My Key Takeaways from the SISO 2026 CEO Summit

March 29, 2026

The SISO – Society of Independent Show Organisers CEO Summit delivered a clear message: the events industry is at a turning point. Traditional growth levers are weakening. AI, data quality, and retention are now the things that separate the leaders from the rest.

This wasn’t a conference about what’s coming. It was about what’s already happening. I attended as representative of ShowCycle – and as someone who has spent decades in event technology – so I wasn’t just listening. I was measuring every conversation against what we’re building, and what our customers are going to need.

AI Is No Longer Optional - It's Foundational

AI came up in almost every session – not as a future concept, but as something already running in real businesses. An AWS-led session showed how AI is changing live events through real-time analytics, personalized engagement, and smarter operations. Attendee expectations are rising fast.

The warning to executives was blunt: most organizations aren’t thinking big enough. AI isn’t just about automating tasks. It means rebuilding how you work – your workflows, your data, your decision-making. Start small, prove it, then scale.

I’ve watched this industry navigate technology shifts before. Social media is the one everyone remembers – a window opened, a few moved early, and everyone else spent years trying to catch up. Some never did. This feels like that moment, except faster. The organizations that treat AI as something to evaluate later aren’t just being cautious. They’re making a choice that will be very hard to undo.

From AI Experiments to AI in Production

Several sessions moved past theory into real results. In the AI in Action panel, one company deployed AI-powered sales reps that generated meaningful pipeline within months. Another automated most of its prospect list processing. These aren’t pilots – they’re production.

But success also exposed a real risk: ungoverned AI. Without clear standards, validated integrations, and honest communication with employees, AI creates privacy problems and inconsistent results. The message was consistent – AI scales fastest when it’s governed well.

I’ve seen this play out on the organizer side too. A new system goes in, the team doesn’t trust it, and within six months everyone’s working around it. Technology without buy-in doesn’t stick. What struck me in these sessions was how clearly the successful deployments had one thing in common – the people using the tools understood why. That’s not a technology problem. That’s a leadership problem. 

AI Elevates the Retention Imperative

Here’s the number that stopped the room: industry attendee retention runs at just 27-30% year over year. Even lower among younger cohorts. Speakers were direct – this isn’t a marketing problem. It’s a leadership and data problem.

AI can help fix it. When attendees leave with a real outcome – a connection made, something learned, a deal started – they come back. AI-driven personalization and behavioral analysis can make those moments happen by design, not by luck. And retention, not NPS, should be the metric that matters.

When that number came up, I wrote it down and underlined it. Twenty-seven percent. I’ve sat across from enough organizers to know that most of them sense this – they just haven’t been forced to stare at the data. There’s something clarifying about hearing it said out loud in a room full of CEOs. Retention isn’t a program you run. It’s the score on the board. 

Data Is the Fuel That Makes AI Work

One theme ran through every session – KPIs, sponsorship, M&A, AI – clean first-party data. AI can’t deliver without it. Event buyers want real-time behavioral data – dwell time, session attendance by persona – immediately after the event. Investors are scrutinizing data depth as a valuation input.

The organizations that treat data as a core asset, not a byproduct, are better positioned on every dimension – AI deployment, margin defense, long-term growth.

This one hit close to home. The conversations we have with prospects almost always reveal the same thing – data that lives in three systems, owned by nobody, trusted by no one. It’s not a technology gap. It’s years of decisions that made sense at the time. Hearing PE investors say they’re pricing that into valuations felt like a turning point. The industry has been able to treat data as a back-office problem. That’s over. For ShowCycle customers, this isn’t a problem to solve. Building natively on Salesforce means first-party data is already centralized, trusted, and AI-ready. 

AI's Broader Economic Context

The Economist session zoomed out. AI infrastructure is a major growth engine – but it’s also accelerating workforce displacement and widening inequality. Rising costs and softer consumer sentiment add near-term pressure.

In that environment, AI becomes a resilience tool. It helps you run leaner, get more from your existing audience, and make a clearer case for ROI.

This was the session I sat with longest afterward. The economic pressures aren’t abstract – they show up in registration numbers, in sponsor budgets, in the conversations we have every day. What I took from it is that efficiency isn’t just a nice outcome of AI. For a lot of businesses, it’s going to be the difference between weathering the next two years or not. 

Now What?

The Summit named the challenges clearly. The harder question is what you do Monday morning.

  • Audit before you automate. Map your data infrastructure before adding more AI tools. Fragmented data doesn’t get fixed by AI – it gets amplified. The first investment might not be a platform. It might be a cleanup project.
  • Make retention a primary KPI. If it’s not on the dashboard your leadership reviews every quarter, it won’t drive decisions. Set a target. Track it alongside revenue.
  • Build governance alongside pilots. Don’t wait for AI to scale before setting the rules. Define your standards and communication approach now, while mistakes are still small.
  • Design the peak moment. Ask one cross-functional question: what does a first-time attendee need to experience to make coming back feel obvious? AI can help engineer that moment – but someone has to define it first.
  • Use the macro headwinds as your internal argument. “We’ll figure out AI later” is harder to defend when cost pressure is real. The economic context isn’t background noise. It’s the business case.

One thing I keep coming back to as a supplier: we don’t get to react. Organizers move fast and change direction without warning. We have to be ahead of that curve – or at minimum, right alongside it. Salesforce and AI are what make that possible for us. As for everyone else in that room – the answers will look different for each of you. That’s the nature of this shift. Figure out where you stand first. Then look around.

The SISO CEO Summit made a compelling case for what good architecture looks like in 2026. We’re already standing on it. Salesforce isn’t just our technology choice. It’s our answer to every challenge this industry is about to face. That doesn’t make the work ahead easy. But when the whole industry is being asked to rearchitect around AI and data, starting on Salesforce isn’t just an advantage – it’s an unfair one.

The organizations that move deliberately – not reactively – will be the ones setting the standard in three years.

Are you built for this – or do you need to rebuild?