Anarchy, in the profound sense attributed to it by Colin Ward, has nothing to do with chaos. It is a different way of thinking about the organisation of a society, not as a rigid apparatus but as a living ecosystem founded on clear, negotiable, adaptive norms that are, above all, free of a command-and-control centre. Ward invites us to observe reality: people, when they cooperate spontaneously, already display anarchic modes of self-organisation on many occasions (neighbourhood groups, shared coworking spaces, open-source online communities). Moreover, to quote him directly: “A great deal of research is done on methods of administration, but very little on self-management. There are entire libraries devoted to business management, management consultancies are paid handsomely, yet very few books, no courses of study and certainly no fees are directed at those who want to get rid of managers and replace them with workers’ self-management”. And perhaps that is why we continue to believe that repeating the same bureaucratic rules can guarantee us order and predictability, in a world where the status quo no longer exists. But it is no longer so: in the age of AI, innovation requires light structures, distributed autonomy, and a constant capacity to learn and adjust course.
The thesis of Kopernicana is that organisations born in the industrial era were designed for stability, but today they move within a complexity that no longer responds to the chain of command; and to address this it has chosen #Holacracy which can be read as a model that does not eliminate organisation but transforms it. It does not suppress structures, it turns them into enabling platforms. The same philosophy of Ward is found in Holacracy, which redistributes decision-making authority into clear and dynamic roles, allowing those closest to the problem to act without waiting for approval from a slow hierarchy. Robertson notes that “power is not in people, but in processes” — a phrase that echoes the anarchist principle of preventing the concentration of power in the hands of a few. Sociocracy deepens this philosophical continuity further through the consent process, the double link between circles, and the idea that organisations should “correct themselves” through continuous feedback cycles. The assumption is the same as Ward’s: the best rules are those produced by those who live directly with the consequences of decisions. Even the approach found in the text “Open Organisations” by Alberto Gangemi reaffirms that real work never coincides with the org chart and that the organisation takes shape through daily adjustments that emerge spontaneously from people. It is the idea that social ecosystems regulate themselves from within, like the trees of a forest that naturally generate the distance that separates them.
This perspective becomes even more urgent if we read it in light of the “Jagged Frontier” of Ethan Mollick. The AI frontier is not linear, it is jagged, unpredictable, full of areas where the technology surprises and others where it fails in a disarming way. In such a scenario, we cannot govern innovation with annual plans or rigid protocols. Continuous experimentation is needed, and above all it is needed where information is richest: at the margins of the organisation, close to the customer, close to the context, close to the problem. At FAIRFLAI we see it every day, because transformative insights do not come from boards but from those who live the jagged frontier of real work. The episode of a sales agent is exemplary: after one of our intensive courses, he understood that he didn’t need beautiful emails — he needed a channel his clients actually listened to. He took the technical brochure, had it translated (into understandable language) by AI and created personalised micro-videos and audio messages to send via WhatsApp. This solution was not foreseen by any official process, and precisely for that reason it was effective. Its value was born from proximity to the problem, and from the freedom to act. His innovation was not individual creativity — it was the consequence of a context that did not prevent him from trying something new.
If innovation is born at the margins, the role of #leadership changes profoundly. It is no longer about defining the direction, but about building the field within which people can move with autonomy and trust. Designing and cultivating the conditions for this to happen. Semco Style Institute Italy has been saying for decades that everything starts from mutual trust, from treating “adults like adults”, from letting teams find the solutions most suited to them, because “whoever is closest to the problem is best placed to solve it”. It is the same quality of leadership I recognised in Alberto Ostorero — my first boss (whom we remembered today at an internal Allianz event). That way he had of saying: “we’ll make it, you’ll see”, which today might seem naive, was in fact an act of operational trust. It was not superficial optimism, it was the conviction that when people are placed in the right conditions something always happens. This is the heart of self-organisation: believing in the system’s capacity to find its own solutions, provided it is given the information, the space, and the freedom it needs.
I don’t think the question should be how to control AI, but how to build organisations capable of moving with AI. Structures that do not stifle experimentation but distribute it, that do not inhibit the margin but enable it, that do not seek blind efficiency but evolutionary capacity. In the end everything converges on a single insight that belongs as much to anarchism as to the future of work: order emerges from freedom, not from coercion. Value is born from interactions between competent and autonomous people, not from their obedience. Complexity is faced with adaptation, not control. If we build #trust, #autonomy and frontiers free to experiment, the result cannot be otherwise.
Anarchy, in Ward’s sense and re-read for our times, is no longer a provocation — it becomes the grammar of the living organisation in the age of artificial intelligence to put into practice, one experiment at a time.
