Teknologins framtid speakers
Teknologer och framtidstänkare utforskar hur innovation kommer att omvandla industrier, ekonomi och vardagsliv
Speakers Associates represents 251 speakers on Teknologins framtid, including Michael Beckley, Michael Lyon, Mark Stevenson, Ashlea Atigolo, Kemal Apaydin, Edvard Moser, Nikolas Badminton, Marc Saltzman, Alex Goryachev och Timandra Harkness.
Boards are asked to commit capital to AI before the returns are visible, and to do so while regulators, sovereign governments and a small group of US infrastructure companies redraw the rules around them. Most leadership teams do not have an internal source who covers all three at once. The gap shows up as exposure: investments made on vendor narratives, strategy decks built on last quarter’s headlines, and a quiet sense that the people in the room do not actually know who controls what.
Most boards understand that AI, 3D content and immersive platforms will reshape how brands meet customers. Few have any operational picture of what that actually looks like inside their business. The gap between strategy decks about the metaverse and a working AI commerce stack is where most digital ambition stalls.
Autonomous AI agents have started acting on people’s behalf, sending messages, booking, buying, and making decisions without a human in the loop. Organisations now have to decide how much of that autonomy to hand over, and who answers for it when an agent gets something wrong. The technology is moving faster than the controls and oversight meant to govern it.
Most leadership teams know they need a position on generative AI and immersive technology, yet very few can tell the difference between a real commercial use case and an expensive pilot. Vendors arrive with demos, internal teams chase tools, and the strategy stays vague. The hard work is choosing which technologies actually belong inside the business model and which are noise.
Marketing budgets are moving toward creators faster than most organisations know how to spend them well. Brand teams trained on paid media and agency frameworks are being asked to build relationships, communities, and platform-native content at a speed and authenticity that legacy approaches cannot deliver. The gap between “we should be on TikTok” and a working creator strategy is where most of the value, and most of the wasted spend, sits.
Boards are being asked to make calls on artificial intelligence and health technology before the evidence base has settled. Most senior teams have a strong grasp of the hype cycle and a weak grasp of what the science actually supports, where the ethical exposure sits, and which innovations will reach customers and workforces inside the planning horizon. The gap between confident vendor pitches and defensible internal judgement is widening.
Most leadership teams cannot articulate the basic scientific systems that their business depends on. When resources tighten, supply chains fracture or new technologies arrive faster than the strategy cycle, the gap between executive intuition and physical reality becomes a serious commercial risk. Foresight at this depth is rare, and almost never delivered with clarity.
Senior teams rehearse for crises they expect and freeze when the actual one arrives. The gap between a documented decision protocol and a leader who can run one in real time is where most organisations are exposed. Mission control culture closes that gap, and very few people in business have lived inside it.
Senior teams know the AI race rewards speed and punishes caution, even when caution is what their own risk function is asking for. Coordination across competitors looks naive; unilateral restraint looks like ceding ground. The question is how to operate, and govern, inside that pressure without sleepwalking into outcomes no one in the room actually wants.
Most organisations have AI governance policies. Very few have a principled account of what those policies are actually trying to govern. The result is compliance frameworks that cannot answer the questions boards now face: when AI acts, who is responsible, and why.
Large, multi-year programmes fail less often on technology than on coordination. The risk sits in holding a coalition of governments, suppliers and scientific egos together long enough to deliver, and in recovering credibility when something visible goes wrong. Most leadership models assume conditions far simpler than this.
Most organisations claim they want diverse technical talent, then keep recruiting from the same pipelines and wondering why nothing changes. The harder problem is cultural: how leaders make complex science legible to non-specialist audiences, and how they build environments where people who do not fit the standard profile of a scientist or engineer can stay and rise. Solving that takes more than a recruitment campaign.