AI for event planners is mostly about the paper trail. Every event runs on enquiry replies, quotes, timelines, supplier briefs and follow-ups, and most of that is the same shape every time with different names and dates.
That is the part worth handing over. Negotiating with a venue, reading a nervous client, and deciding what to do when the florist is stuck in traffic stays with you.
What AI should and should not do in event planning
- AI drafts a reply to an enquiry from your template. You decide whether the enquiry is a fit, and you send it.
- AI turns your notes into a first-pass run sheet. You confirm every time with the people who own it.
- AI builds a supplier comparison table with sources. You make the call and negotiate.
- AI turns a client questionnaire into a one-page brief. You notice what the client did not say.
- AI never decides on supplier contracts, deposits or client money. Those stay human, start to finish.
Workflow 1: enquiry replies in your voice
Enquiries arrive in bursts, often late at night, and the best reply is quick and specific.
Collect five or six of your real past replies, with names removed. Tell Claude or ChatGPT to match that voice and to ask you for any missing detail rather than guess it. Paste in the new enquiry and get a draft that mentions the date, the guest count and the venue the couple named.
You check it, fix the personal touches and send it yourself. Keep one rule: the draft never promises availability or a price. That comes from your calendar and your quote.
Workflow 2: proposals and quotes that start from your scope
A blank proposal is slow. A proposal built from your own inclusions list is not.
Give the model your standard service tiers, what each includes and your usual exclusions. Add the discovery call notes. Ask for a proposal draft that uses only those inclusions and marks anything uncertain as "to confirm".
Then you set the numbers. The model can lay out the document, but prices, payment schedules, deposits and cancellation terms are your decisions, and a template from your accountant or solicitor should govern the wording. If your platform already has a proposal tool, use the AI to draft the cover note and keep the figures in the platform.
Workflow 3: run sheets and day-of timelines
This is where AI earns its keep, because a run sheet is a lot of small times that all depend on each other.
Give it the ceremony time, the venue's bump-in and bump-out windows, travel times, supplier arrival times and any fixed items like speeches. Ask it to work backwards and list every conflict it finds, such as a caterer arriving before the venue opens its doors.
Then do the human part:
- Confirm each time with the supplier in writing.
- Walk the layout yourself or from the venue's floor plan.
- Add the contingency items the model cannot know, like the weather call.
Ask for two outputs from the same data: the full planner's version and a one-page version for each supplier showing only their own times and contacts.
Workflow 4: supplier research and briefs
I tested exactly this. My job for a ChatGPT agent was to find three workshop venues in Perth, make a table with sources, and draft an enquiry for me to review. The rule was no contacting venues and no booking anything. You can read how that went in my comparison of ChatGPT Dots and Grok Bot.
That is the right shape for event research. Ask for a shortlist of venues or suppliers, each with a link, the date the page was checked and the criteria you set, such as capacity, accessibility and catering rules. Open the sources and confirm the details by phone. Then have AI draft the enquiry email, and send it yourself.
An agent that can click around the web can also message people, so set the limits in the instruction. If you are new to the idea, what an AI agent is covers what is safe to hand over first.
Workflow 5: questionnaires, budgets and the follow-up
Three smaller jobs sit around every event:
- Client questionnaire. Ask AI to draft questions for your event type, then to summarise the answers into a brief. Check it against what the client said on the call.
- Budget tracker. AI can set up the columns and categories in a spreadsheet. You enter the real quotes and payments, and a person reconciles it.
- Post-event follow-up. Have it draft a thank-you, a review request and a short note for each supplier, using details you give it from the day. Send the review request while the memory is fresh.
The small stack worth learning
- Claude or ChatGPT: drafting, tables and run sheet conflict checks
- Your client platform: HoneyBook states on its homepage that AI is included in its plans, with email drafts, project recaps and a meeting notetaker (checked 23/10/2026).
- A spreadsheet: the budget and the supplier comparison
- Zapier, Make or n8n: later, to move enquiry details into your tracker
Check a vendor's own page before you rely on a feature, because plans and features change.
Keeping it personal
Clients hire you for care. Use AI for the structure and keep the warmth in your own words, especially in anything that touches a wedding. Keep client names, family circumstances, dietary and medical details out of any tool that is not approved for client data, and read your tool's settings first. The post on whether ChatGPT trains on your chats shows what to check.
Your first build: one run sheet
Take a finished past event. Paste in the confirmed times and suppliers with names removed. Ask for a run sheet and a list of conflicts. Compare it with what actually happened and note what it missed. Then try the same on your next event, before it is confirmed.
Once that works, wire the handoffs together with the ideas in four business automations you can build this week. If you want a room of women building these systems alongside you, see the Wright Mode membership.