Chapter 8 - Futures: Scenarios for European Infrastructure Advisory

8.1 Constructing the four scenarios

This chapter takes the cross-stage pattern Chapter 7 developed into futures. It constructs four scenarios for professional advisory under AI mediation - not predictions, not forecasts, not most-likely projections, but analytical exercises that stress-test the framework against alternative trajectory paths. The scenarios are constructed with European infrastructure advisory as the primary illustration: the specific content, the institutional actors, and the third-box stakes are developed in this research site. But the two structural axes from which the scenarios are derived are general: where expertise lives (in human practitioners or in AI models) and under whose sovereignty AI models operate (extractive Anglo-American commercial or alternative). The same scenario architecture - and the same four quadrants - applies to professional advisory contexts broadly. The Commodity Advisory trajectory is available to any advisory firm where AI mediation absorbs the formative base; the Artisanal Advisory trajectory is available to any advisory firm that recognises the formation question and builds its institutional choices around it.

Between the fourth scenario and the cross-scenario synthesis, the chapter includes a supplementary thought-experiment - the Knowledge Commons - positioned explicitly outside the four-quadrant structure. Its analytical purpose is to demonstrate that sovereignty and formation are genuinely independent problems: a commons that resolves sovereignty comprehensively leaves the formation deficit structurally intact, which by contrast clarifies what makes Artisanal Advisory’s institutional choices distinctive.

The chapter then identifies seven cross-scenario findings - concerns that hold regardless of which trajectory unfolds: the contributory/interactional distinction is the primary structural determinant of professional value, the formation question becomes inescapable, sovereignty pressure operates across multiple scales, the third-box question persists, explicit legitimacy narration becomes inescapable, extraction operates structurally in all scenarios, and the Applied stage has no safe trajectory. These seven findings are then carried into Chapter 9’s recommendations to constituencies. The recommendations are robust to the trajectory variation the scenarios capture because they are suited to concerns that hold across all four scenarios, not to any single trajectory.

The chapter is methodologically distinctive within the thesis. The analytical chapters (5, 6, 7) operate in the present tense - describing what is happening in current practice through the framework’s analytical apparatus. This chapter operates in a counterfactual register - describing what could happen under alternative trajectory paths, with analytical work suited to the framework’s concerns. The methodological framing in §8.2 articulates how this counterfactual register operates as philosophical thought-experimentation rather than as prediction.

The chapter is also where the framework’s analytical apparatus becomes most visibly integrated. The three ChMC stages from Chapter 7, the dual-scale sovereignty argument from Chapter 5, the extraction argument from Chapter 5, the third box from Chapter 2 (developed in Annex B), the integrated three-scale system from Chapter 4 - all operate across the four scenarios. The integration is what makes the cross-scenario findings robust.

8.2 Method: scenarios as philosophical thought-experiments

The scenarios in this chapter operate as philosophical thought-experiments, not as predictions. The methodological commitment is and requires explicit articulation.

The corporate-strategic scenario tradition - developed by Pierre Wack at Royal Dutch Shell in the 1970s 1 and elaborated by Kees van der Heijden 2 , Peter Schwartz 3 , and adjacent figures in the strategic-foresight literature - constructs scenarios as narratives that stress-test institutional decisions against alternative trajectory paths. Corporate-strategic scenarios are suited to the institutional decisions they support: they help institutions develop capability to operate under conditions that are structurally different from the present. The methodological tradition has been influential in strategic foresight practice and has analytical apparatus that the chapter draws on.

The philosophical thought-experiment tradition - developed in twentieth-century analytic philosophy, with contributions from Williamson on the epistemology of thought-experiments 4 , Brown and Fehige on the philosophical apparatus of thought-experimentation, and adjacent figures in philosophy of science - constructs counterfactual scenarios as analytical exercises that stress-test analytical frameworks against alternative conditions. Philosophical thought-experiments are suited to the analytical frameworks they engage: they help analytical traditions develop understanding of what their claims commit them to under conditions that are structurally different from the present.

The chapter’s methodological commitment is to bridge these two traditions. The scenarios operate as corporate-strategic exercises (the institutional content is suited to consequences for European infrastructure advisory) and as philosophical thought-experiments (the content is suited to stress-testing the framework’s analytical claims). The bridging is important because the framework’s concerns operate at both levels - the institutional level of what European infrastructure advisory becomes, and the philosophical level of what the framework’s analytical apparatus commits to under alternative conditions.

The chapter is explicit that the scenarios are not predictions. The scenarios are counterfactual rather than forecast. The chapter does not advance a claim that any one scenario is more likely than the others, and the analytical work the scenarios do does not depend on probability assessment. What the scenarios do is articulate trajectory paths whose conditions can be analysed through the framework’s analytical apparatus, with consequences for the four constituencies the recommendations of Chapter 9 then engage.

