Innovation & Disruption
Speakers who examine how industries are reshaped — and how organisations can lead rather than follow change
Most enterprises have run AI pilots. Far fewer have an actual playbook for how AI changes the way work gets done. Leaders are stuck between vendor noise, employee anxiety, and a board asking why productivity has not moved.
Most brands can no longer rely on advertising spend to sustain commercial growth. Consumer purchasing decisions are now driven by taste, values, and cultural affiliation, forces that sit outside the traditional marketing brief. Organisations built for reach-and-frequency marketing have no structural model for converting cultural relevance into revenue.
Younger consumers and workers no longer accept the trade-offs older marketing playbooks were built on. They expect brands to take a position, deliver on it, and prove it in the product, not in a campaign. Most commercial and brand teams are still reaching them with research that is one cohort behind the cultural reality.
Marketing budgets are under sharper scrutiny than at any point in a decade, and the old assumptions about how brands earn attention have stopped holding. AI has reset what creative, media and customer experience teams are expected to produce, and most organisations are still reasoning about it as a tool rather than a structural change to how brands compete. The commercial question is which parts of the marketing operation get rebuilt around AI, and which parts get protected because they still depend on human judgement.
Most large organisations treat creativity as a campaign, not a capability. They run an innovation sprint, produce a deck, and return to the same operating rhythm that produced the problem. The harder commercial question is how to make original thinking a daily habit of the people who already run the business, without a separate function or a hired-in consultancy.
Generative AI has moved faster than most operating models can absorb. Boards approve pilots, then stall on how to make the technology work inside real processes, real teams and real customer experiences. The gap between technology curiosity and operating capability is where transformation programmes lose momentum.
Most AI initiatives stall between the pilot and the operating line. Boards have approved spend, teams have shipped demos, and nothing in the actual product, process, or P&L has changed. The pressure now is to move from curiosity to deployed advantage, with governance that holds up to scrutiny and design choices that customers will actually use.
Most large organisations talk about simplicity and ship complexity. Product roadmaps grow, customer journeys fragment, internal processes accumulate, and the original argument for the business gets lost. The problem is rarely a shortage of ideas. It is the absence of a discipline for removing the wrong ones.
Most boards have approved AI strategies. Very few have AI in production at the heart of a regulated business. The gap between pilot enthusiasm and operating reality is where strategy stalls, governance gets nervous, and customer-facing teams quietly lose faith in the technology.
Most leadership teams now have an AI strategy on paper and very little operating conviction behind it. The question senior executives are actually asking is narrower and harder: which emerging technologies will compound into advantage, which will absorb capital and produce nothing, and how do you tell the difference early. Few people have lived both sides of that question, building a category from scratch and then placing hundreds of bets on what comes next.