Recent marketing conversations around AI agents have leaned heavily on theory and hype. At Agentic World, however, industry leaders moved past the hype to explore what happens when those ideas move into practice.
Hosted by Treasure AI from Oct. 5–7 at the JW Marriott Turnberry Resort & Spa in Miami, the event brought that shift into focus, examining how governed agents and customer data can help teams act faster and create more relevant experiences.
A closer look at the agentic experience
Agentic World put the focus on what comes after the AI hype: seeing the technology in action.
The event brought together more than 800 decision-makers, including executives, directors, and hands-on architects, with representation from more than 40 Fortune 500 brands. OpenAI, AWS, Snowflake, and ADWEEK were among the event’s major sponsors.
Rather than treating agentic AI as an abstract concept, the event focused on what it looks like in practice. Mainstage sessions and breakouts explored customer stories, the commercial value of customer data, human involvement in AI workflows, and applications for AI agents, while an Innovation Showcase and hands-on workshops gave attendees opportunities to engage more directly. Demonstrations featuring real prompts and outputs reinforced the event’s focus on execution.
Daymond John, founder and CEO of FUBU and a Shark Tank host, headlined the event. His session covered what it means to build a brand as culture in an era of AI agents, and why speed matters to the companies shaping that era.
Beyond the mainstage, Agentic World was highly experiential, designed to give attendees firsthand opportunities to explore the technology and compare notes with peers. Hands-on workshops gave attendees a chance to dig into practical applications of AI and customer data, while the Treasure House offered self-guided product experiences, space to relax, and opportunities for more personal conversations.
Away from the formal sessions, the event emphasized connection as well as education. Roundtables, executive meetings, receptions, and dinners gave attendees opportunities to compare challenges with peers and connect with experts, while the Agentic World Awards recognized practitioners and brands at the forefront of customer experience and AI.
Treasure AI’s chief product and growth officer, Rafa Flores, noted some memorable takeaways for attendees. First, that the conference was all about humans. And secondly, Treasure AI’s new pricing.
“We unveiled something unique, which is that now you will pay not by the emails you send, but by click rate,” Flores shared. “I want attendees to go back to their teams and say, ‘Hey, this company is actually charging me for true outcomes.’”
Taken together, the programming was designed to move attendees from hearing about agentic AI to seeing how it can work in practice.
3 ideas for putting agentic AI to work
Agentic AI is moving beyond experimentation, but putting it to work effectively requires more than adopting new technology. The following three ideas can help leaders think about where agentic AI fits into their organizations and how to turn its potential into practical results.
Agentic AI is moving from hype to execution: AI agents can use customer data to act on signals in real time, helping teams execute campaigns faster and respond to customer needs more effectively. But making that possible requires more than the technology itself. Organizations need to connect the right data, design workflows around how agents will operate, and determine where human oversight belongs. The goal is not simply to automate more work, but to use agents in ways that produce better, more relevant customer experiences.
The best AI makes work feel more human: AI can take on repetitive, executional work that slows teams down, giving people more room for judgment, creativity, and connection. That doesn’t mean handing every decision to an agent. People still need to determine what matters to customers, whether an experience feels right, and when to change course. When AI handles more of the mundane work, teams can spend more time on the decisions and creative thinking that shape meaningful customer experiences.
Agentic transformation offers a place to start: Leaders don’t need a complete picture of AI’s future to identify a useful next step. They can start by looking at where work is creating friction, then consider whether an agent could help remove it. That means examining potential use cases, understanding the data and oversight they would require, and defining what success should look like. From there, organizations can choose a focused problem to solve, identify the people and systems needed to support it, and test an approach before expanding it.
The opportunity with agentic AI isn’t simply to do more with new technology. It’s to rethink how work gets done, giving organizations a practical path toward faster execution, more relevant customer experiences, and more time for people to do the work that requires them most.