The two structural axes that produce the four scenarios emerge from the analytical chapters. The expertise location axis emerges from the framework’s distinction between contributory expertise (which resides in human practitioners reproduced through the integrated three-scale system) and the content that AI mediation can absorb (which resides in the technical systems through which the mediation operates). The two extreme cases - expertise concentrated in human practitioners, expertise concentrated in technical systems - define the axis. The sovereignty conditions axis emerges from Chapter 5’s political-economic argument: where AI mediation systems are produced and under whose ownership they operate. The two extreme cases - extractive Anglo-American commercial sovereignty (the current dominant trajectory), alternative sovereignty (European public-interest, firm-proprietary, or individually-owned alternatives) - define the axis.

The four scenarios are produced by the combinations of the two axes. The chapter develops each scenario in turn before identifying the cross-scenario findings.

8.3 Scenario one: Commodity Advisory

The project team is three people: a partner, a senior consultant, and a recent graduate running generation pipelines and approving outputs. Five years ago this engagement would have required eight people over four months. The work passes quality checks. Nobody has said out loud what the graduate is not learning.

The Commodity Advisory scenario is the trajectory where expertise concentrates in technical systems under extractive Anglo-American commercial sovereignty. European infrastructure advisory becomes absorbed into the generic capabilities of AI mediation systems whose institutional architectures are commercially structured around their sale as services to consulting firms, infrastructure clients, and adjacent institutional architectures.

The scenario operates as follows. Generic AI mediation matures across the components of advisory work that Chapter 7’s analysis identified - the formative tasks of Foundation stage, the deliverable production of Applied stage, increasingly the analytical components of Chartered-stage work. The cumulative effect is commoditisation: advisory work becomes replicable across firms through generic AI mediation, with distinctiveness compressed into a narrow band where senior contributory expertise still operates. The consulting profession does not abolish; it narrows, with value flowing upward to the platform vendors that own the AI mediation systems and inward to the senior practitioners whose contributory expertise has not been absorbed.

The Commodity Advisory scenario corresponds closely to what Acemoglu, Kong and Ozdaglar’s formal model treats as the path the system follows when agentic AI accuracy is sufficiently high and the stock of general knowledge is allowed to deplete unchecked 5 . Their model demonstrates that under these conditions, the system tips into a knowledge-collapse steady state where the community’s general knowledge vanishes despite high-quality individual decisions. The thesis’s reading of Commodity Advisory as the path of least resistance under current conditions is the philosophical-political-economic analogue of their formal result. The two registers converge on the same structural concern: that under unchecked extractive conditions, the system depletes even as individual outputs continue to look competent.

The consequences for the three ChMC stages are stark. Foundation-stage work is absorbed into AI mediation; Foundation-stage formation pathways collapse, with consequences for what Applied-stage practitioners can be formed into and what Chartered-stage practitioners can become two decades from now. Applied-stage work is commoditised; the deliverable-as-performance moat erodes; firm-distinctiveness compresses into a narrow band where senior practitioners still operate. Chartered-stage work is narrowed; senior advisory becomes the content that AI mediation cannot replicate, which is narrower than Chartered-stage advisory in current practice.

The consequences for the third box are negative. The answerability of European infrastructure advisory to the publics whose lives are shaped by infrastructure decisions depends on the content I treat as constitutive - contributory expertise reproduced through the integrated three-scale system, engagement with consequence, answerability across long time horizons. In the Commodity Advisory scenario, the content is absorbed into generic AI mediation, and the answerability operates through AI-mediated systems whose content is suited to extractive Anglo-American commercial sovereignty rather than to the European public-interest tradition.

Milan, 20xx. An Italian infrastructure advisory firm has lost three consecutive bids for energy regulatory strategy work to competitors who have structured their offerings around AI-mediated analytical production: faster turnaround, lower price point, outputs that cover the required regulatory categories in the required format. The firm’s partners are confident the outputs are analytically thinner - less specific to the Italian regulatory context, less attentive to ARERA’s particular institutional character, less capable of the strategic framing that has historically been the firm’s differentiator. The clients appear either not to notice the difference or not to weight it against the price gap. One partner prepares a presentation for the firm’s annual strategy day titled: The market is pricing our distinctiveness at zero. The conversation that follows is long. Nobody disputes the diagnosis. Nobody has a confident answer to what it implies.

The market-level evidence for this trajectory is measurable rather than projected. A mid-2026 industry analysis documents that all four major global consulting firms converged on the same two or three AI model vendors within approximately seven months - Deloitte deploying Claude to over 470,000 staff, Accenture deploying Copilot to 743,000 - and observes that these deployments, marketed as competitive advantages, represent “a slow, expensive way to disappear into your category” 6 . The analyst’s observation is, from the Commodity Advisory framework, exact: the same four workstreams, the same vendor shortlist, the same generic mediation apparatus, marketed as differentiation and operating as its structural opposite. The scenario the thesis treats as a thought-experiment is, at the market level, an ongoing process.

