TECTEC-001 — Integration Architecture Weaknesses
AI Bargaining Inefficiencies from Information Asymmetry in Multi-Agent Systems
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Multi-agent AI systems engaged in negotiation produce suboptimal or failed agreements when operating under uncertainty about counterparty valuations and alternatives. Organisations deploying such systems risk material value destruction and unpredictable contractual outcomes without governance controls over inter-agent bargaining behaviour.
Domain
Technical Implementation
Blindspots in integration architecture, deployment, performance, data pipelines, security architecture, and maintenance.
Source
MIT AI Risk Repository — Multi-Agent Risks from Advanced AI (Hammond2025) ↗https://airisk.mit.edu/
Could this happen in your organisation?
A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.