Innovation & Disruption
Speakers who examine how industries are reshaped — and how organisations can lead rather than follow change
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.
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Most boards are setting AI strategy from briefings that are already out of date.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.
David Aguilar is an inventor and bioengineering graduate who designs and builds functional LEGO® prosthetic arm prototypes and speaks about innovation, resilience, and applied engineering.
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 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 bank digital transformation programmes are redesigning customer interfaces, not the structural model underneath. The real question is whether a bank retains a meaningful role when AI manages financial decisions autonomously on the customer’s behalf. Boards that cannot answer that question are investing in the wrong conversation.
Most leadership teams have more information about emerging technology than they have clarity about what to do with it. Platform launches and AI announcements arrive daily, and most will be irrelevant within a year. The question that matters is which signals to trust, and which to filter out before committing budget.