The consequences for the two scales of sovereignty are severe. National-cultural sovereignty is eroded as European public-interest practice becomes absorbed into generic AI mediation whose content is dominated by Anglo-American patterns. Organisational sovereignty is eroded as firm-distinctive ways of seeing become compressed under generic mediation that operates uniformly across firms.

Extraction operates in this scenario. Firm-externalised knowledge flows outward into vendor systems whose content is then recirculated through generic capabilities to competitors and clients. The dark mirror of the SECI model operates at commercial scale: what firms have historically reproduced as competitive distinctiveness becomes part of the generic distribution that AI mediation operates on.

The Commodity Advisory scenario is the trajectory I treat as most concerning. It is the trajectory toward which current conditions tilt, in the absence of institutional engagement with the concerns I name. Chapter 9’s recommendations are suited to engage the conditions under which this trajectory could be shifted.

8.4 Scenario two: The Digital Twin Economy

The procurement brief has a forty-page annex: technical specifications for sovereign AI deployment, including EU data residency requirements, national jurisdiction for training data, and regulatory inspection rights for model query logs. It is an advisory engagement, not an IT tender. The regulatory body issuing it has spent three years building the institutional architecture this annex requires. The firm reading it takes three days to decide whether to bid.

The Digital Twin Economy scenario is the trajectory where expertise concentrates in technical systems under alternative sovereignty conditions. European infrastructure advisory becomes absorbed into AI mediation systems, but the institutional architectures through which the mediation operates are European-public, firm-proprietary, or otherwise alternative to extractive Anglo-American commercial sovereignty.

The scenario operates as follows. The absorption of advisory work into AI mediation operates similarly to Commodity Advisory, but the institutional architectures of the AI mediation systems are different. European public-interest AI initiatives - oriented sovereign AI capability, European institutional architectures of model governance, public-interest training data curation - provide the content that mediation operates on. Firm-proprietary AI capabilities - developed within firms, trained on firm-distinctive material, governed through firm institutional architectures - provide alternative pathways for firm distinctiveness to be reproduced. The trajectory is similar to Commodity Advisory at the level of expertise location (it is concentrated in technical systems) but different at the level of sovereignty (the technical systems are governed through European public-interest or firm-proprietary architectures).

Brest, 2024. A French port authority has commissioned a digital twin of its logistics infrastructure under an EU-funded port digitalisation programme. The twin is built on a platform developed by a French technology consortium under the Programme d’Investissements d’Avenir AI framework - trained on French port operations data, hosted within the consortium’s infrastructure, governed by an agreement that keeps training data and model weights within French jurisdiction. An infrastructure advisory firm is brought in not to advise on port operations but on the governance architecture for the twin: who owns the model’s outputs, who can query it on what questions, what happens when the model’s recommendations conflict with the port authority’s own operational judgment, and how the twin’s advice should be documented for regulatory purposes. The engagement is not about port infrastructure. It is about the epistemic infrastructure for governing port infrastructure - a distinction the firm’s engagement scope had not previously needed to make.

The consequences for the two scales of sovereignty are positive. National-cultural sovereignty is preserved through institutional architectures of European public-interest AI capability. Organisational sovereignty is preserved through firm-proprietary AI capabilities that maintain firm-distinctive content.

Extraction operates differently in this scenario. Firm-externalised knowledge flows into AI mediation systems whose institutional architectures recognise firm ownership. Public-interest knowledge flows into AI mediation systems whose institutional architectures recognise public-interest ownership. The dark mirror of the SECI model is mitigated through institutional architectures that recognise what is being externalised.

The consequences for the three ChMC stages operate differently from Commodity Advisory. Foundation-stage work is absorbed but what is absorbed is European-public-interest rather than generic Anglo-American; Foundation-stage formation pathways are altered but formation is oriented to the European tradition. Applied-stage work is commoditised in technical terms but the commoditisation operates through institutional architectures that recognise European public-interest practice. Chartered-stage work operates as supervisory judgment within the technically mediated system, with content suited to the alternative sovereignty conditions.

The consequences for the third box are mixed. The answerability operates through AI-mediated systems, with content that recognises the third-box constituency through the institutional architectures of European public-interest practice. Whether the answerability is adequate depends on whether the institutional architectures of the alternative sovereignty are suited to the third box. The framework treats this content as institutionally available within European public-interest tradition but not automatically present; engagement with the third box requires institutional architectures even where expertise is concentrated in technical systems.

The Digital Twin Economy scenario is the trajectory I treat as requiring substantial institutional development to be realised. The institutional architectures it requires - European public-interest AI capability, firm-proprietary AI development, governance architectures for both - are present in early form in current practice but underdeveloped relative to what the scenario would require. Chapter 9’s recommendations are suited to engage the institutional development that this trajectory would require.

8.5 Scenario three: Artisanal Advisory

The lead partner has one standing instruction for her team: every analytical judgment in every client-facing document is owned by a named consultant with domain experience in the relevant sector. AI tools run the background research. The analytical judgment is human, identifiable, and answerable. The firm charges a premium. It has never lost a client who genuinely valued the distinction.

