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.
A reputational incident now plays out on a faster clock than the leadership team can convene. Executives are asked to be visible, accurate and human within hours, often with incomplete information and a watching newsroom. The capability to absorb pressure, choose words carefully and stay credible on camera has become a senior leadership requirement, not a communications function.
Most brands still treat marketing as broadcast: a message pushed at a customer through paid media. The customer, meanwhile, decides whether to buy on the basis of what the brand actually does to them in the room, in the app, in the stadium, in the store. The gap between what marketing departments produce and what customers experience is where commercial advantage is now lost or won.
Boards keep hearing that frontier AI is either an existential threat or an inevitable productivity engine, and neither framing helps them set policy. Inside the firm, the practical question is sharper: which capabilities are safe to deploy, what governance is credible to regulators, and how do you tell hype from a real shift in the technology. Most leadership teams have no independent technical voice they trust to answer that.
Early-stage AI companies are hiring against a market that did not exist three years ago. The roles they need are senior, the candidate pool is shallow, and the cost of a wrong executive hire shows up in the first investor update. Founders are trying to scale commercial and technical leadership while still building the product.
Most leadership teams still think about competition the way they think about products: build a better one and customers follow. Platforms break that logic. The harder question is when to compete as a product, when to open an ecosystem, and how to avoid funding rivals you have just enabled.
Industry boundaries are moving faster than strategy teams can redraw them. Software firms, platforms and AI entrants now compete inside sectors that once felt structurally protected, and the rules of value capture have changed with them. Boards keep asking the same question: where in this ecosystem do we still own the customer, and where are we becoming a component in someone else’s stack.
Consumer categories are dissolving faster than brand playbooks can keep up. The familiar segmentation logic, demographic targeting, and brand positioning frameworks that powered the last two decades of marketing are producing diminishing returns against shoppers who refuse to behave consistently across channels, life stages, or identities. Marketing leaders need a sharper read on why people actually buy, and what AI, avatars, and fashion signal about commercial intent.
The cost of capital has reset and globalisation no longer guarantees cheap inputs or stable demand. Growth itself now depends on policy choices to a degree it did not a decade ago. Senior leaders are allocating capital across regions where trade rules and AI policy are being rewritten in real time.
Most large digital and AI investments stall before they deliver. The technology is rarely the reason. The operating model and leadership decisions move slower than the tools, and that mismatch is where most programmes quietly slide off the agenda.
Boards and executive teams know they need to act on AI, but most are stuck between vendor pitches, pilot fatigue and a regulatory picture that keeps moving. The harder question is not whether to invest, but which decisions belong in the boardroom, which belong with the operators, and how to govern the technology without stalling it. Few advisors have sat on all three sides of that table: building the technology, running it at scale, and writing the policy that shapes its limits.
Most change programmes stall in the gap between what leaders ask people to do and what people actually do. Restructures, AI rollouts and new operating models depend on behaviour change inside a workforce that is already tired of being changed. The leadership question is no longer what to do; it is how to get a real human organisation to follow through.
Boards are being asked to make capital commitments against technologies that will not mature for a decade or more. Quantum computing, AI, biotech and energy are converging on timelines most strategy processes are not built to hold. Leaders need a credible read on what is physically possible, what is hype, and where the next decade of value will actually sit.