Editorial Team @ Vihaya Events
Most writing about AI and events is a list of things that might happen. This is the opposite: where AI genuinely saves an organiser time today, where it does not, and where using it is actively a bad idea. If you run college fests, conferences or community events in India, three of these will matter to you and the rest will not.
Where AI actually helps right now
1. Building the registration form
This is the clearest win, because it is a translation task rather than a judgement task. You describe the event in a sentence or two — "two-day inter-college design workshop, teams of three, need college name, year of study and t-shirt size" — and get a working set of fields back, correctly typed, instead of clicking "add field" fourteen times.
The reason it works is that the cost of a mistake is near zero: you can see every field it produced and delete the wrong ones in seconds. Compare that to anything that touches money, where a wrong answer is expensive and invisible.
2. Writing the event description and the reminder emails
Drafting is the other genuinely safe use. A first draft of an event page, a reminder email or a WhatsApp announcement takes an organiser twenty minutes and takes a model two seconds — and you are going to read and edit it anyway.
One caution specific to events: do not let a model invent details. It will happily write "doors open at 6pm" when you never said so, and that sentence will end up on a poster. Give it the facts and ask it to arrange them; do not ask it to fill gaps.
3. Making sense of your own registration data
Once you have a few hundred registrations, the useful questions are ordinary analysis questions — which colleges are actually showing up, which track is underselling, whether the discount code on the Instagram post did anything. This is a good fit because the data is small, structured and yours.
Where AI does not help (and the honest reasons)
| Task | Why it fails |
|---|---|
| Deciding capacity or price | Depends on your venue, your budget and your relationship with sponsors. A model has none of that context and will produce a confident average. |
| Anything touching payment | A wrong answer moves real money and is often invisible until reconciliation. This needs deterministic code and a test suite, not a prediction. |
| Predicting attendance | Your no-show rate depends on whether you charged, the weather, and what else is on that weekend. Historical averages from other events do not transfer. |
| Talking to attendees unsupervised | A chatbot that invents a refund policy has created a commitment you may have to honour. |
The rule of thumb
AI is worth using where you can check the output faster than you could produce it. A registration form, an email draft, a summary of your own data — you can eyeball all three in under a minute. A pricing decision or a payout calculation you cannot, which is exactly why those should be ordinary software.
That is also why the useful AI features on an events platform tend to be unglamorous. The impressive-sounding ones — autonomous agents that "run your event" — ask you to trust output you have no practical way to verify.
What this means for choosing a platform
Treat "AI-powered" in a feature list as meaningless on its own and ask two questions instead:
- What specifically does it generate, and can I see and edit the result? If the answer is no, it is not a time-saver, it is a black box.
- Does anything AI-generated touch the money path? It should not. Pricing, fees and payouts should be plain, testable rules you can reconcile by hand.
On Vihaya Events, the AI features are deliberately on the drafting side — form building and page content — while everything that decides what an attendee is charged is ordinary code covered by tests. You can read exactly what the fee is and how it is banded rather than being told a model optimised it.
Want to see the practical version rather than the pitch? Look at what is actually included on Vihaya Events — free for free events, with no paid add-on tiers.
Common questions
- Will AI replace event managers?
- No, and the reason is specific rather than reassuring: almost everything hard about running an event is negotiation, judgement and physical logistics. Venue availability, sponsor relationships, a supplier who has not shown up — none of that is a text problem.
- Is it safe to put attendee data into an AI tool?
- Be careful. Attendee names, emails and phone numbers are personal data, and pasting a registration export into a general-purpose chatbot sends it to a third party. If you want analysis, use a tool that operates on your data inside the platform you already trust with it.
- Should I use AI to write my event description?
- Yes, as a first draft. Then rewrite the first two sentences yourself — those are the ones that appear in search results and on share cards, and they are where generic AI phrasing is most obvious.