The Artisanal Advisory scenario is the trajectory where expertise concentrates in human practitioners under alternative sovereignty conditions. European infrastructure advisory continues to be reproduced through the integrated three-scale system Chapter 4 described, with institutional engagement that protects the formation pathway through which contributory expertise has historically been reproduced and operates within sovereignty conditions that recognise European public-interest practice.

The scenario operates as follows. AI mediation operates in advisory work but is institutionally bounded - its content is integrated into the three-scale system, not replacing its components. Foundation-stage formation pathways are protected through institutional architectures that recognise formation as constitutive of the profession. Applied-stage work continues to be the site of distinctive firm voice and practitioner-distinctive analytical content. Chartered-stage advisory continues to operate as the site of senior judgment, with content reproduced through sustained engagement with consequence over the arc of careers. The design principle that unifies these institutional choices is what Xu et al. (2026) call scaffolded AI friction: the deliberate introduction of cognitive resistance into AI-mediated processes to force active engagement rather than passive acceptance 7 . The Artisanal Advisory scenario implements this principle at the institutional rather than technical level - through the partner’s requirement that every analytical judgment be owned by a named practitioner, through formation pathways protected from generic mediation, through deliberate supervision structures that require practitioners to engage rather than accept. What Xu et al. identify as a design intervention for human-AI interfaces, the scenario implements as a formation architecture.

Acemoglu et al.’s formal model converges on the Artisanal Advisory scenario from a policy-design direction that complements the thesis’s philosophical reading 5 . Their welfare analysis identifies an information-design policy that maximises long-run welfare: a two-phase intervention consisting of a moratorium phase, in which agentic AI is suppressed to rebuild the depleted stock of general knowledge, followed by a permanent cap at a welfare-maximising level of AI precision. The Artisanal Advisory scenario is the political-economic analogue of what their welfare-optimal policy would produce: a long-run condition in which AI mediation operates within institutional architectures that protect formation pathways, recognise the public-interest tradition, and cap the substitution of AI for the formative engagements that reproduce contributory expertise.

Copenhagen, 2025. A Danish infrastructure advisory practice of twelve consultants has built its entire market position on a single commitment: all regulatory analysis is produced by a named senior consultant with specific domain experience in the sector the client operates in. The firm does not use AI-mediated drafting for deliverable content. It uses AI extensively for background research, data aggregation, and document search. The distinction is not a refusal of technology; it is a formation and quality assurance commitment - the analytical judgment in every client-facing document has been formed through genuine domain engagement. The firm is small. It charges a premium its larger competitors find implausible. Its client base is three major Danish infrastructure operators, one Scandinavian regulatory body, and two European infrastructure funds who have learned that when they need to understand what a regulatory development actually means for capital allocation, the Copenhagen practice will tell them something a platform cannot.

The consequences for the third box are positive. The answerability of European infrastructure advisory to the publics whose lives are shaped by infrastructure decisions operates through contributory expertise reproduced through the integrated three-scale system. The European public-interest tradition is preserved through institutional architectures that recognise advisory work as constitutive of public-interest practice.

The consequences for the two scales of sovereignty are positive. National-cultural sovereignty is preserved through institutional architectures that recognise European public-interest advisory practice. Organisational sovereignty is preserved through institutional architectures that recognise firm-distinctive practice.

Extraction operates in mitigated form. Firm-externalised knowledge flows through institutional architectures that recognise what is being externalised; the dark mirror of the SECI model is bounded by institutional architectures that recognise the consequences of unmitigated extraction.

The consequences for the three ChMC stages are positive. Foundation-stage formation pathways operate through institutional architectures that protect formation. Applied-stage work continues to be the site of firm-distinctive analytical voice and practitioner-distinctive contribution. Chartered-stage advisory continues to operate as the site of senior contributory expertise reproduced through the integrated three-scale system.

The Artisanal Advisory scenario is the trajectory I treat as most aligned with the European public-interest tradition. It is also the trajectory that requires the most institutional engagement to be realised. The institutional architectures it requires - formation pathway protection, procurement frameworks that recognise contributory expertise, disclosure norms that engage the third box, sovereignty architectures that recognise European public-interest practice - are present in fragmentary form in current practice but underdeveloped relative to what the scenario would require. Chapter 9’s recommendations to constituencies are suited to engage the institutional development that this trajectory would require.

8.6 Scenario four: Disintermediated Clients

The utility has brought the work in-house. The advisory firm still has an engagement - four senior conversations a year, no deliverables. Nine years of engagement knowledge, regulatory judgment, and institutional memory sit partly in the utility’s new AI platform and partly in the heads of three advisors who have gone in-house. The platform vendor manages the architecture. The utility’s board has not asked who owns the model weights.

