Innovation & Disruption speakers
Speakers who examine how industries are reshaped — and how organisations can lead rather than follow change
Speakers Associates represents 393 speakers on Innovation & Disruption, including Kemal Apaydin, Michael Lyon, Peter Fisk, Mark Stevenson, Nilofer Merchant, Tahl Raz, Lucy Bullivant, Rita McGrath, Katja Schipperheijn and Neri Karra Sillaman.
Most large companies treat innovation as theatre. They host hackathons, set up labs, announce partnerships, and run accelerators, ending up with a pipeline of pilots that never reach the P&L. The real problem is converting a corporation’s existing assets into products the market will actually pay for.
Most organisations are built to protect what already works – and that same structural logic systematically crowds out the conditions where genuinely new markets emerge. The processes that govern existing product lines, the approval cycles, the business-case requirements: these are exactly what engineering-led invention cannot survive inside. Understanding that gap – not just naming it – is what most innovation strategies fail to do.
Most organisations cannot explain why smart executives fail, and they cannot explain why a small number of leaders consistently produce extraordinary talent pipelines. Both gaps cost the same thing: the next generation of leaders. When the senior team cannot reliably diagnose executive failure or deliberately replicate talent-generating leadership, succession planning, strategic M&A and cultural change all become exercises in hope.
Most leaders are operating with inherited assumptions about what persuades people, what builds lasting professional influence, and what actually separates executives who reach the top from those who plateau – and the empirical evidence consistently contradicts those assumptions. Negotiation training defaults to rational-actor models that perform poorly under pressure; leadership development programmes chase credentials and charisma while overlooking the four behaviours that large-scale CEO data shows actually predict success. The result is that organisations invest heavily in influence and leadership capability while working from frameworks that the evidence has already disproved.
Customers do not behave the way product, marketing and strategy decks assume they will. They misread information, default to inertia, and disengage at exactly the moments organisations most need them to act. Closing that gap between what behaviour the business model requires and what cognition actually delivers is the work.
The integration of brain data, AI, and consumer-grade neurotechnology is moving faster than most senior leaders realise. The organisations engaging with this territory now will set the terms others have to accept later. Most boards do not yet have a real position on it.
Most organisations talk about innovation and treat creativity as a workshop activity, not a leadership capability. The result is incremental change, fatigued teams and a culture that cannot generate new direction when the operating context shifts. The deeper question is whether creativity, inclusion and collective purpose can be designed into how a workforce actually runs, or whether they remain decorative.
Organisations claim they want diverse teams and original thinking, yet the networks inside them keep producing the same conversations with the same people. Hiring loops recycle, ideas stall, and inclusion stays at the level of statement rather than practice. The friction is not values. It is the structure of who talks to whom.
Most leadership teams have run their generative AI pilots and now face a harder question: where does the technology actually sit inside the operating model, and which categories of work change shape entirely. The answer is rarely visible from the inside, where vendors pitch tools and consultants pitch frameworks. It comes from people who have built original commercial product with these systems and watched the next layer of human-machine technology arrive in a hospital bed.
Most leadership teams know the operating environment has shifted. Far fewer have changed how they decide, allocate, or hold their nerve when the assumptions underneath the strategy are moving. The gap between knowing disruption matters and leading through it is where senior teams quietly lose ground.
Senior teams keep facing decisions where the cost of being wrong is irreversible and the data is incomplete. Most leadership development cannot meet that condition honestly because most leadership careers do not. The question is what command actually requires when checklists run out, the crew is exhausted, and the call still has to be made.
Most enterprises now have an AI strategy on paper and very little of it in production. The board wants returns, the engineering organisation is still rewriting pilots, and personalisation, agents and generative AI are stuck behind unresolved questions on data, privacy and operating model. The gap between AI ambition and AI in revenue is now the defining technology problem of the cycle.