Innovación y disrupción
Oradores que analizan cómo se transforman las industrias y cómo las organizaciones pueden liderar el cambio en lugar de seguirlo
Speakers Associates represents 390 speakers on Innovación y disrupción, including Kemal Apaydin, Michael Lyon, Peter Fisk, Neri Karra Sillaman, Mark Stevenson, Nilofer Merchant, Itai Green, Lucy Bullivant, Rita McGrath y Katja Schipperheijn.
Strategy demands commitment, and commitment is what kills companies when the future does not arrive as forecast. Boards reward bold bets; the same bets concentrate risk in ways the planning cycle hides. The hard question is not which strategy to pick, but how to commit to one direction while keeping the option to be wrong.
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.
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 consumer businesses can describe their strategy. Far fewer can execute one that takes them from a category curiosity to a category leader. The gap is rarely about ideas. It is about portfolio discipline, the right partnerships, and a leadership team that can hold focus while the business multiplies in size.
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.
Most organisations declare innovation a priority, then quietly file the hardest ideas under impossible. Teams learn the difference between problems they are allowed to attempt and problems they should not raise. The result is a culture that produces incremental work and tells itself it is being ambitious.
Most organisations build new propositions inside structures designed to keep existing businesses running. Then they wonder why their innovation programmes produce decks and pilots, but very few new customers. The mismatch is rarely diagnosed at the level where it can be fixed.
Most sustainability strategies are written from a position of abundance. The harder test is what holds when resources collapse: degraded soil, brackish water, no reliable supply chains. Working models built under genuine constraint are rare and far more instructive than the aspirational frameworks most boards review.
Most digital transformation programmes are still run as technology projects. Boards approve platform spend and IT delivers the rollout, but adoption numbers come in below the business case. The gap between what the technology can do and what customers and employees actually use is where commercial returns disappear.
Most AI investment is still trapped in pilots, demos and isolated tools. The harder problem is redesigning how the organisation actually decides, staffs and operates once machines do meaningful work. Senior teams need a way to move from AI as a project portfolio to AI as the operating model.
Most boards now treat AI as a strategic priority without a grounded view of how the systems setting that pace are actually built. Executive advice tends to swing between technical detail no operator needs and speculation no fiduciary can act on. The view from inside a frontier lab is rarely in the room with the people who most need it.