The Disintermediated Clients scenario is the trajectory where expertise concentrates in human practitioners under extractive Anglo-American commercial sovereignty conditions, with the consequence that infrastructure clients build in-house AI capability that absorbs advisory work, and advisory practice operates within compressed engagement scopes where senior contributory expertise remains valuable but the institutional architectures of the consulting profession are narrowed.

The scenario operates as follows. Sophisticated infrastructure clients - energy utilities with substantial analytical functions, transport authorities with developed planning departments, regulatory bodies with technical capacity - build in-house AI capability that absorbs the analytical components of advisory work that have historically been consulting engagements. The consulting profession does not abolish but is reshaped: engagements compress to the components that in-house AI capability cannot reproduce, which is senior contributory expertise. The institutional architectures of the consulting profession - firm structures, formation pathways, what makes consulting consulting - are under pressure as engagements narrow.

Lisbon, 2024. ANACOM, the Portuguese regulatory authority for telecommunications and postal services, has deployed an AI-supported regulatory analysis platform that can process consultation documents, identify relevant precedents from European regulatory decisions, and produce preliminary analytical summaries within hours of a new regulatory filing. The platform does not replace ANACOM’s analytical staff; it accelerates the pre-analysis phase that previously required significant external advisory input. An advisory firm that has provided ANACOM with regulatory intelligence briefings for seven years has seen its engagement scope compress: the quarterly briefings, once analytical documents, are now primarily concerned with the questions the platform does not answer - specifically, the relationship between ANACOM’s formal regulatory positions and the political economy of the current government’s infrastructure and telecommunications priorities. The relationship persists. The firm is smaller than it was. ANACOM is, by any analytical measure, a more capable regulator than it was three years ago, and the advisory firm is providing a different kind of advice to a more informed client.

Extraction operates as the scenario’s defining dynamic. What was historically advisory expertise flows into in-house AI capability whose content is shaped by the institutional architectures of infrastructure clients rather than by the consulting profession. The firm’s engagement knowledge - accumulated through years of sustained advisory relationship - becomes training material for the client’s platform, governed by the technology vendor, subject to the vendor’s ownership and reuse conditions. The consulting profession’s institutional architecture is at risk under cumulative disintermediation pressure not from substitution by AI directly but from absorption through the client side.

The consequences for the two scales of sovereignty are negative. National-cultural sovereignty is eroded as European public-interest practice operates through extractive Anglo-American commercial AI mediation, even where the AI capability is nominally in-house at infrastructure clients. Organisational sovereignty is eroded as the institutional architectures of the consulting profession are reshaped under disintermediation pressure.

The consequences for the three ChMC stages are mixed. Foundation-stage work reduces in volume as in-house client AI capability absorbs the analytical components that have historically been Foundation-stage content; Foundation-stage formation pathways compress under reduced engagement scope. Applied-stage work reduces as engagement deliverables narrow; Applied-stage formation pathways compress correspondingly. Chartered-stage work continues to operate where senior contributory expertise remains valuable, but the institutional architecture within which it operates is reshaped.

The consequences for the third box are mixed. The answerability of advisory work to the publics whose lives are shaped by infrastructure decisions operates through Chartered-stage senior contributory expertise that continues in the scenario. But the institutional architectures through which the answerability has historically operated - through firm-mediated engagement, through the integrated three-scale system, through European public-interest advisory practice - are under pressure. Whether the answerability survives the institutional reshaping depends on whether the in-house AI capability that infrastructure clients develop is suited to the third box.

The Disintermediated Clients scenario is the trajectory I treat as threatening to the institutional architectures of the consulting profession even where senior contributory expertise remains valuable. It is the trajectory that emerges from current procurement practices in some infrastructure subdomains, where in-house AI capability development is underway and engagement scopes are compressing.

8.7 A supplementary thought-experiment: the Knowledge Commons

A European infrastructure advisory consortium - nineteen members: transport authorities, energy regulators, water utilities, two national infrastructure banks, six private advisory practices across four national jurisdictions - has operated a shared AI platform for seven years. Eleven years of aggregated project data: regulatory submissions, infrastructure assessments, procurement strategy documents, post-project evaluations from engagements in transport, energy, water, and port governance across the consortium’s member jurisdictions. The platform is governed collectively, its training data contribution rights distributed by sector and jurisdiction, its model weights owned by the consortium’s legal entity, its governance architecture designed by a Dutch public-law firm specialising in intellectual commons. A junior analyst in Lisbon, twenty-six years old, three years into her career, works with the platform daily. She is competent. She produces contextually specific, sector-appropriate regulatory analysis that her supervisors recognise as professional work. She has never built an analysis from scratch that she did not abandon when the platform suggested something better - because the platform, trained on eleven years of aggregated expert judgment across nineteen organisations, consistently suggests something better. What she cannot do is say what she would have seen without the platform’s prior framing. She cannot say whether the judgment she exercises is hers.

