公司的未来：我们如何想象在由技术设计和定义的世界中运营的未来组织？

xx1 1.1Anomnipresent macro scenario An already omnipresent reality We are witnessing, at incredible speed, the emergence of a world where algorithms, which can be defined as digitalinvisible architectures of calculation and decision, have become omnipresent.As we observe in our consultingengagements,they are no longer just tools at the service of human will, but agents in their own right, shapingdecisions, organising flows of information, work, and resources, and changing the very nature of our experiences ofwork, relation or thinking-in companies,governments, and social systems alike. The macro scenario of an algorithmic future describes precisely this systemic shift: a world where the logic ofcomputation becomes the hegemonic organisational principle that structures sense-making, organisation, anddecision-making.In our consulting practice, we see thatit is not simply about integrating AI into existing processes,but about the transformation of governance, regulation, and collective existence through computationalinfrastructures. This is a deep mutation, not only technological, butphilosophical and political, which questions whodecides, how meaning is produced, and what place remains for the human in the loop. This future is not abstract.Infact, we observe concrete dynamics already underway: growing computing power, the exponential importance ofgenerative models such as GPT, Claude, or Gemini, the diffusion of algorithmic decision-making into finance,healthcare, law, logistics... And we can anticipate that technologies like quantum computing promise to amplify theseprocesses even further, multiplying both their capacities and their opacity. In other words, we are not conceptually addressing a question about future or potential issues,but confronting a verycontemporary one that we engage with directly in our client engagements, whose stakes and impacts are growingmore significant with each passing day (see, for instance, Amazon’s recent decision to let go of 10,000 HR workers,partly linked to AI-driven automation).From ourexperience the place and role we choose to give today to algorithms,AI, and computation are therefore fundamental asour individual and collective decisions now will heavily shapetomorrow’s experience. Three great axes structure the development of algorithmic futures The first axis is that of algorithmic governance: themovement toward a rationalised and optimised society inwhich algorithms no longer assist in decision-making butbecome the decision-makers themselves.We increasinglysee in our engagements thatthey regulate traffic in smartcities, allocate energy, manage health systems, shapebehaviours through credit scoring or social evaluation, andeven arbitrate truth through recommendations or thedetection of misinformation. Many thinkers have already explored this terrain andpointed out the dangers that come with it: AntoinetteRouvroy, for instance, describes a new form ofgovernmentality based on correlation rather thanthanlaw2; Evgeny Morozov criticizes the limits of technologicalsolutionism3. The second axis is that of algorithmic intelligence, wherecomputation, once limited to processing data throughprobabilities, begins to evolve toward cognition.In ourconsulting observations,through deep learning andgenerative architectures, algorithms now self-improve andstart to act as cognitive agents. Humans delegate not onlydecisions, but also creativity and reason itself. Optimists imagine a symbiosis: an augmented humanity, expanded in knowledge, longevity, and capacity for action. Others foresee a loss of autonomy, perhaps even the rise of non-humanforms of governance, driven by logics we may no longer understand. Nick Bostrom, with his vision of asuperintelligence surpassing humanity, was one of the first to articulate this possibility-a future where technologyceases to merely extend the human and begins to exist as an autonomous entity. A prospect that raises profoundquestions. Finally, the third axis is that of the algorithmic economy and imagination.We observe thatalgorithms are beginning toorchestrate production, consumption, and attention, transforming everything into data and correlation. Economicvalue becomes predictive.In our client work, we see thatalgorithms no longer simply answer the best to needs anddesires: they manufacture them.For some, this signals the emergence of a new creative intelligence and a more fluid,efficient market. Kevin Kelly4, for instance, is advocating the ability of digital networks to amplify collectiveintelligence in an unprecedented way. For others, it points to alienation: the capture of attention, the “outsourcing” of desire, and a subtle form of voluntary servitude. Shoshana Zuboff5is, for instance,pointing at the emergence ofsurveillance capitalism,and the risk of widespread behavioural extraction, where data collection exceeds the actualneeds of a given service and is then instrumentalised to predict and influence people’s future behaviours.