01
Set the decisions
Write the decisions the workshop must produce and share the list with participants.
- Step 02
Interview executives
Learn each leader's starting point, concerns, and priorities.
- Step 03
Prepare company material
Choose real processes and safe sample documents, and set up approved tools.
- Step 04
Run the five blocks
Brief, demonstrate, practice hands-on, discuss risk, and choose priorities.
- Step 05
Record decisions and owners
Capture every decision with a named owner and date.
- Step 06
Follow up
Send the summary promptly and hold the agreed review meeting.
Chapter 01
What should a leadership AI workshop achieve?
A leadership AI workshop should achieve shared understanding and concrete decisions: a common view of what AI can do for the company, agreement on risk boundaries, a short list of candidate use cases, and named owners for next steps. A workshop that ends with enthusiasm but no decisions rarely changes how the company operates.
Executives arrive with very different starting points. One leader uses an AI assistant daily; another has read headlines and remains skeptical; a third worries mostly about risk. The workshop's first job is a shared vocabulary, so the room can discuss AI agents, assistants, and automation without talking past each other.
The second job is decisions. Write the intended decisions on the invitation: agree risk boundaries for AI use, choose up to three candidate use cases to assess, and name an owner for each. Stating the decisions in advance keeps the session from drifting into a general discussion.
Chapter 02
How do you prepare for a leadership AI workshop?
Preparing for a leadership AI workshop means interviewing a few executives beforehand, gathering two or three real processes from the business, setting up approved AI tools for every participant, and preparing exercises built on company material. Preparation turns a generic presentation into a working session about the company's own decisions.
Checklist
Workshop preparation checklist
Check that the sample documents are safe to use. A board pack or customer contract is a poor choice for a public tool. Use approved company accounts, or prepare sanitized versions of real documents.
Chapter 03
What agenda works for a leadership AI workshop?
A leadership AI workshop agenda works best in five blocks: a plain-language briefing on current AI capabilities, live demonstrations on company tasks, hands-on exercises for each executive, a discussion of risk and governance, and a closing session to choose priorities and owners. Each block should leave time for questions and debate.
Sample agenda
| Block | Purpose | Format |
|---|---|---|
| Briefing | Shared vocabulary for models, assistants, agents, and automation | Short talk with questions |
| Demonstrations | Show AI working on real company tasks | Live demonstration on company material |
| Hands-on | Every executive tries the tools personally | Guided exercises by function |
| Risk and governance | Agree boundaries for data, review, and accountability | Facilitated discussion |
| Priorities | Choose candidate use cases and owners | Scoring exercise and decisions |
Keep the briefing short and concrete. Explain what large language models do well, such as drafting, summarizing, classifying, and answering from documents, and where models struggle, such as precise arithmetic without tools, current facts without retrieval, and judgment the business has never written down. The answers on what an LLM is and agentic AI make good pre-reading.
Protect the hands-on and priorities blocks above everything else. Workshops tend to overrun in the briefing, because questions are welcome and executives enjoy the discussion. A facilitator who keeps the briefing tight leaves enough room for every leader to try the tools and for a real decision at the end. If time runs short, cut demonstrations before cutting practice or priorities.
Chapter 04
Why should executives use AI tools during the workshop?
Executives should use AI tools during the workshop because direct experience calibrates expectations faster than any presentation. Leaders who draft a memo, summarize a report, or analyze a document themselves see both the speed and the errors firsthand, which produces better judgment about where AI belongs in the company and where AI does not.
Write exercises by function. A finance leader summarizes variance commentary. A sales leader drafts an account plan from meeting notes. An operations leader asks an assistant to find the steps in a process document that cause delays. Each exercise uses material the leader recognizes.
Exercise: board update draft
Paste the three internal reports provided.
Ask the assistant for a one-page board update covering:
results against plan, top three risks, decisions needed.
Then check every number in the draft against the reports.
