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.
Boards now make capital and operating decisions inside a system where geoeconomic competition, supply shocks, technological disruption, and political fracture move faster than the institutions designed to manage them. Most leadership teams understand each risk in isolation. The harder problem is reading how they compound across regions and sectors, and what that means for growth, capital allocation, and the next decade.
Boards know AI is not optional. What they do not know is which of the dozen initiatives on the deck will compound into advantage, and which will sink six quarters of budget into pilots that never scale. The gap is not ambition, it is a repeatable way to decide where the organisation actually stands and what to do next.
Frontier technology now arrives faster than corporate strategy, regulatory frameworks, or supply chains can absorb it. Boards face decisions about immersive platforms, defence-adjacent tools, and contested AI applications with no precedent to draw on. The cost of waiting is ceded ground. The cost of moving without judgement is reputational and ethical exposure that does not unwind.
Most boards now treat AI as a strategic line item, but few know how to translate it into operating advantage without tripping the regulators, the workforce, or the customer. The gap between AI ambition and AI deployment is widening, not closing. Leaders need someone who has sat on both sides: the commercial side that has to ship, and the governance side that decides what shipping looks like.
Large organisations know they need to innovate faster than their own R&D cycles allow. They have budget, scouting teams, and pilot programmes, yet most startup engagements stall before any technology reaches a revenue line. The hard question is not where to find innovation; it is how to build the internal structure that lets a corporate actually absorb it.
Healthcare systems, employer health plans, and public health institutions keep designing for populations they do not include in the room. The result is wasted spend, poor outcomes for the communities that need the service most, and a widening gap between what leaders say about equity and what their operations actually deliver. Closing that gap takes an operator who can move between boardroom strategy, clinical reality, and the lived experience of the patients being served.
Most leadership teams have an AI strategy. Far fewer have changed how the business runs. The gap between stated intent and operating-model impact is where executive teams stall, and where the investment case quietly unravels.
Senior leaders are being asked to be more human at exactly the moment the job has become less human. Restructures, AI rollouts, hybrid teams, and constant pressure on results have left many executives defaulting to either detached toughness or performative empathy. Neither produces the trust, candour, or performance the business needs.
Boards are being asked to approve AI strategies they cannot evaluate. The architects of frontier systems openly say they do not fully understand what their models can do, yet executives are expected to deploy, govern and disclose around them. The shortfall is not technical literacy. It is a working theory of where the technology is heading and what that means for capital, headcount and liability.
Every board now owns cyber risk, but very few boards can read it. The attackers have industrialised, the attack surface has expanded into every connected device and vendor, and AI is widening the gap between what executives understand and what their defenders are actually facing. Leadership teams need someone who can make the threat concrete without making the room feel stupid.
Most organisations have run AI pilots. Few have moved from pilot to operating capability. The gap is rarely the technology; it is the absence of a structure that connects model choice, team design, ethics, and day-to-day decision rights across the business.
Most organisations are spending heavily on AI and still producing the same ideas they produced last year. The bottleneck is not the model or the tooling; it is the quality of human judgement brought to the work. The question senior leaders keep returning to is how to get original thinking and technological leverage from the same teams at the same time.