From the 1 of 8 linked papers with an AI index.
8 papers
One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI
Gaston Besanson
Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can admit, degrade, or remediate an…
SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation
Gaston Besanson
The paper studies how agentic AI systems can unknowingly act on stale or incorrect metadata, leading to costly mistakes, and proposes a runtime data‑quality gate that detects such…
Green SARC: Predictive Cost and Carbon Governance for Agentic AI Systems
Gaston Besanson
Agentic AI systems act through tools and sub-agents, yet the controls meant to bound their financial and environmental cost still sit on dashboards evaluated beside or after execut…
SARC: A Governance-by-Architecture Framework for Agentic AI Systems
Gaston Besanson
Agentic AI systems increasingly act through tools, sub-agents, and external services, but governance controls are still commonly attached to prompts, dashboards, or post-hoc docume…
The Inference Bottleneck: A Formal Model of Vertical Foreclosure in AI Markets
Gaston Besanson
As generative AI commercializes, competitive advantage is shifting from model training toward inference, distribution, and routing. This paper develops a formal game-theoretic mode…
The Data Hydration Gap: A Formal Model of Underinvestment in General-Purpose Data Products Under Decentralized Governance
Gaston Besanson
When organizations decentralize data product ownership, as in the data mesh paradigm, each domain team optimizes for its immediate analytical needs, underinvesting in the cross-dom…