Track: Track 2: Socio-Economical and Future Visions
Keywords: cross-border legal services, trust work, commodity cognition, AGI, legal assurance engineer, market structure, auditability, dispute resolution, pricing models, risk allocation, governance artifacts, model passports, professional responsibility, agentic workflows, negotiation strategy, arbitration, compliance, platform economics, legal technology, verification
TL;DR: As AI commoditizes drafting, value shifts to trust work like risk allocation. This paper forecasts a split between volume platforms and assurance boutiques, proposing a "Legal Assurance Engineer" role to create defensible, auditable commitments.
Abstract: Track 2 asks how ubiquitous advanced AI reshapes labor markets in knowledge-intensive domains. We forecast a specific reorganization of cross-border legal services: as general-purpose systems commoditize research, translation, and first-draft drafting, the scarce input becomes trust work—the production of defensible commitments under uncertainty. We formalize a decomposition of legal value into low-marginal-cost commodity cognition and high-assurance trust work (risk allocation, negotiation strategy, governance of agentic workflows, and accountability artifacts). From this decomposition we derive three market-structure hypotheses: (i) further erosion of time-based billing toward subscription, outcome-linked, and risk-sharing fees; (ii) bifurcation between high-volume legal platforms and high-assurance boutiques differentiated by auditability and reputational capital; and (iii) growth of dispute-resolution design as a complementary market because enforcement risk becomes the main brake on transaction velocity. We propose a new professional role—Legal Assurance Engineer—and outline a Tiny-Paper evaluation plan that maps tasks in a representative cross-border deal to substitutable cognition, trust requirements, and failure costs, then tests how governance artifacts (logs, model passports, solver-checked reasoning, and disclosure clauses) shift those costs.
Anonymization: This submission has been anonymized for double-blind review via the removal of identifying information such as names, affiliations, and identifying URLs.
Submission Number: 39
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