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 are now expected to have a view on AI, online manipulation and digital trust without having lived inside any of those worlds. The gap between what executives understand about the internet and what is actually happening on it has become a governance problem, not a technology problem. Most strategy documents treat that gap as a training issue. It is closer to a credibility issue.
Most consumer technology ideas die in the gap between a working prototype and a business that can scale. The pressure comes from all sides at once: capital runs thin, distribution stalls, investors pass, and the founder has to decide what to keep building and what to cut. The organisations that want to back, buy, or learn from founders at that stage need an honest account of what the decisions actually look like from inside the company.
Most senior teams now agree AI matters. Far fewer can say what it changes about their specific business this quarter. The gap between abstract enthusiasm and operational decision sits at board level, and it widens every month a leadership team relies on vendor decks for its mental model of the technology.
Customers now judge a company by how fast it responds and how it handles the people who complain. Most organisations treat speed and complaints as service problems, when in commercial terms they are the largest available source of growth and the largest unmanaged source of churn. The gap between what customers expect of responsiveness and what companies deliver is where revenue quietly leaks.
Established organisations invest heavily in optimising what already works, and that focus becomes the liability when the market shifts. The leaders most at risk are not those who ignore change but those who see it clearly and still cannot mobilise their organisation to act before the window closes. The gap between recognising disruption and profiting from it is rarely a knowledge problem; it is a strategic and cultural one.
Most leadership teams have an AI strategy that describes adoption. They do not have one that describes consequences. The systems being deployed across defence, finance, and healthcare are no longer tools that can be audited line by line, and the gap between what an executive can authorise and what the underlying technology actually does is widening month by month.
Most organisations treat customer experience as a service function that reacts to complaints, surveys and churn. The work that drives loyalty, retention and pricing power happens earlier, in the design of the journey itself, and most leadership teams do not own it. The gap between stated customer-centricity and the operating model that would deliver it is where revenue quietly leaks.
Command-and-control structures are failing under conditions of permanent volatility, yet most executive teams still default to them under pressure. Senior leaders are being asked to authorise decisions at a speed and scale their hierarchies were never built for. The real question is no longer how to push change through the organisation, but how to lead one that has to coordinate without being controlled.
Most organisations treat innovation as a technology question and culture as a brand question. The two functions report separately, fund separately, and rarely produce anything a customer can actually use. The leaders who build durable advantage are the ones who can run cultural intuition and product engineering as a single discipline.
Most consumer businesses do not invent new categories, they iterate inside existing ones. The leaders who do invent categories then face a second problem: holding the category open against well-resourced incumbents while the underlying economics shift beneath them. Knowing how someone has actually run that loop, not theorised it, is what boards want when their own model is under strain.
Assembling the right panellists solves one problem. Ensuring the moderator can hold their own in the conversation – in two languages, across AI, data governance, and autonomous systems – is another. Most technology organisations choose format over content knowledge, and the audience notices.
Most transformation programmes fail before the technology becomes the problem. Leaders invest in AI tools and change programmes, then stall because people are still holding on to a stable world that no longer exists. The gap between what organisations know they must do and what their leaders are equipped to do keeps widening, and it shows up in market value, talent, and relevance.