This thought-experiment operates outside the four-quadrant structure of the chapter’s scenarios. The four scenarios - Commodity Advisory, Digital Twin Economy, Artisanal Advisory, Disintermediated Clients - are defined by their positions on two axes: where expertise lives and under whose sovereignty AI operates. The Knowledge Commons does not occupy a fifth position on those axes. It is a qualitatively different institutional arrangement that resolves some of the concerns the four scenarios raise while leaving others intact - and intensifying still others. It is included here because its resolution of sovereignty and its failure to resolve formation together illuminate what is genuinely distinct about the formation question: that it is not a sovereignty problem, and cannot be solved by sovereignty solutions.

What the commons resolves. The sovereignty concerns identified across the four scenarios - the dual-scale threat to national-cultural and organisational sovereignty - are addressed by a well-designed commons. Extraction becomes symmetric: knowledge flows into the shared platform and returns to contributing institutions, governed by the consortium’s collective ownership architecture. The dark mirror of the SECI model is turned; what firms externalise they co-own, and the extractive asymmetry that the dark-mirror argument identifies is structurally eliminated. National-cultural sovereignty is preserved through governance design: the consortium’s training data architecture ensures that European public-interest practice, European regulatory traditions, and European institutional patterns remain the epistemic content on which the platform operates. Organisational sovereignty persists through sector- and jurisdiction-differentiated contribution rights: firms contribute expertise within their domains and draw from the collective across them. The third box is partially addressed: the platform’s governance architecture is expressly public-interest in design, and the consortium’s mandate can be constitutionally oriented to the infrastructure publics the third box names. The productivity floor rises across all nineteen organisations: junior practitioners work at a level of contextual sophistication that would have required years more formation to reach independently.

What the commons does not resolve. The sovereignty resolution is real. The formation deficit is not touched.

Cross-scenario Finding 1 holds. The commons produces interactional expertise at scale - the capacity to engage the domain’s language, apply its regulatory precedents, produce outputs that read as professionally competent - because that is what eleven years of aggregated expert judgment, encoded and made queryable, can support. What it cannot produce is contributory expertise. Contributory expertise is formed through sustained engagement with consequence: through the accumulation of Erfahrung across encounters with difficulty, through the discomfort of analytical failure, through the forced development of independent judgment under conditions where the platform is not available or has not yet encountered the problem 8 9 . The commons has no mechanism for this. It makes Erfahrung unnecessary; it makes independent judgment formation structurally difficult to pursue. The analyst in Lisbon is interactionally fluent and contributorily hollow.

Cross-scenario Finding 2 holds - and under commons conditions is rendered harder to see. In the four scenarios, the formation deficit is at least legible: in Commodity Advisory, it is visible as the collapse of Foundation-stage pathways; in Artisanal Advisory, its visibility is the institutional motivation for the scenario’s defining choices. In the Knowledge Commons, the formation deficit is concealed by the contextual sophistication of the commons’s outputs. Because the platform is trained on genuine European public-interest practice - not generic Anglo-American patterns - its outputs are analytically appropriate, jurisdictionally accurate, institutionally calibrated. The junior analyst’s work, shaped by the platform, reads as formed. The profession-wide distribution of this concealment is what makes it analytically dangerous: where individual firms in Commodity Advisory might notice that their juniors are producing thin work, the commons makes thin formation uniformly look like thick competence across all nineteen organisations simultaneously. The false proficiency that Ke et al. document at the individual level 10 now operates at the scale of an ecosystem.

Cross-scenario Finding 7 holds. The commons’s architecture of specialised contribution within domains and cross-domain draw creates a form of engagement that systematically forecloses cross-domain integrative judgment. Practitioners contribute their domain expertise to the commons; they draw from the commons across domains; but they never form the capacity for integrative cross-domain judgment through sustained cross-domain engagement, because the commons makes sustained engagement unnecessary. The Applied stage has no safe trajectory under commons conditions any more than it does in the four scenarios. The analytical function that connects Foundation formation to Chartered authority - where the practitioner learns to hold multiple domains in view simultaneously, to make integrative judgments under uncertainty - is bypassed rather than developed.

What the commons intensifies. Three concerns are intensified under commons conditions rather than simply preserved alongside their four-scenario counterparts.

The Morozov circularity is most acute under commons governance. Morozov (2026) identifies the circularity that afflicts any attempt to govern AI systems through value commitments: the values we would use to govern these systems are themselves being formed through our encounters with those systems 11 . In the four scenarios, this circularity operates with some external reference: in Artisanal Advisory, the pre-commons tradition of formative apprenticeship provides an evaluative standard not itself produced by the mediation; in Commodity Advisory, the recognition that something has been lost presupposes a reference point outside the current system. In the Knowledge Commons, no external reference point remains available at the profession-wide level. The commons is constituted by the accumulated professional judgments of its contributing institutions; the evaluative standard for those judgments is produced by the commons; the governance choices about how to develop the commons are made by practitioners whose evaluative frameworks the commons has shaped. The circularity is closed. Whether the commons is adequate cannot be answered from outside it.

