Innovation & Disruption
Speakers who examine how industries are reshaped — and how organisations can lead rather than follow change
Speakers Associates represents 390 speakers on Innovation & Disruption, including Kemal Apaydin, Michael Lyon, Peter Fisk, Neri Karra Sillaman, Mark Stevenson, Nilofer Merchant, Itai Green, Lucy Bullivant, Rita McGrath and Katja Schipperheijn.
Markets are not behaving like markets anymore. Categories collapse, customer expectations shift mid-quarter, and the playbook that built the business is now the thing slowing it down. Senior teams know the brand needs to change shape; the harder question is which parts to keep and which to break on purpose.
Most boards are setting AI strategy from briefings that are already out of date. The pace of frontier development now exceeds the speed at which incumbent organisations can absorb it. Telling which shifts genuinely change the operating model from those that do not has become a core test of senior leadership.
Most organisations can name the technologies disrupting their sector. Few have leadership frameworks capable of responding at the speed those technologies actually move. The gap is not strategic awareness – it is the absence of a decision-making model built for exponential change rather than incremental adjustment. Organisations that cannot distinguish truly disruptive technologies from merely revolutionary ones will continue making that call by instinct – and that instinct was calibrated for a slower world.
Customer expectations don’t shift gradually – they reset when a leading business makes a move that becomes the new standard. Most organisations track their own customers too closely and the forces reshaping those customers not closely enough. The arrival of AI has made the problem acute: more signals, faster change, and a greater penalty for placing bets on the wrong ones.
Food and agribusiness companies tend to operate within one part of the value chain – retail, manufacturing, production, or inputs – and make strategic decisions based on a partial view. Consumer preferences, retail power dynamics and sustainability pressures are all shifting simultaneously, and their effects travel in both directions along the chain. A business that reads only its own segment will consistently misread both the timing and the scale of what is coming.
Most boards are now briefed on AI, but few have thought seriously about what happens when AI has a face. Customer service, healthcare, education and hospitality are all heading towards interactions with machines that look back at you, recognise you, and hold a conversation. The strategic question is no longer whether the technology works. It is how organisations design for trust, responsibility and emotional register when the interface is a humanoid.
Most organisations talk about inclusion as a policy and innovation as a pipeline. The harder question is whether the people the system was not designed for can actually build inside it, and whether their work is treated as engineering or as a story. Cultures that cannot answer that question lose both the talent and the output.
Most strategy processes treat the future as uncertain and respond by hedging. That posture costs time and investment while competitors move on signals that were knowable in advance. Leadership teams need a disciplined way to separate the parts of the future that are already decided from the parts that are still open, and to act on each differently.
AI has moved faster than the institutions it is reshaping. Leaders now face a version of the problem that universities are confronting first: when the tools students, employees, and customers use can produce plausible work in seconds, the old boundaries around expertise, integrity, and credentialing stop holding. The question is no longer whether to adopt AI, but which parts of the institution it quietly dismantles if you do.
Most organisations say they want more creative thinking, then run every meeting, incentive and review process to reward predictable answers. Senior teams know the habits that built the business are not the habits that will change it. The hard part is getting a roomful of smart, time-poor executives to actually practise a different way of seeing a problem.
Most leadership teams treat AI as an efficiency question rather than a question of identity. When algorithms absorb cognitive work, the traits that actually differentiate an organisation become both more valuable and harder to preserve. The strategic question is not whether to adopt AI but what a business chooses to remain unmistakably human about as AI reshapes the default.
Most large banks know their operating model was not built for the speed of modern technology. The harder question is not whether to innovate but how: when to build, when to partner with a startup, when to buy, and how to make any of that stick inside a regulated balance sheet. Leaders need honest answers from people who have sat on both sides of that table.