Rethinking the enterprise

The transformative impact of artificial intelligence on business organisations

AI revolutionises companies not only operationally, but also organisationally and strategically, promoting collaboration and cultural transformation

by Emiliano Pecis*

9 October 2025

4' min read

Translated by AI

Versione italiana

4' min read

Translated by AI

Versione italiana

The artificial intelligence is entering businesses a bit like electricity in the late 19th century: at first it was only used to light lamps, then it transformed factories and entire cities. Today, many see it only as a way to cut costs and time, but its impact goes much further. It is not only about technology, but about the very way in which companies function. We talked about this with Giorgio Sacconi, an expert in artificial intelligence and progressive organisations, co-founder of Fairflai, a micro-business that enables AI adoption models in companies and at the same time experiments with innovative forms of governance within them. With him, we tried to read AI on three intertwined levels: operational, organisational and strategic.

The operational plan: from shadow to transparency

In companies, AI is already present, but often lives in the shadows. There are those who use ChatGPT to write a presentation faster or to analyse a contract, without telling anyone. This phenomenon, called Shadow AI, produces a paradox: the individual gains time, but the organisation does not benefit. On the contrary, a climate of mistrust is generated, because bosses suspect that 'someone is putting in fewer hours than they should' and dump new work on employees.

To get out of this, transparency is needed. Agents only work with clear processes and well-structured data: powerful models are not enough, organisational order is needed. It is the same lesson as in progressive organisations: when roles and rules are explicit, collaboration improves. And even bureaucracy, which thrives on withholding information, loses ground.

The organisational plan: from wheat to rice

If on the operational level AI forces processes to be formalised, on the organisational level it challenges their cultural foundations. The logic that has governed many companies so far is that of the grain: everyone cultivates their own field, measures their own performance, defends their own boundaries. It is a model that rewards the individual and nurtures hierarchies built on seniority.

With AI, this approach shows its limits. A single, more efficient employee is not enough: what is needed is a team capable of integrating agents as new colleagues, to be trained, coordinated and grown together. It is the logic of rice, where the harvest depends on the shared control of water: without collaboration, the whole village fails.

Sacconi points out that this is where the real cultural challenge lies. The West is used to celebrating individual performance, while more collectivist cultures - the 'rice' ones, to be precise - have already codified cooperation as a precondition for success.

On this subject, the studies of the Nobel Prize winner for economics Ostrom are particularly interesting. Ostrom showed how communities sharing natural resources (water, land, agricultural territories) can self-govern themselves, create social rules to avoid depletion, conflicts, inefficiencies. In rice farming, especially in Asia, shared irrigation schemes require cooperation, rules, local organisation just like the adoption of Ai.

AI puts western companies at a crossroads: either continue to reward 'lone champions' or learn to build augmented teams, where artificial intelligence does not replace people, but amplifies their ability to act together.

And it is not just a matter of abstract culture. AI accelerates career paths: a junior who learns to use it well can reach senior skills within a year, disrupting traditional career times and logics. This 'buffers' hierarchies and paves the way for less rigid organisations, where legitimacy no longer comes from seniority, but from the ability to integrate new tools and share knowledge.

The strategic plan: choosing the full moon

The greatest risk, strategically speaking, is that AI will be reduced to a calculation exercise: "how much do I save?", "how many fewer people do I have to hire?". It is the half-moon that Sacconi describes: bright, yes, but incomplete. Companies that stop at this level risk a fragile advantage, easily replicated by competitors.

AI, on the other hand, opens up a more radical crossroads. On the one hand, there is the competitive scenario: everyone with their own agents, a patchwork of private automations, where it is mainly those who sell the tokens who gain. It is the logic of 'every man for himself', which produces immediate efficiency but little collective value. On the other hand, there is the collaborative scenario: agents seen as commons, a shared resource of the team and the organisation. Here, the game is not about cost, but about the ability to generate learning and innovation.

In this context, the strategic choice is not whether or not to adopt AI - because that game is already closed - but how to adopt it. The most agile start-ups are already scaling entire processes thanks to intelligent automations, multiplying their business speed tenfold. Those who remain anchored to short-term metrics risk discovering, too late, that the real competition is not the market neighbour but the new entrant who has built an entire organisation around AI.

Conclusion

In the end, companies have two roads ahead of them. They can either chase technology to squeeze a few more decimal points out of EBITDA, or use it to truly rethink themselves, moving from individual efficiency to collective intelligence. This is, after all, the challenge of those who believe that it is necessary to rethink the enterprise: not to adapt to technology, but to bend it to build organisations that are healthier, more durable and capable of creating value for all.

*Corporate Manager