False proficiency, documented by Ke et al. as an individual-level phenomenon, is amplified to ecosystem scale. Under commons governance, because the platform’s outputs are genuinely contextually calibrated, the gap between interactional competence and contributory formation is invisible in any individual practitioner’s work, in any firm’s outputs, and across the consortium. There is no comparative benchmark that makes the deficit visible: the ecosystem has collectively converged on the platform’s analytical framework, and internal comparison confirms adequacy at every level.

Cross-domain judgment erosion is intensified rather than created by the commons. Practitioners contribute domain expertise and draw across domains through the platform but never form cross-domain integrative capacity through sustained cross-domain engagement, because the commons makes sustained engagement unnecessary. Over a decade, the advisory ecosystem stratifies into well-supported specialists whose integrative capacity is platform-dependent and therefore unavailable in precisely the conditions where the platform’s training data has no precedent - the genuinely novel regulatory problem, the multi-sector interaction with no prior characterisation in eleven years of data.

The commons and the Artisanal pairing. The Knowledge Commons thought-experiment exists in this chapter primarily to clarify the Artisanal Advisory scenario by contrast. What the commons demonstrates is that sovereignty and formation are genuinely independent problems requiring genuinely independent institutional responses. A commons that comprehensively resolves sovereignty - collective ownership, symmetric extraction, European public-interest content, governance architecture oriented to the third box - leaves the formation deficit structurally intact. Artisanal Advisory is defined not by its resolution of sovereignty (it does not resolve sovereignty comprehensively; it bounds the sovereignty risk through institutional choices about how AI mediation operates) but by its additional institutional choices about how formation happens: the protection of Foundation-stage formation pathways, the institutional refusal to absorb the formative components of Applied-stage practice, the governance of AI mediation as a tool rather than a substitute. These choices are independent of sovereignty architecture. They would be needed inside a commons as much as outside one.

The European infrastructure advisory ecosystem, under Knowledge Commons conditions, becomes uniformly adequate. Nineteen organisations, across four national jurisdictions, produce contextually appropriate, jurisdictionally calibrated, institutionally attentive advisory work at a level of sophistication that would have required decades of accumulated expertise to reach without the platform. The adequacy is real. The productivity floor is genuinely higher. The third-box constituency is better served by adequate professional advice than by its absence. None of this is to be dismissed.

But the analyst in Lisbon, at twenty-six, cannot form what the commons makes unnecessary to form. At thirty-six, she will be interactionally fluent at the level of a practitioner with fifteen years of formation - and contributorily adequate at the level of a practitioner who has never needed to form independently. The gap will not be visible in her outputs. It will not be visible in her organisation’s outputs. It will not be visible across the ecosystem. The formation question has not been resolved; it has been made invisible at the scale of an ecosystem whose uniform adequacy forecloses the institutional recognition that adequacy and formation are not the same thing.

8.8 Cross-scenario findings: what holds across all four

The chapter’s contribution is seven cross-scenario findings - concerns that hold across all four scenarios regardless of which trajectory unfolds. These findings provide robust ground for the recommendations in Chapter 9 because they are suited to concerns that hold across the trajectory variation, not to any single trajectory.

First cross-scenario finding: the contributory/interactional distinction is the primary structural determinant of professional value. Across all four scenarios, what AI mediation reproduces at scale is interactional expertise - the capacity to speak a domain’s language, engage its practitioners, and produce outputs that read as competent. What it cannot reproduce is contributory expertise: knowledge formed through sustained engagement with consequence that enables genuine contribution to the domain’s development 8 . This distinction is the load-bearing mechanism beneath all findings that follow. The formation question (Finding 2) matters because formation is the pathway through which interactional competence becomes contributory expertise. The sovereignty question (Finding 3) matters because whose posture structures the mediation determines whose contributory framework operates. The third-box question (Finding 4) matters because it is contributory expertise - not interactional fluency - that sustains public-interest engagement under genuine uncertainty. The legitimacy narration question (Finding 5) matters because explicit narration is how contributory expertise is made legible when interactional fluency is reproducible by agents. What is at stake across all four scenarios is whether the institutional conditions under which contributory expertise is reproduced and made legible can be sustained.

Second cross-scenario finding: the formation question becomes inescapable. Across all four scenarios, how the consulting profession reproduces contributory expertise is at stake. In Commodity Advisory, formation pathways collapse as Foundation-stage work is absorbed. In Digital Twin Economy, formation pathways are altered to operate within technically mediated systems. In Artisanal Advisory, formation pathways are protected through institutional engagement. In Disintermediated Clients, formation pathways compress under reduced engagement scope. The formation question - what is being formed, how it is being formed, what institutional architectures support the formation - is present in all four scenarios. The formation question cannot be avoided; it can only be engaged through institutional choices I treat as important.

