Becoming an AI-First Organization

Each session, industry leaders will discuss the obstacles their organization has faced in the AI-era and highlight what's worked, what hasn't worked and what they plan to do next. Participants will have the opportunity to engage, ask questions, and leave with a better sense of how to build an AI-first organization.

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What you'll hear

This is a working session for leaders building AI-first organizations. We don't focus on hype or theory, but instead share hard-earned lessons about what has and has not worked. And while we'll spend time discussing process changes and organizational patterns, we'll also discuss how to prepare for when AI delivers unexpected new opportunities for your organization.

Built for Leaders

For all leaders who want to use AI as a force multiplier.

Evidence Over Opinion

Grounded in what people have done and experienced.

Practical

Real insights you can begin leveraging immediately.

Industry Breadth

Speakers from across industries provide unique perspective.

Frequently asked questions

What is an AI-first organization?

An AI-first organization is one that has redesigned how work gets done around the capabilities of AI. Instead of treating AI as a productivity tool, it becomes part of the operating model for how products are built, decisions are made, and teams create value. The goal is not simply to use AI, but to generate significantly more output, quality, and leverage because AI is embedded into the way the organization works.

AI-first versus AI-enabled, what's the difference?

An AI-enabled organization uses AI tools to improve existing workflows. An AI-first organization redefines those workflows because the tools exist. The difference is between adding AI to your current process and rebuilding the process around what AI makes possible. Most companies today are AI-enabled; the organizations creating outsized results are becoming AI-first.

How do you become an AI-first organization?

Becoming AI-first requires both capability and commitment. Teams need production-grade AI builders who can reliably ship AI systems, and leaders need to redesign processes, incentives, and workflows around those new capabilities. Organizations typically get there by upskilling existing talent, hiring experienced AI practitioners, or combining both approaches while continuously adapting how work gets done.