How To Have A Real Conversation About AI

AI is everywhere this year. You’ll find it at all the summits. Hear it in the keynotes. See it in the demos. Feel it in the energy of the conference floor.

And honestly, that’s something to celebrate. Because the potential is real—bigger, faster, smarter ways to build, innovate, and scale. The best events create space for bold ideas, live experimentation, and serious momentum.

But in a moment this big, it can also be hard to tell what’s signal and what’s noise. Which demos actually land? Which use cases have traction? Which ideas will still matter when you’re back at your desk next week?

That’s where this guide comes in.

We put together a smarter, sharper way to cut through the noise, stay curious, and spot the real breakthroughs. Whether you're walking around an expo floor, sitting in a keynote, or swapping notes with someone new, this is your unofficial field guide to finding what’s real. It’s part scavenger hunt, part insider cheat sheet—designed to help you ask better questions, spot the moments that matter, and walk away sharper than when you arrived.

Because when you know what to look for, you see more. (And trust us—the good stuff’s out there.)

A clear-eyed guide to AI at any conference

The next time you’re at a conference where they’re talking about AI, challenge yourself to:

Find a session that admits what didn’t work

Not everything is a flawless success story. Look for sessions where failure isn’t sanitized. When a speaker gets real about lessons learned, low adoption, or poor model accuracy, you’re hearing true insight—not marketing. Ask yourself: did this failure lead to better data validation? Stronger observability practices? Governance enforcement? That’s the kind of detail that doesn’t make it into glossy recaps, but it’s what will help your team avoid the same pitfalls.

Ask two vendors: “What does your AI product struggle with?”

The good ones will answer honestly. The rest will talk in circles. Listen for answers about training data gaps, false positives, or model drift. If they give you a clear-cut answer, stay for the demo. If they dodge, you just saved yourself some time. You’re evaluating maturity, not buying a miracle. The more honestly a vendor can speak to their trade-offs, the more likely they are to partner well with your data org.

Attend a hands-on session featuring an LLM

Notice when the room leans in, when questions get sharper, when people stop checking their phones. That's real engagement. Extra credit if you hear mention of retrieval-augmented generation (RAG), prompt injection defenses, or grounding techniques. The best sessions will connect the dots between model logic, business context, and data engineering. Leaving you  with a stronger sense of what it would take to operationalize something similar back home.

Get into a conversation about AI adoption—not just AI architecture

Try to understand what’s stopping teams from actually using the tools they’ve bought. Is it a data trust issue? Lack of internal champions? Poor UX? It’s easy to be impressed by technical diagrams and infrastructure charts. But real value doesn’t come from what’s built—it comes from what’s used.

Ask the uncomfortable question: What percent of the business is actually using the new AI tools? What’s the volume of usage? Are users actively engaging with the model outputs or does it sit unused? Adoption is a metric and if AI is only being used by the same small group of data scientists or stuck behind an Airflow DAG, that’s shelfware. 

Real value doesn’t come from what’s built—it comes from what’s used.

You need to know:

• Can business users access it through governed interfaces?
• Are models explainable enough for risk-averse teams to trust them?
• How are failed model predictions being caught, audited, or corrected in workflows?

If the adoption rate is low, push further. What’s in the way? Lack of training? Skepticism? Governance gaps? Real AI success is about sustained, trusted use across the organization.

Talk to someone who’s skeptical about AI

Find someone who’s cautious, critical, or just not convinced yet. In regulated industries like healthcare or finance, these critiques are often tied to explainability, traceability, or cost. But even in more flexible orgs, the concerns might point to usability or cultural resistance. Ask them questions like: what would need to change for you to trust this technology? Skeptics often see things that true believers miss—and understanding those gaps is key to building better AI for everyone. 

These conversations are invaluable. They show you the roadblocks that product decks rarely mention and help you pressure-test your own assumptions.

Write down one thing AI made harder for your team this year

Not every "innovation" solves more than it complicates. Name it. Then start looking for the solutions that don't just promise to fix it—but show you how. Good AI platforms help untangle that complexity. So when you evaluate solutions, ask: does this vendor acknowledge those tensions? Do they offer tooling, visibility, and workflows that make it easier to manage the messy middle?

Come see what real AI looks like

When you step onto the floor at your next conference, the energy around AI will be impossible to miss.

If you’re looking for a place where that energy turns into action—where ideas move from the whiteboard into real workflows—come find Sigma.

At the events we attend, leaders from companies like Workday, Yamaha, ICE/NYSE, Zelis, and Florida Cancer Specialists share how they’re using Sigma to make smarter decisions, scale faster, and unlock new possibilities across their organizations. You’ll see live demos and hands-on labs where AI models aren't just imagined—they're built, tested live, and used to drive faster, smarter decisions.

And if you want to get beyond the buzz and into the real conversations about what’s working, what’s hard, and what’s next, you’ll find that spirit here too.

We’re here to celebrate what’s possible, stay honest about what’s hard, and help build the future with both eyes open.

See you out there. Bring your questions. Bring your curiosity.

And let’s make it a conversation worth remembering.