Innovation och omvälvning
Talare som undersöker hur industrier omformas och hur organisationer kan leda förändring i stället för att följa den
Speakers Associates represents 390 speakers on Innovation och omvälvning, including Kemal Apaydin, Michael Lyon, Peter Fisk, Neri Karra Sillaman, Mark Stevenson, Nilofer Merchant, Itai Green, Lucy Bullivant, Rita McGrath och Katja Schipperheijn.
Most senior teams have run their first generative AI pilots and stalled. The technology is general-purpose, but the operating decisions are not: which workflows to redesign, which tools to standardise on, where hallucination is tolerable and where it is not. The question is no longer whether to adopt, but how to convert curiosity into measurable operating advantage without ceding judgement to the model.
Most organisations are structured to absorb change slowly, through plans, reviews and sign-offs. The world they now operate in moves faster than those systems can process. Leaders are being asked to make good decisions on projects that have no precedent, with teams they rarely see in person, against competitors who did not exist two years ago.
Financial firms are under pressure to put generative and agentic AI into regulated work without breaching rules, losing trust, or building tools advisers ignore. Most boards can describe the opportunity; far fewer can describe the operating model, the controls, or where an agent stops helping and becomes a liability. The gap between AI ambition and deployment that creates value without eroding the business model is where most programmes stall.
Most deep technology never leaves the laboratory. The gap between a working prototype and a regulated, commercially viable product is where ambitious R&D programmes quietly fail, and where boards lose patience with science-led ventures. The harder question for leadership is what discipline lets a research breakthrough survive the journey to market without losing its scientific integrity.
Legacy businesses do not collapse in a single quarter. They drift, protected by brand equity and habit, until the cost base no longer fits the revenue. The hard work for a leadership team is deciding what to cut, what to defend, and how to keep talent on side while the operating model is rebuilt in public.
Biology is becoming a programmable technology, and most leadership teams still treat it as someone else’s R and D problem. The commercial consequences of that blind spot are accelerating across materials, health, food, energy and computing. Boards need a clear read on which of these shifts are hype, which are imminent, and what a credible corporate response looks like.
Most large companies still treat innovation as a creative event rather than a managed discipline. The teams shipping new products lack the metrics, governance, and decision rules that the core business takes for granted, so good ideas stall and bad ones consume capital for too long. Growth then depends on individual heroics instead of a repeatable system.
Most organisations manage their brand as a communications output rather than a commercial asset – which means brand decisions get delegated to agencies while strategic questions about trust, market positioning, and identity remain unresolved at the leadership level. When a merger, market shift, or reputational event forces a rebrand, few executive teams have the analytical tools to distinguish what is worth keeping, what needs to change, and what the exercise will actually cost in customer equity. The result is expensive, slow, and often wrong.
Most large organisations say they want creativity and then build every process to suppress it. Standard operating procedure rewards predictability, and the people inside learn to stop offering the ideas that would move the business forward. The result is a leadership team that talks about innovation in strategy decks and sees very little of it in the work.
Leaders keep being asked to commit before the picture is clear. The information is incomplete, the team is mixed in experience, and the penalty for freezing is as high as the penalty for moving wrongly. What organisations need is not more data, it is a workable discipline for trusting a team, reading partial signals, and advancing when the path is not visible.
Technology is getting more capable faster than the people using it are getting more skilled. Most digital products are designed for efficiency, not for the human nervous system, and the gap shows up in fatigue, disengagement and shallow adoption. The question for leaders is no longer how to deploy AI faster, but how to design it so people actually want to live with it.
The middle ground that organisations were built around is thinning out, and the rate at which it thins is itself accelerating. Intermediaries lose their role, the nation state loses its monopoly on power, and customers and employees move to the edges. Senior teams have to decide which structures still pay back, which have quietly stopped working, and how to plan when the cycle of change is shortening.