Posted on June 9, 2026
Sourced from this LinkedIn post from InEvent CEO Pedro Góes.
When most people talk about AI and events, they talk about it like it’s one or the other. They discuss the possibility that AI could either break or save the industry.
But what if the real story is very different from that? What if AI isn’t here to make or break event tech at all? What if it’s here to split it in two?
Not into winners and losers, but instead into two honest piles. One side is the part of events where AI genuinely makes it better, faster, sharper, and more useful than it ever was before. And on the other side are the parts of events that simply won’t work, no matter how much AI you throw at it. This is not because the tech isn’t good enough yet, but simply because some things were never really a software problem to begin with.
Pedro Góes, CEO of InEvent, mapped out exactly where that line falls in a recent LinkedIn post, category by category, tool by tool. And once you see the pattern, it’s hard to unsee.
By the end of this, you’ll have a simple way to sort your own event tech stack into the same two piles.
The Pattern: Why Some Event Tech Survives
Events have always been a people thing. From the community around them to the people running them to the people attending them, it’s always been a human-led activity, through and through.
AI is maybe good at copying or mimicking things that are mostly software. If it’s codes, interfaces, or logic, AI can definitely learn to mimic it fast, and it’s already doing that across event tech today.
But a very significant part of events cannot be replicated or mimicked by AI:
- Physical work: Physical work is the obvious one. Somebody has to be there to guide a guest to registration, fix a badge printer when it jams, or get a stage camera-ready in twenty minutes. No bot is showing up to do that in 2026.
- Trust and compliance: Trust and compliance are less obvious but just as real. When money, contracts, or regulated data are involved, nobody wants “probably right” from a machine that can’t be held accountable. They want a system and a person behind it that they can trust completely.
- Access to private data: And private data is its own category entirely. Everything from your guest list, dietary restrictions, and company information attendees only handed over because they trusted you with it. That’s not a dataset you can casually plug AI into.
If you put those three things together, you get a simple test. If a piece of event tech depends on a body in the room, a compliance requirement, or access to data people don’t hand out lightly, it’s safe. If it doesn’t depend on any of those three things, it’s exposed and entirely risky to have it there in the first place.
What Survives: Human Work AI Can’t Touch
Live production & AV: someone has to be there
Starting with the most obvious one. Lighting, sound, staging, and camera operators still need to be done by humans in 2026.
AI can help with the planning side of it, figuring out the logistics like suggesting a lighting plan or drafting a run-of-show. But someone still has to walk into the venue to rig the truss, mic the speaker, and fix it live when a cable fails three minutes before doors open. There’s no bot showing up with a toolkit. And until there is, this part of event tech isn’t going anywhere.
Badge printing, check-in & on-site logistics: more tech, not fewer humans
This is the one people get backwards. They assume more automation means fewer people on-site. The opposite is happening.
Facial recognition, NFC wearables, and self-service kiosks, all of it is genuinely getting smarter. But every layer of new hardware is also a new layer of things that can go wrong. What happens if a printer jams or a kiosk freezes? A facial recognition scan could fail to match because someone showed up in sunglasses and a different haircut than their badge photo. Someone still has to be standing there to fix it in real time.
More tech at check-in doesn’t remove the humans. It just changes what they’re doing.
This is exactly the kind of complexity that shows up at scale. When Santander ran their annual all-employee event for 42,000 people at Allianz Parque, the badge and access side of it was the whole operation. Unique, non-transferable digital tickets that couldn’t be screenshotted or shared. Real-time check-in for tens of thousands of people walking through the doors at once. That’s not a problem you hand to a chatbot. That’s a problem you hand to a team, backed by a system built to handle it.
What Survives: Anything Guarded by Compliance or Private Data
Lead retrieval: the data is the moat
If you walk onto almost any trade show floor today, lead retrieval will cost you around $1,000, because the technology is hard to build. This is so because the thing it’s protecting (access to enterprise-grade attendee data) has gotten more expensive, even with AI in the picture.
AI is genuinely useful here. It’s good at enrichment, good at scoring a lead, good at telling you who’s worth following up with first. What it can’t do is shortcut its way into the private databases that make lead retrieval valuable in the first place. The access itself is the product. And access like that doesn’t get cheaper just because AI got smarter.
That’s the gap InEvent’s lead retrieval tools are built around — not just capturing a lead, but doing it inside a system enterprise teams already trust with everything else.
Payments, ticketing, revenue: nobody’s letting AI near the wire transfer
This one barely needs an argument. Refunds, scheduled wires, ticket revenue, the moment real money moves, the bar changes completely. It stops being a “good enough” problem and becomes a “this has to be exactly right, every time, and provable” problem.
That’s compliance work, not software work. And it’s why this part of the stack tends to stay firmly in human and tightly audited hands.
