Teknologins framtid
Teknologer och framtidstänkare utforskar hur innovation kommer att omvandla industrier, ekonomi och vardagsliv
Speakers Associates represents 253 speakers on Teknologins framtid, including Kemal Apaydin, Michael Lyon, Mark Stevenson, Edvard Moser, Nikolas Badminton, Marc Saltzman, Alex Goryachev, Timandra Harkness, Chris Heemskerk och Dame Wendy Hall.
Most AI deployments produce pilots, not capability. Tools land in the organisation faster than people can absorb them, and leaders default to vendor narratives because they lack a vocabulary for the human variables that decide whether productivity actually moves. The bottleneck is rarely the model. It is the gap between what AI can do and how the workforce learns to think with it.
Categories that touch women’s health, hormones, or stigmatised physiology have been chronically underbuilt. Consumer brands and digital health teams keep underestimating the commercial opportunity in markets they personally find awkward to discuss. Building credibly in those spaces requires a founder who has done both: scaled a brand business and raised capital around physiology most boardrooms still avoid.
Strategy cycles run on three-year horizons. The technologies reshaping markets operate on ten-year ones. Without a methodology for reading early-stage signals, organisations discover the future after competitors have already acted on it.
Most organisations are now deploying AI and IoT faster than they are building the governance, culture and decision rights that decide whether those deployments will work. The technology gap is closing; the leadership-and-ethics gap is widening. Audiences want a speaker who has written the technical manuals and also spent years inside the rooms where large companies argue about whether to proceed.
Leaders now have access to more knowledge than at any point in history – and less clarity about what to do with it. Most strategic frameworks for navigating AI and exponential technology were designed for a world that no longer exists. The gap is not information; it is understanding: the capacity to anticipate what comes next, make decisions with philosophical coherence, and preserve human agency in organisations that are accelerating faster than their leadership thinking can follow.
Most organisations have built hybrid operating models without ever deciding which conversations belong on which channel. Email, video, instant message and phone get used by reflex, and the cost shows up in fractured trust, slow decisions and meetings that produce noise rather than alignment. The question is no longer whether to work remotely. It is which medium to use, for what conversation, and what that choice does to performance.
Biology is moving from something organisations observe to something they can write. Pharma, agriculture, materials, energy and insurance leaders now face an industry that behaves like software, with the same compounding curves, platform dynamics and governance risks. Most executive teams have no clear view of what is already possible, what is five years out, and where their own business model is exposed.
Most organisations want the upside of AI but cannot share the data that would make their models useful. Regulators, customers, and competitors all push in opposite directions, and the standard answer is to slow down. The harder question is how to use sensitive data across institutional boundaries without giving it up, and that question is now sitting on the desk of every senior leader running an AI programme.
Executive conversations on markets, policy and geopolitics rarely fail for lack of material. They fail when the person in the chair cannot press a CFO, a central banker and a trade minister with the same confidence, or hold a room when the news changes between rehearsal and showtime. The cost is a flagship event that reads as polite rather than sharp, and a leadership team whose message never lands.
Most planning tools were designed for a world that no longer exists. Strategy cycles built for predictable horizons break down when disruption compounds across technology, geopolitics, and social change at once, producing false confidence rather than genuine foresight. Organisations that cannot distinguish structural change from noise will always be reacting to a future someone else shaped.
Most innovation strategies still assume one capital model, one growth curve and one definition of a winning company. That assumption now constrains where ideas come from, who gets funded, and which businesses survive their second decade. Boards backing the next generation of operators need a sharper view of what disciplined, purpose-aligned entrepreneurship actually looks like at scale.
Most IoT and digital innovation projects run out of budget before they create value, and the reasons are rarely technical. They are structural. One function owns the work while others join too late, and the partner ecosystem needed to scale sits outside the room.