AI in events: useful vs. gimmick
Somewhere around mid-2024, every event tech platform became "AI-powered." New landing pages went up. Press releases were issued. The word "intelligent" appeared in front of features that hadn't changed. And most of it was, to be blunt, superficial.
That doesn't mean AI is useless for events. It means the industry is bad at distinguishing between AI that does something genuinely new and AI that's a marketing label on the same old thing. Here's our honest take on which is which.
Where AI actually helps
There are specific tasks where AI is a real step forward for event teams. Not because it's magic, but because it's good at things humans find tedious, slow, or error-prone.
Querying live event data in plain language. Instead of running three reports and cross-referencing a spreadsheet, you ask "what's our exhibitor compliance rate?" and get an actual number. This only works if the AI has access to your real event data — not a cached export from last Tuesday. When it does, it replaces a 15-minute task with a 10-second one.
Drafting communications with event-specific context. Writing 40 exhibitor reminder emails isn't hard. It's just slow. AI that knows which exhibitors are behind on submissions, what they're missing, and when their deadline is can draft those emails with the right context already filled in. That's not autocomplete — it's a genuinely useful workflow.
Intelligent matching based on real profile data. Attendee networking and session recommendations that actually work require more than keyword overlap. AI that can read attendee profiles, past session ratings, and stated interests — then surface relevant connections — is doing something a filter can't. The key word is "real profile data." Without it, you're just matching job titles.
Analysing documents and floor plans. Upload a 200-booth floor plan and have AI cross-reference it against your exhibitor assignments, flagging mismatches and missing allocations. Try doing that manually at 4pm the week before your event. This is where AI shines: structured analysis of visual and document data that would take a human hours.
Summarising meeting notes and surfacing action items. Event planning involves dozens of calls with production teams, venues, sponsors, and internal stakeholders. AI that can pull out the action items, deadlines, and decisions from a meeting transcript saves real time — and catches the things that would otherwise fall through the cracks.
Where AI is a gimmick
Now the uncomfortable part. A lot of what's being sold as AI in event tech doesn't pass a basic test: could you do this with a search bar and some filters?
"AI-powered" event websites. These are templates. Some have a chatbot bolted on. The AI didn't design your event site — a template engine did, same as before. The chatbot can answer questions that a well-organised FAQ page already covers.
Generic content generation. A language model that doesn't know anything about your specific event, your audience, or your brand voice is just producing filler. "Generate a welcome email for your attendees" sounds helpful until you read the output and it could be for literally any event on earth.
"AI matchmaking" that's really keyword matching. If the matching algorithm is comparing job titles and industry tags, that's not AI. That's a database query with a nicer label. Real matching requires understanding context, preferences, and behaviour — not string comparison.
Chatbots that answer FAQ questions. If your AI can only tell an attendee what time registration opens and where to find the venue map, a search bar does the same job. The bar for "AI-powered" should be higher than "can read a help document."
"AI analytics" that's pre-built reports. If clicking "AI insights" gives you the same charts your dashboard already shows, just with a natural language question at the top, that's a UI change. Not intelligence.
The test worth applying
Here's a simple filter: can this AI do something that wasn't possible before, or is it doing the same thing with a new label?
AI that can query your live event data, cross-reference multiple data sources, and take action based on what it finds — that's new. AI that summarises a help page you could have just read — that's not.
The difference comes down to context. A language model that can't access your event data, your exhibitor records, your budget, or your schedule is just autocomplete with better grammar. It doesn't know your event. It's guessing.
Be honest about what AI is good at
AI is genuinely good at specific things: retrieving data from structured systems, finding patterns across large datasets, generating text with the right context, and analysing documents. These are real capabilities that save event teams real time.
AI is not good at judgement calls. It won't tell you whether to accept a controversial speaker. It can't read the room when a sponsor is unhappy. It doesn't have creative instincts about programme design. And it handles edge cases poorly — the weird, one-off situations that every event produces.
The honest position isn't "AI will transform events" or "AI is all hype." It's somewhere more specific: AI is a tool that's very good at certain tasks, and the event industry would benefit from being more precise about which ones.
The platforms that get this right — that connect AI to real event data and use it for tasks where it genuinely outperforms manual work — will be the ones that matter. The ones that slap an AI label on a chatbot and call it innovation will fade into the background noise.
That's the difference between building with AI and marketing with it.