Future of Technology
Technologists and futurists exploring how emerging innovation will reshape industries, economies and daily life
Most boards are now expected to take a public position on AI and immersive technology before the rules that will govern them exist. They are making capital decisions on cities, infrastructure and customer environments under standards that are still being drafted. Knowing who is writing those standards, and how to align to them early, has become a leadership question, not a technical one.
Boards have approved AI pilots, signed responsible-AI principles, and named ethics committees, and still cannot answer whether their deployed systems would survive a regulator’s audit or a serious public failure. The gap is not awareness. It is the operating distance between governance language and the decisions engineers, product leads and procurement teams actually make every week.
Most boards still treat AI as a software question their CIO will solve. The story is bigger than that. The contest is over compute, fabs, energy supply, and the sovereign infrastructure that will decide which companies and which countries hold the next decade of pricing power. Leaders who frame AI as a productivity tool are already a strategy cycle behind.
Most leadership teams know the pace of change has shifted, but their planning cycles, capital decisions, and org charts still assume a slower world. The cost of that mismatch is invisible until a competitor moves first, a category re-prices, or a technology curve bends. Boards need an outside voice that can name what is actually accelerating in their industry, separate signal from noise, and put a sharper time horizon on decisions already on the table.
Most AI deployments produce pilots, not capability. Tools land in the organisation faster than people can absorb them, and leaders default to vendor narratives because they lack a vocabulary for the human variables that decide whether productivity actually moves. The bottleneck is rarely the model. It is the gap between what AI can do and how the workforce learns to think with it.
Senior teams rehearse for crises they expect and freeze when the actual one arrives. The gap between a documented decision protocol and a leader who can run one in real time is where most organisations are exposed. Mission control culture closes that gap, and very few people in business have lived inside it.
Boards are asked to commit capital to AI before the returns are visible, and to do so while regulators, sovereign governments and a small group of US infrastructure companies redraw the rules around them. Most leadership teams do not have an internal source who covers all three at once. The gap shows up as exposure: investments made on vendor narratives, strategy decks built on last quarter’s headlines, and a quiet sense that the people in the room do not actually know who controls what.
Established firms are organised to defend what they already do well. The same discipline that protects today’s margin makes the search for the next business feel slow, indulgent, and easy to defund. Leaders need a way to run both at once, without the exploration agenda quietly losing every internal argument.
Boards are being asked to make calls on artificial intelligence and health technology before the evidence base has settled. Most senior teams have a strong grasp of the hype cycle and a weak grasp of what the science actually supports, where the ethical exposure sits, and which innovations will reach customers and workforces inside the planning horizon. The gap between confident vendor pitches and defensible internal judgement is widening.
Frontier technology now arrives faster than corporate strategy, regulatory frameworks, or supply chains can absorb it. Boards face decisions about immersive platforms, defence-adjacent tools, and contested AI applications with no precedent to draw on. The cost of waiting is ceded ground. The cost of moving without judgement is reputational and ethical exposure that does not unwind.
Most boards now treat AI as a strategic priority without a grounded view of how the systems setting that pace are actually built. Executive advice tends to swing between technical detail no operator needs and speculation no fiduciary can act on. The view from inside a frontier lab is rarely in the room with the people who most need it.
Energy transition strategies designed in mature markets break the moment they meet a weak grid, a thin balance sheet, or a population already paying for diesel. Boards investing in climate, infrastructure or emerging markets need someone who has built clean energy hardware and software where the grid is unreliable and capital is scarce, not someone who has only modelled it. The gap between net zero ambition and operational reality is widest exactly where the next billion energy customers are coming online.