Future of Technology
Technologists and futurists exploring how emerging innovation will reshape industries, economies and daily life
Banking, payments and customer trust are being rewritten by code, and most incumbent institutions are still organising around branches, products and quarterly earnings. Boards know the platform players, embedded finance and AI agents are reshaping the economics of the industry. The strategic question is how far to push, how fast, and what kind of institution remains on the other side.
Most organisations treat innovation as a technology question and culture as a brand question. The two functions report separately, fund separately, and rarely produce anything a customer can actually use. The leaders who build durable advantage are the ones who can run cultural intuition and product engineering as a single discipline.
A handful of companies now sit between every business and its customers, and the rules of competition no longer reward operational excellence alone. Leaders are being asked to build durable strategy inside an economy where scale, data, and distribution compound for a few and erode for everyone else. The question is no longer how to compete, but where the next defensible position actually exists.
Most organisations have built hybrid operating models without ever deciding which conversations belong on which channel. Email, video, instant message and phone get used by reflex, and the cost shows up in fractured trust, slow decisions and meetings that produce noise rather than alignment. The question is no longer whether to work remotely. It is which medium to use, for what conversation, and what that choice does to performance.
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 consume far more futures content than they can act on. The problem is not a shortage of prediction. It is the absence of a structured method for connecting macro change to the specific decisions an organisation is already under pressure to make. Without that connection, strategic planning is reactive, investment decisions trail the market, and the wrong questions dominate the board’s time.
Most boards now treat AI as a strategic line item, but few know how to translate it into operating advantage without tripping the regulators, the workforce, or the customer. The gap between AI ambition and AI deployment is widening, not closing. Leaders need someone who has sat on both sides: the commercial side that has to ship, and the governance side that decides what shipping looks like.
Categories that touch women’s health, hormones, or stigmatised physiology have been chronically underbuilt. Consumer brands and digital health teams keep underestimating the commercial opportunity in markets they personally find awkward to discuss. Building credibly in those spaces requires a founder who has done both: scaled a brand business and raised capital around physiology most boardrooms still avoid.
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 now running AI through their creative, design and brand functions without a clear view of what humans should still own and what machines should do. The result is output that looks generative but feels generic, and teams that cannot articulate where their craft adds value. The harder question, what creative judgement actually contributes once the machine can produce a draft, rarely gets answered.
Boards know AI is not optional. What they do not know is which of the dozen initiatives on the deck will compound into advantage, and which will sink six quarters of budget into pilots that never scale. The gap is not ambition, it is a repeatable way to decide where the organisation actually stands and what to do next.
Most leadership teams have an AI strategy that describes adoption. They do not have one that describes consequences. The systems being deployed across defence, finance, and healthcare are no longer tools that can be audited line by line, and the gap between what an executive can authorise and what the underlying technology actually does is widening month by month.