Inteligência Artificial e IA Generativa
Oradores que descodificam o impacto real da inteligência artificial em indústrias, força de trabalho e vantagem competitiva
Speakers Associates represents 355 speakers on Inteligência Artificial e IA Generativa, including Kemal Apaydin, Olivier Sibony, Rahaf Harfoush, Purna Virji, Itai Green, Limor Ziv, Tom Goodwin, Daniel Trabucchi & Tommaso Buganza, Katja Schipperheijn e Diana Verde Nieto.
Leaders are being asked to make decisions faster, against opponents and systems they do not fully understand, with machines increasingly involved in the thinking. The instinct is either to defer to the model or to dismiss it. Neither works. What organisations need is a clear view of where human judgement still carries the match, and where it should step aside.
Most technology leaders are asked to deliver speed, resilience and measurable performance with a flat budget and a shrinking error tolerance. The leadership conversation has moved past digital transformation as a project and now sits inside the operating model itself. What executives want is a working picture of how IT, data and AI compound into competitive advantage when decisions are made in seconds and failure is public.
Executive teams know the rules of the game have changed and still default to the playbook that built the last decade. Automation is eating predictable work, and the human capabilities that matter most, empathy, judgement, persuasion, are the ones leadership pipelines were never designed to develop. The question is no longer whether to adapt, it is which parts of the business to rebuild first and how to develop the people who will lead that rebuild.
Most leaders now agree that AI will reshape their workforce. Fewer can say what that looks like on a Monday morning for a marketing coordinator, a finance analyst or a field engineer. The distance between boardroom AI strategy and the person being asked to use the tools is where adoption stalls, budgets leak and cultural resistance hardens.
Organisations are deploying AI capabilities faster than they are building the governance structures to manage them. The gap between what technology can do and what leadership has decided it should do keeps growing. The harder question is not whether to automate but what must remain human – and most boards do not yet have a framework to answer it.
Boards are being asked to make decisions about biometric data, immersive interfaces and human-machine integration before most leadership teams have a working vocabulary for any of it. The technology is moving into products, workplaces and customer experiences faster than governance can keep up. Organisations need a credible human-side view of where this is going, and what to commit to now.
Most retail and consumer businesses now operate across physical, digital and virtual channels at once, but their org charts, P&Ls and brand playbooks still assume a single dominant channel. The result is fragmented customer experience, duplicated investment, and a leadership team unsure which version of the business it is actually running. The harder question is what to centralise, what to redesign, and what to stop doing entirely.
Generative AI is being deployed faster than the governance, voting, and ownership systems around it can adapt. Boards now have to decide which AI systems get a seat at the decision table, who is accountable when those systems shape public opinion, and what legitimacy looks like when a model can speak with more authority than an executive. The hard question is no longer whether to use AI. It is how to keep human institutions credible while doing so.
Most boards still treat cybersecurity as a compliance line item managed by the CISO. The attackers do not. They move faster than procurement cycles, exploit the gap between IT controls and human behaviour, and turn ransomware into an operating crisis within hours. Leadership teams need a sharper feel for how attackers actually work, not another framework.
Sustainability investments have not delivered the commercial returns most organisations expected. AI adoption has followed the same pattern – pilots multiplied across business units, producing modest efficiencies but no strategic differentiation. The pressure on growth and commercial leaders is to turn both into genuine sources of customer value before the window for competitive advantage closes.
Most senior teams now accept that AI will reshape how their organisation works. The harder question is what their people should be doing more of, not less, as the technology takes on more of the cognitive load. Without an answer, transformation programmes default to tooling and miss the human capability shift the strategy actually depends on.
Senior leaders are being asked to commit capital and strategy to technologies whose second-order effects are still being written. The gap is not a shortage of information about AI, cybersecurity or platform shifts. It is the absence of a sober, editorially disciplined read on which signals matter, which are noise, and what the next eighteen months look like for the companies making the bets.