Smart Event Studio

AI is....upending everything. Every new demo I get and it feels like every conversation I have is about how to use AI in our work.

Organizations invest in workshops, bring in consultants, and declare strategic direction. I've even been GIVING that training, but we are stuck.

A few months pass and it's back to business as usual.

The problem isn't the training. It's that we're asking overwhelmed people to stop working to learn something that might help them later—and "later" isn't compelling enough when you're drowning in today's work.

Immediate Benefit Is Required

Unless generative AI makes life better right now, teams don't prioritize it—no matter how strategic the buy-in is from leadership. People need to see a direct, personal payoff. We know this from lived-experience—long-term gains aren't sufficient motivation when you're already stretched thin.

True enablement requires protected space to learn and experiment. And that's incompatible with how most of us work today.

The Billing Model Problem Nobody Wants to Admit

Here's where it gets...awkward: an hourly billing model and increased efficiency can be at odds unless handled with care.

Most agencies bill hourly. If you automate a task that took 40 hours down to 20 minutes, you've just lost thousands in revenue. The math is brutal.

How do I know? Because that 40-hour to 20-minute example is what I recently did to myself when I automated a painful repetitive task. Now, I'd do it again in a heartbeat, but it's also not a choice everyone wants to make.

How do you justify charging the same amount for work that now takes a fraction of the time?

I don't have a good answer. But, it's a structural problem baked into how many agencies price their services and I foresee a reckoning coming soon.

What Actually Works: Three Paths Forward

1. Dedicated, Non-Negotiable Time Blocks

Allocate, for example, 4 hours per week (or a half-day) specifically for AI learning and implementation with real projects and real expectations.

It requires some resource re-allocation to free up those hours, but it's the only realistic way to create space for real integration.

2. Bring in External Specialists

Not everyone needs to become an AI expert. Hire consultants whose specialty is building custom agents—RFP bots, URL verification tools, whatever solves your specific pain point. Use platforms like Replit and custom GPTs to build solutions without requiring deep technical expertise from your team.

3. Shift Your Business Model

For agencies especially: value-based billing instead of hourly billing. Charge for outcomes, not time spent. This aligns your financial incentives with efficiency and better client results. Yes, it's a bigger conversation. But it's the conversation we need to have.

The Broader Reality

This goes way beyond events to any organization reliant on billable hours. Sustainable AI adoption requires industry-wide transitions to value-based pricing and structured enablement time.

But the reality is that without redesigning how we bill and allocating protected time for integration, enablement remains impossible. We can't ask people to learn their way to efficiency while keeping them fully booked.

The good news? These solutions are available now. The question is whether we're willing to invest in them.

What's your biggest barrier to AI adoption in your organization?