Note one thing the draft did well and one error or omission.Chapter 05
How should the workshop handle risk and governance?
The workshop should handle risk and governance as a practical discussion about boundaries: which data stays out of AI tools, which outputs need human review, who owns AI-assisted decisions, and how new tools get approved. The goal is agreement on principles that an AI acceptable use policy will later turn into written rules.
Bring three or four concrete scenarios to discuss. A sales rep pastes a customer contract into a personal chatbot account. A support agent sends an AI-drafted reply with a wrong refund amount. A manager uses AI to rank job applicants. Asking the room how the company should respond produces clearer principles than abstract debate.
Record the agreed principles and assign an owner to draft the policy. The guide on writing an AI acceptable use policy covers the next step.
Keep the discussion grounded in the company's actual exposure. A company that handles health records, payment data, or information about children faces different obligations than a company that sells to other businesses. Invite the person responsible for security or compliance to frame the boundaries, and capture any question that needs legal input as an open item with an owner rather than settling the question in the room.
Chapter 06
What should happen after the workshop?
After the workshop, the facilitator should send a short written summary within days listing decisions, owners, candidate use cases, and open questions. The named owners then start the next steps, often a readiness assessment or a first pilot, and leadership reviews progress at the follow-up date agreed during the session.
Momentum fades quickly after a good session. A summary that arrives promptly, with names next to every action, keeps the decisions alive. Put the follow-up meeting on calendars before people leave the room.
Typical next steps include an AI readiness assessment for the candidate departments, scoring candidates with the first use case guide, and drafting an AI roadmap. Lingows AI facilitates leadership workshops as part of AI training engagements.
Workshop summary template
| Section | Contents |
|---|---|
| Decisions | Each decision made, in one sentence |
| Owners | The person responsible for each next step, with a date |
| Candidate use cases | Up to three, with the reason each was chosen |
| Risk principles | The boundaries agreed for data, review, and accountability |
| Open questions | Items needing more information, with an owner |
01Summary
Key takeaways
What to remember
- Write the decisions the workshop must produce before the session.
- Use the company's own processes and documents as examples.
- Have every executive use the tools and check the output personally.
- Turn risk discussion into principles for a written AI use policy.
- End with named owners, a short priority list, and a follow-up date.
02FAQ
Questions about this guide
How long should a leadership AI workshop run?
A leadership AI workshop usually fits in a half day or a full day, depending on how many hands-on exercises and decisions the session includes. Shorter briefings build awareness but rarely produce decisions. The agenda should allow enough time for every executive to try the tools and for genuine debate about priorities.
Who should facilitate a leadership AI workshop?
A leadership AI workshop works best with a facilitator who understands both current AI capabilities and the company's business, plus a separate note-taker. An internal leader can facilitate when the company has the expertise. An outside facilitator helps when leaders disagree strongly or when nobody inside has hands-on AI experience.
Should the board attend the leadership AI workshop?
Board members can attend a dedicated session, but the leadership AI workshop usually works better with the executive team alone, because the session focuses on operational decisions and owners. A shorter board briefing afterward can share the agreed principles, priorities, and risk boundaries, and invite questions on governance and oversight.
What if executives disagree about AI?
Executive disagreement about AI is useful when the facilitator surfaces the reasons. Disagreement often comes from different experiences, different risk exposure, or different assumptions about cost. Concrete scenarios and hands-on exercises narrow the gap. Remaining disagreements become open questions with owners rather than blockers for the whole program.
Do executives need technical knowledge before the workshop?
Executives do not need technical knowledge before a leadership AI workshop. A short pre-reading on large language models, AI agents, and automation helps, but the briefing covers the essentials in plain language. Curiosity, a few real problems from each executive's area, and willingness to try the tools matter more.
Written by
Lingows AI Team
Engineering and strategy team, Lingows AI
The Lingows AI team has built AI systems since 2017 and software since 2012. Collective posts cover model landscape changes, tooling selection, and the direction of applied AI.
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