Hey

Did you feel the shift in the event tech conversation recently?

For two years, we’ve been in a "honeymoon phase" with AI. It was exciting, experimental, and—let’s be honest—a little chaotic.

But this week at PCMA Convening Leaders, the conversation grew.

And here’s what we discovered…

The excitement about "what AI could do" has been replaced by

a very practical, almost impatient demand for

"what AI should be doing right now."

We heard the same sentiment in every session: Generic AI is hitting a wall.

It’s fantastic for brainstorming. But when you are in the trenches—staring at a deadline for a 3-day conference agenda, or turning 40 hours of video into a content strategy—a blank chat box isn’t a tool. It’s a burden.

It forces you to become a "prompt engineer" just to get a basic result.

The Realization: Context is Everything

Think of it this way:

• If you’re a Planner, you need logistics, risk assessments, and speaker management. You shouldn't have to wade through marketing prompts.
  

• If you’re a Marketer, you need content repurposing, campaign strategy, and sentiment analysis.
  

• If you’re a Supplier, you need dedicated flows for RFP responses and prospecting.

Giving everyone the exact same interface is like giving a carpenter and a chef the same toolbox. 

It doesn't make sense.

Your work is specialized. Your AI should be too.

This thinking directly shaped Spark 2.0, where we built role-specific Pathways instead of a generic AI interface.

At the Spark Hackathon, we watched real event teams take messy, complex challenges and solve them in real-time.

We saw teams build comprehensive event strategies, complete with risk mitigation plans and multi-channel content calendars, in minutes rather than days.

They didn't do it because they were tech wizards. They did it because they finally had tools that understood the context of their work.

The Takeaway

The future isn't about writing better prompts. It's about having technology that respects the complexity of your job and gets out of your way.

If you are ready to stop experimenting and start actually working with AI, take a look at what a purpose-built workspace feels like.

Have a suggestion? Hit reply and fill us in.

See you next week,

Team Gevme

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