AI vs Excel Sheets: A Battle That AI Can't Possibly Win

If you've been reading any event technology publication lately, you've probably noticed the AI revolution narrative. And yes, the promise is genuinely exciting: AI can transform raw event data into actionable insights, enable predictive analytics, perfect attendee matching, and facilitate product-buyer connections that would have been impossible just a few years ago. But here's the thing: none of this works if our data lives in twelve different Excel sheets and seven disconnected systems.

The beauty of Artificial Intelligence in the event industry isn't about having a glorified chatbot at our registration web page. It's about being able to do something meaningful with the mountains of data we're already collecting. Analysis that reveals hidden patterns. Predictions that actually predict. Connections that create real business value. All those capabilities that were hardly (or not at all!) possible without AI.

But there's a fundamental problem we need to address, and it's not about the AI technology itself.

The Seven-App Symphony of Chaos

Let me paint you a picture that might feel uncomfortably familiar. Consider the typical attendee journey at any modern B2B event. They start by registering through our ticketing system - that's app number one. Then they browse the agenda on our event website, perhaps building their personal schedule - app number two. Upon arrival, we're using a badge printing and check-in system - app number three. During the event, they're navigating with the mobile event app - number four. Meanwhile, sponsors are scanning badges with their lead retrieval tools - app five. Marketing campaign engagement tracking? Different system - app six. Session feedback and post-event surveys? If we're lucky, they're in one app - number seven.

When vendor A offers the "best" registration system and vendor B has the "perfect" mobile app, it seems logical to use both. After all, we're getting best-of-breed solutions which enable us to offer the best possible experience to our attendees, right?

Except that we aren't. At a major event technology fair in London last year, I found myself juggling six different platforms just to manage my presence. As a speaker, I had one portal for my session materials. As an exhibitor, we had two completely different tools for our booth logistics. And when I wanted to walk the floor as an attendee, visit other booths, and network with people? Yet another app. Three roles, six systems, six usernames and passwords to remember, one increasingly frustrated me. The irony of needing this many disconnected tools at an event celebrating innovation in event technology wasn't lost on anyone paying attention.

Now, imagine being the organizer of that event, trying to answer seemingly simple questions: Which sessions did each attendee actually attend? Which exhibition booths generated the most qualified leads? What was the correlation between marketing campaign engagement and actual attendance patterns? Which networking connections turned into business opportunities?

We have all this data. Every single piece of it. It's sitting right there in our systems. Yet we might as well be sitting in the dark, because creating the comprehensive dataset that AI needs would require a proper integration project, the kind that takes weeks or even months to implement, costs more than our entire event budget, and requires consultants who charge by the hour just to explain what needs to be done. We could hire developers and build APIs, but let's be realistic: most event organizers have neither the time, budget, nor technical expertise for such undertakings. They're trying to run events, not become a software company.

So what happens in reality? Nobody does it.

The Excel Archipelago Effect

Here's where it gets even more interesting. On top of those seven systems, there's the undisputed king of IT in event management: Microsoft Excel. We create dozens of Excel sheets that mysteriously multiply as the event approaches. The sponsor tracking sheet that lives on Sarah's desktop. The speaker logistics spreadsheet that marketing maintains. The dietary requirements file that catering insists on managing separately. The budget tracker that finance won't let anyone else touch.

Each of these sheets contains critical data. Some even have clever cross-references that took someone hours to set up, and I'm certain they felt productive doing it. There's something deeply satisfying about that Excel sheet we've been refining for five years. We know exactly where everything is, we've memorized the formulas, and manually connecting data points gives us those "aha!" moments after staring at rows and columns for hours. It feels like control.

But let's be honest: we're just burning hours sticking to familiar tools, convincing ourselves we're doing 'data analysis' when we're only extracting maybe 10% of our data's value.

We're confusing activity with productivity, mistaking the feeling of control for actually being in control.

What is holding us back?

This data fragmentation doesn't just undermine AI capabilities, it makes implementing meaningful AI practically impossible. We're essentially asking AI to be brilliant while blindfolded, with its hands tied, standing in separate rooms simultaneously.

Faced with this impossible situation, organizers do what seems like the path of least resistance: they slap an AI chatbot on their registration page and call it a day. "Look, we're doing AI too!" they announce proudly, while the overpriced chatbot answers basic FAQs that a well-designed website could handle just as easily. The real AI capabilities (the predictive analytics, the intelligent matchmaking, the pattern recognition that could improve the event experience) remain forever out of reach. Not because the AI isn't sophisticated enough, but because it's being asked to perform magic tricks without being shown the cards.

The approach with seven different systems and only God knows how many Excel spreadsheets is what's preventing us from leveraging the power of Artificial Intelligence. It's like having a Formula 1 engine but insisting on installing it in seven different cars simultaneously and expecting it to perform just as good.

The Integration Illusion

"But we can integrate our systems!" I hear this response frequently, usually followed by descriptions of Zapier workflows, CSV exports, and API connections that supposedly solve everything. Yes, we can connect systems. We can build bridges between our data islands. But at what cost, and with which efficiency?

Every integration is a potential failure point. Every data transfer is an opportunity for information to get lost, corrupted, or delayed. In any case, it will get duplicated, and we will at some point of time inevitably ask ourselves what our primary source was. More fundamentally, these band-aid solutions don't address the core issue: not only that our data architecture wasn't designed for the AI age, it wasn't designed at all.

Modern AI thrives on comprehensive, real-time, high-quality data. It needs to understand relationships between attendees, sessions, speakers, sponsors, exhibitors, products, and marketing campaigns. Not as separate entities in different databases, but as interconnected elements of a single ecosystem.

The Path Forward: Unified Data, Unified Possibilities

The solution isn't about choosing better AI, it's about fixing the foundation. Event organizers need to fundamentally reconsider their approach to data management. Instead of treating each event function as a separate kingdom with its own systems and spreadsheets, we need to think holistically.

This means moving toward modern event management platforms, such as run.events, that handle multiple functions within a single data architecture. When registration, agenda management, networking, lead retrieval, and feedback collection happen within the same ecosystem, AI suddenly has the complete picture it needs to deliver genuine value.

Imagine being able to ask your system: "Which first-time attendees from the pharmaceutical industry attended at least three technical sessions and visited sponsor booths related to their session interests?" And getting an answer in seconds, not days.

Or better yet, having AI proactively identify these patterns and suggest targeted networking opportunities in real-time. This isn't futuristic fantasy, it's entirely possible with current technology. The only barrier is our addiction to fragmented systems and Excel sheets.

Making the Leap

The decision to consolidate event data systems isn't just technical, it's philosophical. It requires acknowledging that true control comes from comprehensive data intelligence, not from beloved spreadsheets. Yes, change is uncomfortable. Yes, there's a learning curve. But the alternative is remaining locked out of all the benefits that AI could bring us, not because the technology isn't available, but because we've made it impossible to implement.

Those who choose the path of consolidation and modernization are ten steps ahead today, and that gap will only widen with time.

The Bottom Line

AI versus Excel isn't really a battle, it's a mismatch. The question isn't whether AI will transform event management, but whether our data architecture will allow us to be part of that transformation.

In a world where attendees expect personalization, sponsors demand ROI metrics, and competition is global, the comfortable chaos of disconnected systems and Excel spreadsheets might be the most expensive comfort we've ever chosen.