Chapter 1 — Introduction (plain-language version)

The puzzle

Lisbon, late 2025. A junior consultant on a railway project drafts the risk section of a client presentation with an AI tool. It reads well, follows the textbook, and is wrong. The senior partner had spent three meetings working out the rail regulator’s real concern, which the regulator could only hint at. The junior had not been in the room, since nobody thought to bring them, and neither had the tool.

I have advised on European infrastructure projects long enough to notice when something shifts beneath ordinary practice. Engagements continue and clients receive recommendations, yet the way the next generation of consultants is formed is changing.

There are two ways of talking about AI in advisory work. The first, dominant in vendor marketing and early research, treats it as banal: a productivity tool. In the second, the conditions under which professional judgment is formed are being altered. Junior work looks polished, but the grasp behind it is sometimes thinner than the polish suggests.

This work takes the second view seriously 💡 , and reads it through a philosophical framework. Its first anchor is Bernard Stiegler, a French philosopher who described proletarianisation: the loss of know-how as it moves into technical systems 💡 that the worker, the firm and the professional culture do not own 1 2 . Its second is the philosopher Hans Jonas, whose imperative of responsibility grounds what infrastructure advisers owe the publics who bear the consequences of decisions 3 .

I am not arguing that consulting was better before AI 💡 , or that the tools should be refused 💡 . The argument is that the conditions under which advisory work has reproduced its expertise are being structurally altered by new technologies and ways of working 💡 . I test it in European infrastructure advisory, where the stakes are easiest to see.

The title, and what each part of it does

The title is The Proletarianisation of Advisory: Judgment, Sovereignty, and Responsibility in European Infrastructure Consulting under AI Mediation.

Proletarianisation, in Stiegler’s sense, reaches beyond practical know-how to the know-how of living and thinking 1 2 . It is selective: the worker remains, but the expertise that made them a professional is displaced.

Judgment is the expertise of those who can do the work, formed by living with consequences, as the sociologist Harry Collins describes it 4 . Sovereignty works at two scales: the European public-interest tradition and each firm’s own way of seeing, both at risk from tools that carry the habits of their training material. Responsibility is Jonas’s term for what the work owes the public, including future generations 3 .

European Infrastructure Consulting names the research scope 💡 : transport, energy, water, defence and other public projects, one family bound by a public-purpose tradition. Under AI Mediation names the mechanism. The work names no products: tools change faster than writing can track 💡 .

The central claim, and why it matters

The claim works at two levels. In general:

Generic AI mediation, under current conditions, risks proletarianising the situated, answerable judgment on which the legitimacy of professional advisory work rests.

In plain words: general-purpose AI, as it is built and owned today, risks draining away the judgment, rooted in real situations and answerable to real people, that gives advisers the right to be heard. In European infrastructure advisory the claim takes its most demanding form, because the profession’s obligations to the public and future generations depend on that judgment. This is the hardest case: finding the mechanism where replacing judgment should be least attractive strengthens the case for its generality without proving it. Readers in other advisory fields should read the infrastructure material as an instance of the general claim, not its boundary.

It matters for three reasons. First, existing research on AI in consulting sees tasks, workflows and efficiency gains, but not what happens to professional formation, to a firm’s distinctiveness, or to what advisers owe the public. Second, infrastructure decisions bind futures materially: a grid connection or a tram extension shapes how people live for decades, sometimes generations. Whether those decisions stay answerable to the public depends on the profession keeping the expertise that answerability rests on. Third, the argument yields recommendations for consultants, firms, clients and European policymakers. 💡

Six “original” contributions

Research on AI in consulting, on AI sovereignty, on neighbouring professions such as law and software 💡 , and in philosophy has not been brought together on this question.

First, the work applies Stiegler’s proletarianisation to management consultancy 💡 , at three scales: the consultant, the firm and the cultural-professional domain 1 5 . Second, it extends Jonas’s imperative of responsibility 3 to infrastructure advice, which grounds what advisers owe the third box: the publics and future generations who bear the consequences. Third, it maps the three career stages of the Chartered Management Consultant framework 6 against what AI can substitute at each, to my knowledge for the first time 💡 . Fourth, it describes pipeline rupture: the path from junior to senior can break whatever happens to headcount, as software and law already show. Fifth, it joins national and organisational sovereignty through one mechanism, where existing research stays mostly procedural. Sixth, it builds four scenarios as thought experiments, not predictions 7 .

How the research was done, and where I stand

I write as a working consultant in European infrastructure, and the itch behind this work is one I have experienced 💡 . The material comes from my own practice, colleagues and published research.

My position gives access outsiders cannot reach: the feel of client relationships, the quiet forming of judgment in daily practice. The burden is vested interest, and the temptation to mistake my situation for the field’s. I follow Donald Schön 8 , who argued that practitioners reflect in action rather than merely apply theory.

There are limits 💡 . This is not a systematic empirical study: no interviews, no survey, no long-term study of firms. The claims are conceptual and about what advisers owe. Testing them in practice remains open.

How this work is structured

Chapters 2 and 3 lay the ground: what consulting means, why European infrastructure advisory is distinct, the third box as the people advisers answer to 9 3 , and the philosophical framework.

Chapters 4 and 5 describe how expertise is made in individuals, firms and the field, then how general AI tools tilt advisory work toward the habits of their training material while a firm’s knowledge risks flowing outward into the models it uses.

Chapter 6 brings evidence from software and law. Chapter 7, the core analysis, follows the mechanism through three career stages: juniors lose the tasks that formed them, mid-career consultants the work that showed the firm’s value, and seniors meet clients building their own AI capability. Some firms and partners choose differently 💡 .

In Chapter 8, four scenarios yield seven findings that hold in any future, among them the formation question, sovereignty pressure, the third box, and the profession’s need to explain its legitimacy. Chapter 9 offers recommendations, limits, and questions further work could 💡 take up.