This second finding - that the formation question becomes inescapable across all four scenarios - is the philosophical-political-economic correlate of what Acemoglu et al. derive as the central result of their formal model: that human effort produces both private decision-quality and a public good (the community’s general knowledge stock), and that the public good is what makes future human effort productive 5 .

Third cross-scenario finding: sovereignty pressure operates across multiple scales. Across all four scenarios, where AI mediation operates under whose sovereignty is at stake. National-cultural sovereignty (the distinctiveness of European public-interest practice) and organisational sovereignty (the distinctiveness of firm-level analytical voice) operates across all four scenarios with different force. The sovereignty pressure cannot be avoided; the question is what institutional architectures recognise sovereignty at multiple scales.

Fourth cross-scenario finding: the third-box question persists. Across all four scenarios, how the publics whose lives are shaped by infrastructure decisions are engaged is at stake. The third-box constituency - the publics who bear consequences without holding contracts, including the future generations whose conditions of life are being shaped now - operates across all four scenarios with different force. The third-box question cannot be avoided; the question is what institutional architectures recognise the third box in each trajectory.

Fifth cross-scenario finding: explicit legitimacy narration becomes inescapable. Across all four scenarios, professional legitimacy requires explicit institutional narration. The implicit legitimacy that has historically operated through institutional architectures of expertise, formation, and senior practice is insufficient in all four scenarios. Legitimacy now requires institutional architectures of explicit narration: what is being done, who is doing it, what AI mediation operates, what content the practitioner is contributing. Explicit legitimacy narration cannot be avoided; the question is what institutional architectures support the narration in each trajectory.

Sixth cross-scenario finding: extraction operates structurally across all four scenarios. The variable is not whether knowledge flows outward from European advisory practice into the generic mediation apparatus - it does, in all scenarios - but through what institutional architecture and under whose ownership. In Commodity Advisory, extraction is unmediated: junior outputs feed training processes, accelerating the substitution that displaces them. In the Digital Twin Economy, extraction operates through the technical layer: the firm’s analytical posture is encoded in the twin’s configuration, portable and legible. In Artisanal Advisory, extraction is actively contested: the defining institutional choices of the scenario are precisely those that limit its scope and govern the terms on which the posture circulates. In Disintermediated Clients, extraction is client-side: the client’s direct AI tools absorb the advisory posture the firm historically provided. The question shifts from ‘are we at risk of extraction?’ - all four scenarios answer yes - to ‘what are the ownership conditions of the extraction already happening?’

Seventh cross-scenario finding: the Applied stage has no safe trajectory in any scenario. In Commodity Advisory, Applied practice is commoditised from below as AI mediation absorbs deliverable production, and squeezed from above as Chartered-level authority becomes the defensible asset. In the Digital Twin Economy, Applied practice is technically reconfigured: the consultant becomes a system-integration and quality-assurance function, exercising judgment through configuration rather than direct analytical contribution. In Artisanal Advisory, the Applied stage is the scenario’s defended constituency - which is to say it is otherwise at risk, and the institutional design choices that define the scenario are partly constituted by the refusal to accept Applied-stage substitution. In Disintermediated Clients, the Applied stage is disintermediated outright. Applied-stage vulnerability is structurally distinct from both the Foundation-stage formation argument and the Chartered-stage senior-judgment argument: it concerns the intermediary analytical function - where interactional fluency and early contributory capacity combine - that connects formation to authority, and deserves its own institutional design logic.

These seven cross-scenario findings together constitute the contribution of the futures analysis. Chapter 9’s recommendations to constituencies are suited to engage these concerns rather than to advocate for any single trajectory. The recommendations are robust to trajectory variation because they operate at the level of cross-scenario findings, not trajectory-specific institutional architectures.

8.9 The cross-scenario ground

Four scenarios, two structural axes, one consistent pattern. Across Commodity Advisory, Digital Twin Economy, Artisanal Advisory, and Disintermediated Clients, the framework’s seven findings hold: the contributory/interactional distinction structures what AI mediation can and cannot displace; formation is at structural risk wherever AI mediation absorbs the formative components of advisory work; sovereignty is at risk wherever generic mediation operates without European contextual alignment; the third box is further removed wherever the formation pathway that connects junior practice to public-interest consequence is disrupted; legitimacy requires explicit narration wherever the implicit institutional architectures that have historically supported it are under pressure; extraction is operating in all scenarios, with ownership conditions as the institutional question; and the Applied stage faces no safe trajectory and requires its own institutional design logic. The variation across scenarios is real - each scenario produces a distinctive pattern of these findings - but the findings themselves are robust across the trajectory space.

The scenarios are philosophical thought-experiments, not probability assessments. Their purpose is to stress-test the framework against alternative trajectory paths and to establish that the recommendations Chapter 9 develops are not specific to a single anticipated future. The ground the chapter establishes is the cross-scenario robustness of those recommendations.

The scenarios have stress-tested the framework. Chapter 9 takes what holds across them - the seven cross-scenario findings - into recommendations for the constituencies whose decisions shape the trajectory.