It’s also why the back-end matters as much as the front-end experience. When XP Investments ran a 20,000-person tradeshow with more than 50 integrated solutions running through their event stack, the integrations weren’t the hard part. Trusting that every connected system met the same bar for security and compliance was. That’s the kind of trust SOC 2 Type II and PCI DSS certifications exist to back up — not as a badge on a website, but as the reason a financial services company can run an event like that without losing sleep over it.
What’s Disappearing: Anything a Weekend Project Can Replace
Event mobile apps
An agenda, a speaker list, a map. That used to be a real product. Now it’s a commodity, and a fast-disappearing one. Anyone can spin up an event app on a vibe coding platform in about ten minutes — no developer, no design team, just a prompt and a coffee break. When something used to take a team and now takes a weekend, it’s not really a product category anymore.
Virtual event platforms
Video stopped being special the moment the whole world got forced onto Zoom calls overnight. Now it’s Zoom, Teams, Google Meet — pick one; they all stream a webcam just fine. Many of these platforms also integrate with an AI meeting note taker, making it easier to capture discussions and action items without manual note-taking. Unless your event needs something genuinely custom, AI tools already do this job well enough. There’s not much left to defend here.
Gamification platforms
This is the one that should sting a little. Leaderboards, points, badges — built online in seconds now. Pedro mentioned something in his post that sums it up better than any market data could: in his peer CEO group, some of the kids — six and seven years old — are building games in hours. Not days. Hours. If a six-year-old can build it before bedtime, it’s probably not a durable software category anymore.
Would Registration Also Survive The AI Onslaught?
Registration doesn’t sort as cleanly as the rest.
The ticketing logic of any registration tool can be built by AI tools like lovable, base 44 and so on.
But everything from fraud detection, payment handling, and chaos sorting of having thousands of registrants attempt registration at the same time is still very much non-replicable.
So the honest answer depends on the size of the event in front of you.
- If it’s a small, simple event maybe a local meetup, a single-session webinar- it’ll be low stakes if something glitches, and your AI-assisted registration is probably fine. The risk is low, and the logic is genuinely something AI can carry on its own.
- If it’s a large-scale event, or anything with real fraud exposure like a big conference, a paid ticketing tier, an event where a registration error means a real financial or reputational problem, it still needs a platform built for that, not a weekend project. That’s the difference between registration software built to handle scale and a form that happens to work until it doesn’t.
So registration isn’t really a “survives or dies” category. It’s a “depends on what you’re actually running” category — and that’s worth knowing before you pick a tool, not after it breaks on you mid-event.
So What Does This Mean for Your 2026 Tech Stack?
Here’s the test: ask whether something is physical, regulated, or built on private data. If the answer is yes to any one of those, it’s safe for now.
That’s it. That’s the whole filter. Run any tool in your stack through it. AV and on-site logistics are physical. Payments and lead retrieval are regulated, or sit on data nobody hands out lightly. Mobile apps and gamification are usually none of the above, which is exactly why they’re the easiest to replace.
This isn’t really about AI replacing people. It’s about knowing where your budget should actually go. The tools that pass the test are where your people, your training, and your process still matter most. The tools that don’t pass it are where you should probably stop overspending on custom builds, because the commodity version is catching up fast and it’s free, or close to it.
Spend your tech budget where AI is genuinely better. Spend your people budget where it still can’t compete. That’s the whole strategy.
Final Thoughts
Pedro Góes ended his original post with a simple question: Do you agree, and what would you add? It’s worth asking yourself the same thing about your own stack.
Run your tools through the test, physical, regulated, or built on private data and you’ll probably find your own list of survivors and your own list of things you’ve been overpaying to keep around. If you want to see what a platform built around the “survives” side of that list actually looks like in practice, InEvent’s case studies are a good place to start.
Frequently Asked Questions
Will AI replace event planners?
No. AI can help with planning tasks like drafting schedules or suggesting layouts, but the physical, on-site, and trust-based parts of running an event still need a person. Event planning is a people job with software support, not the other way around.
What event technology is most at risk from AI?
Event mobile apps, virtual event platforms, and gamification tools are the most exposed. They’re mostly software with no physical, regulated, or data-sensitive components, which makes them easy for AI tools to replicate quickly and cheaply.
Is event registration software going away?
Not entirely. Simple ticketing logic can be handled by AI for small, low-stakes events. But registration for large-scale events still needs fraud detection, payment security, and the ability to handle high volume, which still requires a dedicated platform.
Why is lead retrieval considered safe from AI disruption?
Lead retrieval depends on access to private, enterprise-grade attendee data. AI can enrich and score leads, but it can’t replace the access itself, which is what makes lead retrieval valuable and expensive to begin with.
Why do compliance-heavy tools like payments and ticketing survive AI?
Because handling real money carries legal and financial accountability that AI can’t take on. Refunds, wires, and ticket revenue need to be provably correct every time, which keeps this work in human and audited hands.
About the Author / Adedoyin
