Fernando Gadotti, Tako's founder, opens the day by explaining the scale that will organize the next ten hours and the deal every speaker accepted to step on this stage: talk about what they have actually done, mistakes and numbers included. Fifteen minutes to understand how to make the most of the day, and thirty seconds to decide which of the two stages you will be at by 10:15.

Endeavor closely tracks Brazil's most relevant scale-ups and now measures, in a structured way, what they are actually doing with AI on the inside, not what they announce. Tetê Fornea, Managing Director of Endeavor Brasil, presents the data from that research and then opens the conversation: where companies started, who pulled adoption forward, where it stalled, and what is working. You leave with the scale you will use across every other session of the day, and an honest answer to the question that brought you here: where exactly is my company on this journey.

Everyone has an AI strategy on paper. Few people describe what happens the day it meets the routine: goals that collide, roles that did not exist, processes nobody had mapped, managers who agree in the meeting and change nothing afterwards. Veronica Jany has spent her career leading large transformation programs in complex operations and speaks here in a personal capacity, free to tell what she saw, got wrong, and fixed. You leave with a vital-signs checklist to know whether your company's program is alive or already a zombie nobody switched off.

An MIT study estimates that 95% of generative AI pilots produce no measurable financial impact. Elisa Pereira, researcher at the Stanford Digital Economy Lab, went to study the others. She is co-author, with Erik Brynjolfsson, of the Enterprise AI Playbook: 51 implementations with proven value, across 41 organizations in seven countries, 61% of which grew out of an attempt that had failed before. The presentation is in Portuguese and brings the study's most uncomfortable finding for this audience: support functions, HR included, were the most frequent source of resistance, ahead of the users themselves. Published field research, with the selection bias acknowledged by the author herself.

Three founders look back on AI adoption in their own companies: whether it came from the top or the base, what they measured, what they abandoned with money already spent, and what they would do differently. Guilherme Weigert runs Conexa Saúde, a telehealth operation with more than thirty million patients served, which went AI-first by manifesto. David Pires is leading Zig's redesign with AI at the center of the operation. Fernando Gadotti founded Tako AI-first and tells what breaks when a company is born that way. Part of this conversation is about you: how founders see HR's role in this shift, said to your face.

The project was announced with fanfare, the pilot worked, and six months later almost nobody uses it. Jonathan Levav, professor at the Stanford Graduate School of Business, dedicates this session to the four human forces that hold back AI's promised productivity, and to the mechanisms that make projects stall right after the announcement. One hour with Q&A, and every force he describes will echo a story you heard earlier on this stage. Behavior is the one territory where HR is the best-equipped function in the company.

By the end of the day, iFood will have been mentioned on stage more often than any other company, and not by accident. To close, Raphael Bozza, iFood's CHRO, tells the journey of making the company AI-first: when it became a decision, what broke along the way, the role HR took on in the shift, what he would do differently, and where the journey has not yet arrived. The CHRO-to-CHRO version, hard chapters included.