Progress takes more than a breakthrough.

AI gives us reasons to be hopeful about better healthcare, new scientific discoveries and more effective public services. But technological breakthroughs won’t deliver that potential on their own. Our starting hypothesis is that progress depends on building the conditions for useful technology alongside the technology itself: evidence people can trust, credible demand, shared resources and institutions able to put it to work.

With these essays, we hope to offer a few ideas for a path between dystopia and utopia to help decision-makers, from public officials to private individuals, consider some practical responses to the latest developments in AI. All of it requires reclaiming agency, both personal and collective, and taking responsibility for how AI diffuses across society.

We have spent our careers navigating this gap, building teams and programmes inside fast-growing companies where policy, science and markets meet. Much of that work means connecting people who see different parts of a problem: researchers, founders, public officials and funders. Founders we have backed bring us similar questions: who will buy this, what evidence will they need, and who must work together?

That suggests starting with a field and asking what better would look like in ten years. We like Cosmos Institute’s idea of the philosopher-builder: someone who asks what they are building for, and puts that thinking into practice. Which parts can a company deliver? What else is missing? A shared dataset, an independent evaluation or a coalition of buyers may be as important as the product. These can support many builders and institutions, and change which ideas get built at all.

What matters is whether we can collectively shape how AI is absorbed so that everyone benefits. It’s true that we will be able to solve problems that we couldn’t without AI, but it’s equally true that there are plenty of problems AI won’t be able to solve without us. Take the NHS. AI could tackle the acute challenge of queueing for care, but turning the system toward preventative care rather than treating the sick isn't something it can operationalise alone. Building the trust and incentives for transformational change is work only the people within and around the system can do.

Science and engineering can only take us so far. They are the practice of finding the best solution within a given set of constraints. Democracy is something else: the practice of “forming a more perfect union,” or, put more simply, figuring out how we live together.

Public benefit cannot be defined from inside the technology sector alone. Patients, teachers, workers, researchers and public officials should help shape the problems, measures of success and decisions along the way. Progress should be felt in their lives: a more reliable energy system, a more accessible service, a discovery that becomes something people can use.

Underneath it all is a bet that when people experience science and technology in ways that benefit them directly, they are far more likely to welcome it into daily life and to trust the institutions that brought it to them.

The five essays explore who gets to share in the value created, and how proven technology gets stuck before it reaches those who need it most in public services like the NHS. They ask what ‘sovereign AI’ should actually mean, and why governments should focus on shaping demand rather than building supply. They also look at where we need to build what the market won’t deliver on its own.

These essays are our way of testing that reasoning in the open, and seeking common ground on what we want the next twenty years to look like. We would love you to read and think along with us: share something we should be reading, tell us where you disagree, or bring a question we have not thought to ask.